Best : Journal of Applied Electrical, Science and Technology
type: channel
description: a Journal that contain Applied Electrical, Science & Technology. Published twice a year, in March and September. P-ISSN: 2715-2871(print); E-ISSN: 2714-5247 (online)
publisher: Universitas PGRI Adi Buana Surabaya
language: en
publication name: Best : Journal of Applied Electrical, Science and Technology
issn: 2715-2871
items: Performance Analysis of the 110 VDC Battery System in the DC System of the 150 kV Soppeng Substation
items: The Development of Train Artificial Intelligence (AI) Model for Bagapit Chess (Catur Bagapit) Engine using Random Forest Regressor Algorithm : a Traditional Game from Kalimantan, Indonesia
items: Deep Learning Approach for Identifying Fresh and Rotten Chili Peppers using YOLO
items: Development Of Fiber Optic Practicum Learning Media Based On Virtual Reality
items: Automated and Efficient Monitoring System for Organic Waste Compost Processing based on The Internet of Things (IoT)
items: Enhancing Cluster-Based SMOTE with kNN-Based Post-Oversampling Cleaning for Robust Health Risk Prediction
items: A Systematic Literature Review of Convolutional Neural Networks for Gender Analysis using Fingerprint Images and other Biometric Modalities
items: Design of an Internet of Things (IoT) based Main Reservoir Water Level Measuring Device at Siti Hajar Hospital Sidoarjo
items: Integration of Concatenated Deep Learning Models with ResNet Backbone for Automated Corn Leaf Disease Identification
items: Filling Machine Panel Retrofit into Arduino Nano-Based Digital System at CV Sarana Engineering
items: Design and Development of a Geographic Information System for Historical Tourism Sites in Sumenep Regency Using the Location-Based Service Method
items: P2GS Web-Based E-CRM with WhatsApp API for MSME Customer Engagement
items: Short Circuit Current Analysis and Recloser Coordination in 20 kV Distribution Network Using Manual Calculation and ETAP Software Simulation
items: Design of Omniwheel Kinematics Learning Platform using ESP32 and Microsoft Visual Studio
items: Application of Knowledge Based Method in Mobile Application-Based Cat Feed Recommendation System
items: Design and Construction of Pharmacy Sales Information System
items: Design and Development of a Web-Based Employee Attendance and Payroll Information System at CV Expressa
items: Design and Construction of Web-Based Budgeting Submission Information System at CV Expressa
items: Development of A Machine Learning Based Chess Game in Python
items: Handling Imbalanced Fraudulent Transaction Data Using SMOTE-Tomek and Random Forest: A Classification Approach
items: Implementation of Decision Tree and Item Response Theory (IRT) in SIMPATIF (Sistem Penilaian Adaptif)
items: TensorFlow Based AI Training for Translating Indonesian Sign Language (BISINDO)
items: Design and Simulation Sag Tension of a 20kV Power System with 150kV Tower Infrastructure in Marabahan City with Monte Carlo method
items: Artificial Intelligence System for Face Detection to Identify Passenger Identity at the Airport
items: Design, Build, and Implement Monitoring Applications Student Grades and Violations
items: Implementation of Charity Box Security System based on Internet of Things (IoT) using Sensor and Notifications
items: Smart Backpack Solution for Child Safety Monitoring using GPS Tracker and Internet of Things (IoT)
items: Implementation of Face Detection Login System using Python
items: Soil Moisture and PH Control Device in Sprout Cultivation
items: Design and Construction of Power Monitoring and Circuit Breaker Devices for PLN Customers based on IoT

Performance Analysis of the 110 VDC Battery System in the DC System of the 150 kV Soppeng Substation
type: item
description: Soppeng Substation is an important part of the electrical power transmission system that requires high operational reliability. One of the components that supports this reliability is the 110 VDC battery system, which functions as a backup power source for protection, control, and telecommunication equipment when the AC supply is disrupted. This study aims to analyze the feasibility of the 110 VDC battery system at the Soppeng Substation based on cell voltage, battery bank voltage, charging system performance, and the battery's ability to support DC loads. The research method includes field observations, technical measurements, and analysis of operational data collected from September to November 2025. The results show that the battery bank voltage is 119.4 V for Battery Bank 1 and 123.0 V for Battery Bank 2, with cell voltage deviations of 0.14 V and 0.18 V, respectively, which are still within the allowable limits. The rectifier output voltage ranges from 123.0–123.1 V with a current of about 6.5–6.6 A under float charging conditions. The battery capacity is able to support a DC load of 13.1 A, indicating that the battery system is feasible and reliable as a backup power source.
subject: Contents of the Journal
  topic: section
subject: 110 VDC battery, substation, battery bank, rectifier, DC system
  topic: keywords
creator: Tony Koerniawan
creator: Fajar Sabri Saputra
creator: Novi Gusti Pahiyanti
creator: Ayu Febrina Rizal
creator: Sugeng Purwanto
creator: Aas Wasri Hasanah
creator: Sigit Sukmajati
creator: Evi Suhaevi
rights: Copyright (c) 2026 Tony Koerniawan, Fajar Sabri Saputra, Novi Gusti Pahiyanti, Ayu Febrina Rizal, Sugeng Purwanto, Aas Wasri Hasanah, Sigit Sukmajati, Evi Suhaevi https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 41
ending page: 53
doi: 10.36456/ct2z2e83

The Development of Train Artificial Intelligence (AI) Model for Bagapit Chess (Catur Bagapit) Engine using Random Forest Regressor Algorithm : a Traditional Game from Kalimantan, Indonesia
type: item
description: Bagapit Chess (Catur Bagapit) is a traditional strategy board game originating from the Kalimantan region of Indonesia. Despite its rich cultural heritage and strategic depth comparable to international Chess, Bagapit Chess remains largely unstudied from a computational intelligence perspective. This paper presents the development of an Artificial Intelligence (AI) model for the Bagapit Chess engine using the Random Forest Regressor (RFR) algorithm. The AI model is trained to evaluate board positions and generate competitive move decisions through a heuristic evaluation function augmented by machine learning. A dataset of 15,000 annotated game positions was constructed from expert gameplay, encoding board features including piece Material Advantage, Chess Movement, Defense Stance, mobility, and Attack Coverage across the 8×8 Bagapit board. The Random Forest Regressor model was integrated with a Negamax search tree enhanced by Alpha-Beta Pruning to achieve efficient and intelligent move selection. The trained model achieved an R² score of 0.9134, a Mean Absolute Error (MAE) of 0.0872, and a Root Mean Squared Error (RMSE) of 0.1104 on the test set. In engine evaluation against a rule-based baseline, the AI model won 84.2% of games under standard time control. This study contributes to the digitalization and preservation of Indonesian traditional games and demonstrates the applicability of ensemble machine learning to non-standard board game engines.
subject: Contents of the Journal
  topic: section
subject: Bagapit Chess,
  topic: keywords
subject: Bagapit Chess Engine
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
subject: Random Forest Regressor
  topic: keywords
subject: Negamax with Alpha-Beta Pruning
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: Dwi Hastuti
creator: Harits Ar Rosyid
creator: M. Zainal Arifin
rights: Copyright (c) 2026 Dwi Hastuti, Harits Ar Rosyid, M. Zainal Arifin https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 19
ending page: 26
doi: 10.36456/eab74t67

Deep Learning Approach for Identifying Fresh and Rotten Chili Peppers using YOLO
type: item
description: Chili peppers are a vital agricultural commodity, yet post-harvest quality assessment primarily relies on manual inspection, which is subjective, labor-intensive, and prone to inconsistency. This study proposes a deep learning-based computer vision system using the You Only Look Once (YOLO) framework to automate the identification and classification of fresh and rotten chili peppers. The model was trained using a dataset of 400 web-crawled images, annotated and augmented to handle visual diversity. A novel evaluation strategy was employed using synthetic image generation to simulate real-world scenarios, including neatly arranged grids and randomly distributed objects with varying orientations. Experimental results demonstrate that the proposed model effectively localizes and classifies chili peppers with confidence scores ranging from 0.55 to 0.90. The system successfully distinguishes between fresh and rotten categories even under conditions of intra-class variation, such as discoloration and shriveling. These findings validate the robustness of the YOLO-based approach, offering a promising, efficient solution for automated post-harvest quality control and smart agriculture applications
subject: Contents of the Journal
  topic: section
subject: Deep Learning
  topic: keywords
subject: YOLO
  topic: keywords
subject: Chili Pepper
  topic: keywords
subject: Quality Assessment
  topic: keywords
subject: Synthetic Image Generation
  topic: keywords
creator: Akbar Sujiwa
creator: Nailul Hasan
creator: Fajar Timur
creator: Reffany C. Rizkiarna
rights: Copyright (c) 2026 Akbar Sujiwa, Nailul Hasan, Fajar Timur, Reffany C. Rizkiarna https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 61
ending page: 66
doi: 10.36456/4gmxqj65

Development Of Fiber Optic Practicum Learning Media Based On Virtual Reality
type: item
description: The rapid development of multimedia technology has encouraged innovation in learning media, particularly for practical-based courses. Fiber optic practicum learning requires direct practice, specialized equipment, and adequate laboratory facilities, which often become constraints, especially during distance learning conditions. This final project aims to develop a virtual reality–based learning media for fiber optic practicum to support students’ understanding of practical procedures in a more interactive and immersive manner.The development process utilizes Blender as a 3D modeling and animation tool to design laboratory environments and fiber optic practicum equipment, including stripper, cleaver, fusion splicer, optical power meter, and fiber optic cables. Verge3D is used to create interactive animations and integrate the models into a virtual reality environment. The learning media simulates key practicum stages, such as cable stripping, cutting, splicing, and attenuation measurement using an optical power meter.The resulting virtual reality learning media allows users to experience fiber optic practicum activities in a simulated laboratory environment as if performing real practices. This media is expected to function as an alternative learning tool that enhances students’ understanding, motivation, and readiness before conducting actual fiber optic practicum in the lab.
subject: Contents of the Journal
  topic: section
subject: virtual reality
  topic: keywords
subject: learning media
  topic: keywords
subject: fiber optic practicum
  topic: keywords
subject: Blender 3D
  topic: keywords
creator: Dimas Saputra
creator: Mohammad Fadhli
creator: Martinus Mujur Rose
rights: Copyright (c) 2026 Dimas Saputra, Mohammad Fadhli, Martinus Mujur Rose https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 9
ending page: 18
doi: 10.36456/f9chnw88

Automated and Efficient Monitoring System for Organic Waste Compost Processing based on The Internet of Things (IoT)
type: item
description: In developed countries, waste has been regarded as an important component of management systems as well as reuse practices. In contrast, developing countries, particularly Indonesia, still face various challenges in waste management. Approximately 60% of the total national waste generation originates from household waste, and about 39.98% of this amount has not been optimally managed. Processing organic waste into compost is an environmentally friendly alternative that can reduce waste volume while increasing the value of household and agricultural waste. However, conventional composting methods often encounter difficulties, especially in maintaining temperature and moisture stability, causing the decomposition process to be less optimal. Based on these issues, this study aims to design and implement an automated efficiency and monitoring system for compost processing based on the Internet of Things (IoT). The developed system utilizes an ESP32 microcontroller, a soil moisture sensor for moisture measurement, a DS18B20 sensor for compost temperature monitoring, as well as an automatically controlled water pump and a 12 V DC fan. Sensor data are transmitted in real time to the Blynk platform for remote monitoring purposes. The experimental results indicate that the system is capable of maintaining moisture levels within the ideal range of 50–60% and compost temperature within the optimal range of 30–40°C, enabling the composting process to operate more stably, efficiently, and in a controlled manner.
subject: Contents of the Journal
  topic: section
subject: Compost
  topic: keywords
subject: Internet of Things
  topic: keywords
subject: ESP32
  topic: keywords
subject: Sensors
  topic: keywords
subject: monitoring
  topic: keywords
creator: Lilik Sugiarto
creator: indrawan ady saputra
creator: Robi Wariyanto Abdullah
rights: Copyright (c) 2026 Lilik Sugiarto, indrawan ady saputra, Robi Wariyanto Abdullah https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 1
ending page: 8
doi: 10.36456/7madhs96

Enhancing Cluster-Based SMOTE with kNN-Based Post-Oversampling Cleaning for Robust Health Risk Prediction
type: item
description: Class imbalance is a common problem in health datasets and often leads to poor recognition of the minority (disease) class. NR-Clustering-SMOTE is a cluster-based oversampling method that combines noise reduction, K-Means clustering, and SMOTE with a modified distance metric to improve classification performance on imbalanced health data. However, the original method only performs noise reduction before SMOTE, so noisy synthetic samples generated around borderline or highly overlapped regions may still degrade classifier performance and introduce epistemological bias in the learned decision rules. This paper proposes a lightweight extension called NR-CluSMOTE-KNC (NR-Clustering-SMOTE with Post-SMOTE k-NN Cleaning). After the standard NR-Clustering-SMOTE pipeline, a k-nearest neighbour filter is applied solely to synthetic minority samples; synthetic points that are surrounded predominantly by majority neighbours are identified as extreme noise and removed. On the Pima Indians Diabetes dataset using Random Forest, the proposed method improves accuracy from 0.8481 (baseline NR-Clustering-SMOTE) to 0.8589 with NR-CluSMOTE-KNC, accompanied by consistent gains in G-Mean and AUC. These results indicate that a simple post-SMOTE cleaning step can epistemologically refine the representation of minority concepts in the data, producing more reliable and fair predictive models for health decision support.
subject: Contents of the Journal
  topic: section
subject: Imbalanced Data
  topic: keywords
subject: SMOTE
  topic: keywords
subject: NR-Clustering_SMOTE
  topic: keywords
subject: epistemology
  topic: keywords
subject: post-SMOTE cleaning
  topic: keywords
creator: Mohamad Ilham
creator: Akhmad Solikin
creator: Syaad Patmanthara
rights: Copyright (c) 2026 Mohamad Ilham, Akhmad Solikin, Syaad Patmanthara https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 67
ending page: 71
doi: 10.36456/a9k8xq74

A Systematic Literature Review of Convolutional Neural Networks for Gender Analysis using Fingerprint Images and other Biometric Modalities
type: item
description: This study systematically reviews the application of Convolutional Neural Networks (CNN) for gender classification using fingerprint images as a biometric identifier. CNN demonstrate a strong ability to automatically extract ridge and texture features that differentiate male and female fingerprints. Using the PRISMA 2020 framework, a Systematic Literature Review (SLR) was conducted on 15 Scopus-indexed studies published between 2020 with 2025, focusing on CNN-based fingerprint gender recognition. The review reveals that CNN models achieved accuracy ranging from 85% to 99.97%, depending on the network architecture, dataset size, and training strategy. Architectures such as VGG16, GoogleLeNet, AlexNet, EfficientNetB0, and Hybrid Model CNN–LSTM or CNN–SVM performed best, especially when enhanced with data augmentation and transfer learning. Interpretability methods such as Grad-CAM improve model transparency by visualizing fingerprint regions influencing gender prediction. Although the trend in accuracy slightly declined after 2023 due to dataset diversity and overfitting in deeper models, CNN remains the dominant and most reliable approach in biometric analysis.
subject: Contents of the Journal
  topic: section
subject: biometric, CNN, fingerprint, deep learning, gender
  topic: keywords
creator: Zuhdi Fatkhurrahman
creator: Budi Murtiyasa
rights: Copyright (c) 2026 Zuhdi Fatkhurrahman https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 27
ending page: 40
doi: 10.36456/jhyde786

Design of an Internet of Things (IoT) based Main Reservoir Water Level Measuring Device at Siti Hajar Hospital Sidoarjo
type: item
description: The volume of water levels in hospital water reservoirs really requires full monitoring. Where water reservoirs often run out when the water is to be used. This is very fatal and hinders activities that must be carried out immediately. If this happens, it will result in the failure of ongoing activities at the hospital. This research aims to design a prototype that is capable of monitoring water levels in IoT-based hospital reservoirs. By designing a water level monitoring system in the reservoir using the HC-SR04 ultrasonic sensor as an input that measures water level and ESP32 as a microcontroller. The application produced from MIT App Inventor is a notification output and can display monitoring results. Based on the research results, it shows that the water level monitoring system in the reservoir can work well as expected, namely when the water is at the 25% limit, the application will send a notification to the smartphone in the form of sound so that users or technicians can find out and find the cause of the decreasing water level.
subject: Contents of the Journal
  topic: section
subject: MIT App Inventor
  topic: keywords
subject: IoT
  topic: keywords
subject: ESP32
  topic: keywords
subject: Sensor Ultrasonic
  topic: keywords
subject: Sistem Monitoring
  topic: keywords
creator: Adi Winarno
creator: Sagita Rochman
creator: Bagus Nanda
rights: Copyright (c) 2026 Adi Winarno, Sagita Rochman, Bagus Nanda https://creativecommons.org/licenses/by-sa/4.0
date: 2026-07-11
publication date: 2026-07-11
starting page: 55
ending page: 60
doi: 10.36456/zckxkc65

Integration of Concatenated Deep Learning Models with ResNet Backbone for Automated Corn Leaf Disease Identification
type: item
description: Corn is one of Indonesia's food commodities, which is an alternative food that supports food diversification in Indonesia. However, leaf infections in corn plants often cause significant yield losses and threaten food security. Early detection of this disease is very important, especially for small farmers, because conventional diagnostic methods that rely on agronomists are expensive and time-consuming. Recent advances in Agricultural Artificial Intelligence (AI) and image processing have facilitated automatic plant disease recognition through Convolutional Neural Networks (CNN), with ResNet as the main backbone combined through concatenation with MobileNetV3, DenseNet161, and GoogleNet. The dataset consists of 4,000 images divided into 2,560 training data, 640 validation data, and 800 test data, with image sizes adjusted to 224×224 pixels. The dataset consists of 4,000 images distributed across four categories: gray leaf spot, common rust, northern leaf blight, and healthy leaf. The testing was conducted using three different optimizers, namely Adam, RMSprop, and SGD, with a learning rate of 0.01. The experimental results showed that the SGD optimizer provided the best performance with a loss value of 0.2275, accuracy of 0.9513, precision of 0.9536, recall of 0.9513, and F1-score of 0.9512. These findings confirm that the combination of ResNet, MobileNetV3, DenseNet161, and GoogleNet architectures with the SGD optimizer can significantly improve the accuracy of corn leaf disease detection, making it a potential application for automatic detection systems in support of smart farming practices.
subject: Contents of the Journal
  topic: section
subject: Digital Image Processing
  topic: keywords
subject: Corn Leaf
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: CNN
  topic: keywords
creator: Achmad imam sudianto
creator: Sigit Susanto Putro
creator: Eka Mala Sari
creator: Ika Oktavia Suzanti
creator: Aeri Rachmad
creator: Wildan Surya Wijaya
rights: Copyright (c) 2025 Achmad imam sudianto, Sigit Susanto Putro, Eka Mala Sari , Ika Oktavia Suzanti , Aeri Rachmad , Wildan Surya Wijaya https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-07
publication date: 2025-10-07
starting page: 114
ending page: 119
doi: 10.36456/3kct9e57

Filling Machine Panel Retrofit into Arduino Nano-Based Digital System at CV Sarana Engineering
type: item
description: The control panel on the filling machine is an important component in the industrial automation system that functions to regulate the work sensors, actuators, and time-based control devices. This research begins with the emergence of ideas or needs to develop a system or solve a problem, which is then followed by problem identification and literature study to strengthen the theoretical basis. This study aims to redesign the filling machine control panel using a modular approach based on the Arduino Nano microcontroller. By replacing analog components with digital ones such as relay channels, LCDs, and modular PCBs, a cost efficiency analysis was carried out between the old and new systems. Testing was carried out by evaluating the response time, stability, and actuator coordination of the control panel, as well as conducting an economic analysis that included cost reduction and Return on Investment (ROI) calculations. These indicators were compared between the new and old panels to assess improvements in both technical performance and economic efficiency. The results showed that the new panel improved response speed, stability, and actuator coordination, while achieving cost savings of up to 80% compared to the conventional panel.The Return on Investment (ROI) analysis indicated an ROI of 405%, which demonstrates a significant economic advantage as the initial investment can be recovered multiple times over. This result highlights that the redesigned system is not only technically superior but also cost-effective and flexible, making it highly suitable for small to medium-scale industries. This system is also more modular, easy to program, and supports digital interface integration, making it a feasible and sustainable automation solution
subject: Contents of the Journal
  topic: section
subject: Machine Filling
  topic: keywords
subject: Automation
  topic: keywords
subject: Arduino Nano
  topic: keywords
subject: Return of Investment
  topic: keywords
creator: Wildan Surya Wijaya
creator: Aditya Ilham
creator: Muhamad Abdul Jumali
creator: Sagita Rochman
creator: Akhmad Solikin
creator: Nihayatun Nafisah
rights: Copyright (c) 2025 Wildan Surya Wijaya, Aditya Ilham, Muhamad Abdul Jumali, Sagita Rochman, Akhmad Solikin, Nihayatun Nafisah https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-12
publication date: 2025-09-12
starting page: 60
ending page: 65
doi: 10.36456/z17w7r20

Design and Development of a Geographic Information System for Historical Tourism Sites in Sumenep Regency Using the Location-Based Service Method
type: item
description: This study presents the development of a Web-based Geographic Information System (Web GIS) aimed at mapping historical tourism sites in Sumenep Regency. The system integrates Location-Based Services (LBS) to enhance the delivery of spatial information and support tourism promotion. A prototype-based methodology was used in designing and building the application, which includes planning, requirements analysis, system design, data collection, and testing. The system architecture was modeled using UML diagrams, including use case, activity, and entity-relationship diagrams to ensure functionality and data integrity. Spatial and attribute data were collected through literature reviews and transformed into an interactive web platform that allows users to search for and visualize historical tourism locations. The system supports administrative features for data input and updates, alongside public-facing features such as maps and visitor statistics. Testing was conducted using black-box methods to verify the system’s performance and reliability. The final output is a fully functional Web GIS platform that enhances public access to tourism information and assists local authorities in managing tourism data effectively. This research contributes to the advancement of digital tourism infrastructure and promotes cultural heritage visibility in the region.
subject: Contents of the Journal
  topic: section
subject: GIS
  topic: keywords
subject: Web-Based System
  topic: keywords
subject: Location-Based Services
  topic: keywords
creator: Achmad Zain Nur
creator: Puteri Nurul Ma'rifah
creator: Wildan Surya Wijaya
rights: Copyright (c) 2025 Achmad Zain Nur, Puteri Nurul Ma'rifah, Wildan Surya Wijaya https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-12
publication date: 2025-09-12
starting page: 55
ending page: 59
doi: 10.36456/v7n71q66

P2GS Web-Based E-CRM with WhatsApp API for MSME Customer Engagement
type: item
description: This study discusses the development, implementation, and user guide of the web-based Electronic Customer Relationship Management (E-CRM) P2GS system integrated with the WhatsApp API as an innovative solution for customer relationship management in Micro, Small, and Medium Enterprises (MSMEs). The system was developed using the System Development Life Cycle (SDLC) Waterfall model, comprising requirement analysis, design, implementation, testing, and evaluation stages. The trial was conducted on five MSMEs that are members of Perkumpulan Pengusaha Gading Sukowati (P2GS) in Sragen. Key features include a dashboard, sales management, purchase management, product master data, stock-taking, reporting, and store settings. The WhatsApp API integration enables automated messaging to customers, enhancing retention and engagement. Evaluation results indicate a 23% increase in customer retention, an 18% reduction in marketing costs, and a 12% increase in monthly revenue. The system’s usage is documented in the P2GS E-CRM Application User Guide to facilitate adoption and training. This study demonstrates that integrating popular technologies into E-CRM systems can significantly improve efficiency and performance in MSMEs
subject: Contents of the Journal
  topic: section
subject: E-CRM; WhatsApp API; MSME Empowerment
  topic: keywords
creator: Khabib Alia Akhmad
creator: Nurohman
rights: Copyright (c) 2025 Khabib Alia Akhmad, Nurohman https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-07
publication date: 2025-10-07
starting page: 101
ending page: 104
doi: 10.36456/jjxnrx20

Short Circuit Current Analysis and Recloser Coordination in 20 kV Distribution Network Using Manual Calculation and ETAP Software Simulation
type: item
description: This study aims to analyze the performance of reclosers in improving the reliability of the 20 kilovolt distribution network at PT PLN (Persero) UP3 Lhokseumawe. The research focuses on optimizing the placement and delay time settings of reclosers based on fault current and network impedance. A comparative method was used involving manual calculations and simulation using ETAP 16.0.0 software. The object of study is the CD 12 feeder. The simulation evaluates fault currents and the corresponding recloser delay times at several bus locations. Results show that the closer the fault location to the power source, the higher the short-circuit current, which leads to shorter recloser operating time. Conversely, longer distances result in lower fault currents and longer delay settings. The analysis confirms that proper coordination and parameter settings significantly improve system protection and recovery. Moreover, differences between manual and simulation results emphasize the importance of digital tools in distribution network analysis. The study concludes that recloser configuration based on accurate load profiles and fault data enhances overall system performance and operational efficiency.
subject: Contents of the Journal
  topic: section
subject: Recloser configuration, fault current analysis, ETAP simulation.
  topic: keywords
creator: Riswanda
creator: Raihan Putri
creator: Muchlis Abdul Muthalib
rights: Copyright (c) 2025 Riswanda, Raihan Putri, Muchlis Abdul Muthalib https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-07
publication date: 2025-10-07
starting page: 94
ending page: 100
doi: 10.36456/nw6kbg33

Design of Omniwheel Kinematics Learning Platform using ESP32 and Microsoft Visual Studio
type: item
description: Wheeled robots have evolved significantly, starting from simple designs that utilized a single wheel for maneuvering to the present day, where there are numerous types capable of moving in all directions. The increasing complexity of wheeled robots today has created a learning gap for students who are just entering the world of robotics and the advanced robots that currently exist. Based on this problem, a mobile robot learning platform is needed to bridge their knowledge. The design of this platform is expected to help guide students’ learning of omniwheel robot kinematics in terms of robot model preparation, robot firmware design, communication design between the PC and the robot, and the implementation of kinematic formulas as robot commands. This platform is also designed to be universal, so it can be implemented for ready-made robots or robots built with any type of microcontroller. Comprehensive testing was performed for both movement modes in the application: forward kinematics and inverse kinematics. The forward kinematics test was carried out by assigning speed values to each motor individually. The inverse kinematics test was cariied out by assigning target position in cartesian plane. This platform is expected to serve as a valuable tool in the study of omniwheel robot kinematics.
subject: Contents of the Journal
  topic: section
subject: Omniwheel
  topic: keywords
subject: Robots
  topic: keywords
subject: Kinematics
  topic: keywords
subject: PID
  topic: keywords
subject: GUI
  topic: keywords
creator: Sayyidul Aulia Alamsyah
creator: Parama Diptya Widayaka
creator: Pradini Puspitaningayu
creator: Taj Hakam Ikhsan
creator: Rifando Arya Pradana
creator: Ryan Rizky Herdiansyah Palma
creator: Ibrohim Zuhayr Achmad
rights: Copyright (c) 2025 Sayyidul Aulia Alamsyah https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-07
publication date: 2025-10-07
starting page: 105
ending page: 113
doi: 10.36456/fn9f2t21

Application of Knowledge Based Method in Mobile Application-Based Cat Feed Recommendation System
type: item
description: Choosing the right cat food is often an obstacle for Giant Pet shop customers due to the many product variations and monotonous recommendations from sellers. This study designs a mobile application-based cat food recommendation system by implementing a knowledge-based method and a constraint-based approach. The system allows users to receive product suggestions based on brand attributes, taste, cat age, weight, price, and type of food. Data collection was carried out through literature studies and direct observations at Giant Pet shop, with system development following the waterfall model including needs analysis, UML design, and implementation. The results of the system test showed very good performance with a precision of 88.90% which proves the accuracy of recommendations according to user criteria, and a recall of 100% which shows completeness in displaying all relevant products. These results confirm that the system can help and make it easier for users to find products that suit their needs.
subject: Contents of the Journal
  topic: section
subject: Recommendation System
  topic: keywords
subject: Knowledge Based
  topic: keywords
subject: Constraint Based
  topic: keywords
subject: Cat Food
  topic: keywords
subject: Mobile Application
  topic: keywords
creator: Farrel Putra Ediansyah
creator: Pramono
creator: Dwi Hartanti
rights: Copyright (c) 2025 Farrel Putra Ediansyah, Pramono, Dwi Hartanti https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-06
publication date: 2025-10-06
starting page: 88
ending page: 93
doi: 10.36456/m2w0fk03

Design and Construction of Pharmacy Sales Information System
type: item
description: Hero Farma Pharmacy in Boyolali serves more than 40 daily transactions but still uses a manual Excel recording system that is prone to human error , data duplication, and slow in reporting. This study aims to create a web-based sales information system to improve the efficiency and accuracy of pharmacy operations. The research method uses a waterfall which includes the stages of needs analysis through interviews and observations, system design with UML, implementation using Laravel 10 and React.js integrated with Inertia.js, and blackbox testing. The implementation results show that the system has been successfully built with a structured database. Blackbox testing on 8 main functions. This web-based information system has succeeded in replacing the manual Excel process , minimizing recording errors, increasing operational efficiency, and supporting better managerial decisions to support pharmacy performance.
subject: Contents of the Journal
  topic: section
subject: information systems
  topic: keywords
subject: pharmacy
  topic: keywords
subject: sales
  topic: keywords
subject: Laravel
  topic: keywords
subject: React.js
  topic: keywords
creator: Sanggita Erinne
creator: agustina srirahayu
creator: Nibras Faiq Muhammad
rights: Copyright (c) 2025 Sanggita Erinne, agustina srirahayu, Nibras Faiq Muhammad https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-06
publication date: 2025-10-06
starting page: 80
ending page: 87
doi: 10.36456/gb8xvd83

Design and Development of a Web-Based Employee Attendance and Payroll Information System at CV Expressa
type: item
description: This study aims to design and build a web-based employee attendance and payroll information system at CV Expressa to overcome problems arising from manual processes, such as late salaries, data recapitulation errors, and lack of transparency. The method used is the System Development Life Cycle (SDLC) waterfall model approach, which includes needs analysis, system design, implementation using the Laravel framework and MySQL database, testing with the blackbox method, and maintenance. The results of the study show that the system built is able to automate GPS-based attendance recording and salary calculations, accelerate data recapitulation, and provide independent payslip access for employees. This system also succeeded in increasing operational efficiency and data accuracy, as well as reducing administrative workload. However, this study has limitations in the scope of implementation which is still limited to one company and does not include advanced security features such as biometric authentication and mobile applications. Further development is recommended to improve the scalability and flexibility of the system.
subject: Contents of the Journal
  topic: section
subject: attendance
  topic: keywords
subject: payroll
  topic: keywords
subject: information systems
  topic: keywords
subject: web
  topic: keywords
subject: SDLC
  topic: keywords
creator: Wanda Fadillah
creator: Hanifah Permatasari
creator: Moh. Muhtarom
rights: Copyright (c) 2025 Wanda Fadillah, Hanifah Permatasari, Moh. Muhtarom https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-06
publication date: 2025-10-06
starting page: 73
ending page: 79
doi: 10.36456/agn6m149

Design and Construction of Web-Based Budgeting Submission Information System at CV Expressa
type: item
description: CV Expressa faces problems in budget management due to a slow manual process, less transparent, and vulnerable to errors. This study aims to design a web -based budgeting information system to improve efficiency and accuracy. System development uses the SDLC Waterfall method (Analysis of Needs, Design, Implementation, Testing, Maintenance) with Laravel Technology (PHP) and PostgreSQL Database. Features include budget submission, tiered approval, reporting, and audit trail. Blackbox testing test results show all functions run optimally, supported by automatic notifications and printed reports. This system is proven to speed up the process, reduce errors, and increase budget transparency at CV Expressa
subject: Contents of the Journal
  topic: section
subject: Information Systems
  topic: keywords
subject: Budget Submission
  topic: keywords
subject: SDLC Waterfall
  topic: keywords
subject: Laravel
  topic: keywords
subject: Efficiency
  topic: keywords
creator: Muhammad Hashfi Rafid Muttaqin
creator: Hanifah Permatasari
creator: Dwi Hartanti
rights: Copyright (c) 2025 Muhammad Hashfi Rafid Muttaqin, Hanifah Permatasari, Dwi Hartanti https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-06
publication date: 2025-10-06
starting page: 66
ending page: 72
doi: 10.36456/rw747x67

Development of A Machine Learning Based Chess Game in Python
type: item
description: This paper presents the design and implementation of a Machine Learning (ML)-based chess game developed in Python. Unlike traditional chess game that rely primarily on alpha-beta pruning and handcrafted evaluation functions, this approach employs supervised learning techniques to create a neural network model capable of evaluating chess positions and making move decisions. The system leverages the python-chess library for game representation and the scikit-learn framework for implementing the machine learning components. We demonstrate that even with relatively simple feature engineering and a modest neural network architecture, the system can learn effective chess strategies. The implementation is designed to run in a Jupyter Notebook environment, providing an interactive interface for human players to compete against the ML agent while facilitating educational insights into both chess strategy and machine learning principles.
subject: Contents of the Journal
  topic: section
subject: Machine Learning
  topic: keywords
subject: Chess Game
  topic: keywords
subject: Neural Networks
  topic: keywords
subject: Supervised Learning
  topic: keywords
subject: Phyton
  topic: keywords
creator: Dwi Hastuti
creator: WILDAN surya Wijaya
rights: Copyright (c) 2025 Dwi Hastuti, Wildan Surya Wijaya https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 21
ending page: 28
doi: 10.36456/best.vol7.no1.10343

Handling Imbalanced Fraudulent Transaction Data Using SMOTE-Tomek and Random Forest: A Classification Approach
type: item
description: This research aims to address the class imbalance problem in fraud detection using hybrid resampling techniques, specifically SMOTE-Tomek, combined with Random Forest classifiers. Imbalanced data in fraud detection tasks can severely hinder model performance, resulting in poor detection of minority (fraud) cases. By employing SMOTE to oversample minority class instances and Tomek links to clean the borderline majority class samples, this study evaluates the effectiveness of this hybrid method in improving classification metrics. Using a benchmark credit card fraud dataset, we compare the performance of Random Forest models with and without the hybrid sampling approach. The experimental results show that SMOTE-Tomek significantly enhances recall and F1-score without sacrificing accuracy. This finding underscores the importance of using appropriate resampling strategies for improving model robustness in fraud detection.
subject: Contents of the Journal
  topic: section
subject: Fraud Detection
  topic: keywords
subject: Imbalanced Data
  topic: keywords
subject: SMOTE-Tomek
  topic: keywords
subject: Random Forest
  topic: keywords
subject: Clasisification
  topic: keywords
creator: Mohamad Ilham
creator: Adi Winarno
creator: Moch Lutfi
creator: Artanti Indrasetianingsih
rights: Copyright (c) 2025 Mohamad Ilham, Adi Winarno, Moch Lutfi, Artanti Indrasetianingsih https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 35
ending page: 38
doi: 10.36456/best.vol7.no1.10335

Implementation of Decision Tree and Item Response Theory (IRT) in SIMPATIF (Sistem Penilaian Adaptif)
type: item
description: This study discusses how to accurately determine the level of ability of students using Computer Adaptive Testing (CAT). In the implementation of CAT, test participants are given question items according to their abilities. This shows the difference from existing testing systems such as Computer Based Testing (CBT). ADAPTIVE in this system is an automated exam system that is carried out adaptively, adjusting the difficulty level of the questions to the ability of each examinee. The questions given depend on the answer to the previous question: true or false. If the answer is correct, then the next question item has a higher level of difficulty, while if it is wrong, the difficulty level of the next question decreases. CAT in this study is also called the term SIMPATIF (Adaptive Assessment System). The difference between CAT and SIMPATIF is from the selection of question items, in the test using the SIMPATIF application, the selection of question items using the C4.5 algorithm and IRT 3 Parameter Logistics Model (3PL). The 3 parameters are the difficulty level of the question, differentiation, and deceit. In the development of this SIMPATIF. The input attributes from the decision tree have 4 attributes, namely difficulty level, differentiation, deceiver and IRT, while the target attributes are 2, namely YES and NO. The questions used are productive subjects majoring in Multimedia at SMK PGRI 2 Sidoarjo. The study was conducted with 10 students, SIMPATIF only succeeded in 67,901% for the adaptive status of the questions. Meanwhile, if correlated with CBT 76.58%.
subject: Contents of the Journal
  topic: section
subject: Item Response Theory
  topic: keywords
subject: Computer Adaptive Testing
  topic: keywords
subject: Computer Based Testing
  topic: keywords
subject: Paper And Pencil Test
  topic: keywords
creator: Norma Devi Kurniasari
creator: Anis Shobikhah
creator: Trian Basofi Rohman
creator: Muchamad Kurniawan
rights: Copyright (c) 2025 Norma Devi Kurniasari https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 17
ending page: 20
doi: 10.36456/best.vol7.no1.10317

TensorFlow Based AI Training for Translating Indonesian Sign Language (BISINDO)
type: item
description: Communication is an important aspect of social life, including for deaf people who rely on sign language as their primary means of interaction. However, the limited understanding of sign language in society, especially BISINDO (Bahasa Isyarat Indonesia), is often a barrier to effective communication. This study aims to develop a simple sign language translator system using TensorFlow and Keras-based machine learning technology, as well as image processing support from OpenCV. The system is trained to recognize six basic signs in BISINDO, namely “Halo”, “Nama”, “Saya, “A”, “D”, and “I”, using hand images as training data. Each word is represented by 20 images with variations in horizontal position. The test results show that the system is able to recognize signs with fairly good accuracy under certain conditions, but still has difficulty when faced with variations in hand positions that are different from the training data. This study shows the potential of sign language recognition technology in supporting inclusive communication, as well as the importance of data enrichment and variation in viewpoints in the model training process so that the system can function more optimally in various real conditions.
subject: Contents of the Journal
  topic: section
subject: BISINDO
  topic: keywords
subject: Sign Language
  topic: keywords
subject: TensorFlow
  topic: keywords
subject: AI
  topic: keywords
subject: Translating
  topic: keywords
creator: Akbar Sujiwa
creator: Nailul Hasan
creator: Nenni Mona Aruan
rights: Copyright (c) 2025 Akbar Sujiwa, Nailul Hasan, Nenni Mona Aruan https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 29
ending page: 34
doi: 10.36456/best.vol7.no1.10312

Design and Simulation Sag Tension of a 20kV Power System with 150kV Tower Infrastructure in Marabahan City with Monte Carlo method
type: item
description: Rumpiang Bridge is a vital object and requires special handling for voltage installation; therefore, a construction that is capable of spanning a wide area is needed, where the construction obtained is the 150 kV HV construction, and for the cable span, it is simulated using the Monte Carlo method for the analysis of cable crossing deflection in Barito Kuala, with three types of cables, namely ACSR, AAAC, and AAACS. The simulation was carried out 1000 times by considering random variations of ±10% in cable weight and tensile force and ±5% in the crossing length. The results show that ACSR and AAAC cables have low average deflections, 3.24 meters and 3.26 meters, respectively, with standard deviations of 0.33 meters and 0.32 meters, indicating stable and consistent mechanical performance. While the AAACS cable shows a higher average deflection of 4.72 meters and a standard deviation of 0.48 meters, indicating a greater variation in deflection due to its physical characteristics. All three cables meet the technical requirement of maximum deflection <30 meters, but ACSR cable is recommended as the primary choice due to its combination of low deflection and high stability, which provides a greater safety margin in extreme crossing environmental conditions.
subject: Contents of the Journal
  topic: section
subject: MV 20 KV
  topic: keywords
subject: MonteCarlo
  topic: keywords
subject: HV 150 kV
  topic: keywords
subject: Sag Cable
  topic: keywords
creator: Muhammad Alviando Wisang
creator: Mohamad Noor Hidayat
creator: Cahya Rahmad
creator: Wldan surya Wijaya
rights: Copyright (c) 2025 Mohamad Noor Hidayat, Muhammad Alviando Wisang , Cahya Rahmad , Wildan surya Wijaya https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 45
ending page: 50
doi: 10.36456/best.vol7.no1.10234

Artificial Intelligence System for Face Detection to Identify Passenger Identity at the Airport
type: item
description: Facial biometric technology is widely used in various fields such as bank security, border crossings, airport check-in, home surveillance, remote meetings in offices, prisons, and factories. This makes facial recognition an important field to study and develop. In countries like the United States and Germany, trials have begun for the implementation of Face Recognition technology in airport areas. This technology is used for airport check-in systems to address the issue of long queues, especially during holiday seasons, which is a common occurrence in airports worldwide. Although online check-in methods already exist, they still do not resolve this issue. Unfortunately, this technology has not yet been implemented or discussed for application in Indonesian airports. Therefore, the researchers intend to conduct a study on this technology to ensure that Indonesia does not fall behind other countries in facial detection technology. Based on the test results of the developed system, it can be concluded that the facial detection system is quite effective in identifying faces, but there are some limitations, such as lighting and facial accessories. The system works optimally at light intensities ranging from 806 lumens to 161 lumens, and if the person to be detected is wearing a mask or sunglasses, the system will not be able to recognize the face.
subject: Contents of the Journal
  topic: section
subject: detector
  topic: keywords
subject: face
  topic: keywords
subject: check in
  topic: keywords
subject: air port
  topic: keywords
subject: Artifical Intelligence
  topic: keywords
creator: Akhmad Solikin
creator: Sagita Rochman
creator: budi Widiarto
rights: Copyright (c) 2025 Akhmad Solikin, Sagita Rochman, Budi Widiarto https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 11
ending page: 16
doi: 10.36456/best.vol7.no1.10310

Design, Build, and Implement Monitoring Applications Student Grades and Violations
type: item
description: Information and communication technology development has entered the era of Industry 4.0, requiring the educational sector to adapt more rapidly and efficiently. Thus, information technology has been integrated into various learning activities. However, the monitoring of information on students' learning progress is mostly carried out by the schools, while parents typically receive report cards at the end of the term. This does not provide effectiveness, as it limits parental involvement in early supervision. This research is designed to help both teachers and parents in supervising students more directly. This research utilizes NFC (Near Field Communication) technology for recording student attendance at school. Based on the results of application testing, users gave high ratings to the system in terms of interface design, NFC card reading accuracy, ease of managing student permissions, recording student behavior and academic grades, as well as the tool’s completeness and functionality. The average success rate of horizontal NFC card reading reached 100%, while vertical reading achieved 90%. The maximum reading distance was 4 cm for Samsung A50s (version 10.0) and Samsung A30s (version 10.0), and 3 cm for the Redmi Note 8 Pro (version 9.0).
subject: Contents of the Journal
  topic: section
subject: Student behavior
  topic: keywords
subject: student achievement
  topic: keywords
subject: teacher-parent communication
  topic: keywords
subject: NFC
  topic: keywords
subject: Firebase
  topic: keywords
creator: Puteri Nurul Ma'rifah
creator: Achmad Zain Nur
creator: Luthfi Awwalia
creator: Wildan Surya Wijaya
creator: Puteri Nurul Magfirah
rights: Copyright (c) 2025 Puteri Nurul Ma'rifah, S.Tr.T., M.Tr.T., Achmad Zain Nur, S.Kom., M.T., Luthfi Awwalia, S.Pd., M.Pd., Wildan Surya Wijaya, S.Tr.T., M.Tr.T, Puteri Nurul Magfirah, S.Tr.T., S.T. https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 39
ending page: 44
doi: 10.36456/best.vol7.no1.10198

Implementation of Charity Box Security System based on Internet of Things (IoT) using Sensor and Notifications
type: item
description: Mosques are places of worship for Muslims. With a large number of mosques, the problems that arise are also diverse, for example the AL Akbar Surabaya mosque has 2 thefts per year. The form of breaking into the charity box was in the form of the destruction of the padlock hinge made of iron plates in the outer courtyard of the mosque. This is a problem for mosque managers. The purpose of this research is to create a security system for the charity box of the Al Akbar National Mosque that can be controlled remotely using the Internet of Things (IoT). This system will ensure the safety of the charity box and prevent the possibility of theft or manipulation of the money contained in it. This security system uses motion sensors as an indicator of suspicious activity around the charity box. When the vibration sensor detects vibration, the system will activate the Buzzer and the ESP32 CAM camera takes pictures to be further processed using a face detection algorithm and the results are sent in the form of a notification to the mosque manager who is connected to the internet network, so that it can take photos that can be accessed in real-time by security control. To control this security system, a mobile application will be built that can be accessed by mosque administrators. Overall, this design will provide a higher level of security for the Al Akbar National Mosque charity box. With a security system that can be accessed and controlled remotely through IoT. The mosque management can quickly respond and take action in unsafe situations.
subject: Contents of the Journal
  topic: section
subject: charity box
  topic: keywords
subject: ESP32
  topic: keywords
subject: IoT
  topic: keywords
subject: vibration sensor
  topic: keywords
subject: buzzer
  topic: keywords
subject: camera
  topic: keywords
creator: Atmiasri
creator: Akhmad Solikin
creator: Anggarjuna Puncak Pujiputra
rights: Copyright (c) 2025 Atmiasri Atmiasri, Akhmad Solikin, Anggarjuna Puncak Pujiputra https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 7
ending page: 10
doi: 10.36456/best.vol7.no1.10159

Smart Backpack Solution for Child Safety Monitoring using GPS Tracker and Internet of Things (IoT)
type: item
description: Abstract- Supervision of children is an important thing to do for the development of behaviour and child safety. The existence of cases around such as after school not going straight home, skipping school to play online games, even in the mass media there are cases of elementary school children who do not go home immediately. in the mass media there are cases of elementary school children who died from drowning while playing. This can cause parents to worry about their children. On the other hand, the space for parents to supervise children directly is limited due to their activities such as taking care of the house or working, so there is an alternative to make a tracking device or GPS Tracker with the concept of the Internet of Things (IoT) that can solve the problem. The manufacturing method includes three stages, namely the design stage, the testing stage, and data analysis stage in order to produce the expected tool. The results of this research are first, GPS Tracker is built by three main components (Ardunino Nano, Ublox NEO-6M, and SIM800L). Second, the tool functions optimally when outside the room with percentage of error 0% and less than maximum when indoors with an error of 40%. room with 40% error. Third, the device is able to track position at various distances. Fourth, the tool has an average working endurance of 4 hours 26 minutes with a power source of 3.7 VDC 3500mAH battery.
subject: Contents of the Journal
  topic: section
subject: Surveillance
  topic: keywords
subject: GPS
  topic: keywords
subject: Internet of Things
  topic: keywords
subject: Website
  topic: keywords
creator: Anggarjuna Puncak Pujiputra
creator: Thomas Brian
creator: Putri Nur Rahayu
creator: Atmiasri
rights: Copyright (c) 2025 Anggarjuna Puncak Pujiputra, Thomas Brian, Putri Nur Rahayu, Atmiasri Atmiasri, https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-18
publication date: 2025-03-18
starting page: 1
ending page: 6
doi: 10.36456/best.vol7.no1.10158

Implementation of Face Detection Login System using Python
type: item
description: Traditional authentication methods, primarily relying on passwords, face several critical challenges. Users often choose weak passwords, reuse them across multiple platforms, or struggle to remember complex combinations, leading to potential security vulnerabilities. As cybersecurity threats continue to evolve, traditional password-based authentication mechanisms have proven increasingly vulnerable to various attacks. Face detection-based login systems have emerged as a promising alternative, offering a balance between security and user convenience. This paper provides a detailed examination of implementing face detection-based login systems, focusing on using Python programming language. The research highlights both the advantages and potential vulnerabilities of such systems while proposing mitigation strategies for enhanced security.
subject: Contents of the Journal
  topic: section
subject: cybersecurity
  topic: keywords
subject: login system
  topic: keywords
subject: face detection
  topic: keywords
subject: python programming language
  topic: keywords
creator: Dwi Hastuti
creator: Rasyida Shabihah Zukro Aini
creator: Afif Nuril Musthofa
rights: Copyright (c) 2024 Dwi Hastuti, Rasyida Shabihah Zukro Aini, Afif Nuril Musthofa https://creativecommons.org/licenses/by-sa/4.0
date: 2024-09-16
publication date: 2024-09-16
starting page: 79
ending page: 83
doi: 10.36456/best.vol6.no2.9880

Soil Moisture and PH Control Device in Sprout Cultivation
type: item
description: Sprout cultivation is one of the practical and economical methods to obtain a type of food rich in nutrients. However, the success of sprout cultivation requires proper control of soil moisture and water pH in the cultivation environment. Watering begins when the moisture of the mung bean plant reaches the specified parameters with a soil moisture of 67 and a pH value of + 9. This tool aims to make manual work easier to automate, a benefit in watering sprout plants. This tool uses a water ph sensor and a soil moisture sensor or soil moisture sensor that functions as a soil moisture detector that will send commands to the Arduino uno to turn on the relay so that the water pump can automatically water according to the needs of the soil. The creation of this final project is carried out by designing, making and implementing system components which include Arduino uno as a controller, relay to turn on the water pump and turn off the water pump, LCD (linquit Crystal Display) to display the soil moisture value and water ph value. The results of the research value prove that the tools to be made can function properly and can be developed as expected.
subject: Contents of the Journal
  topic: section
subject: Arduino
  topic: keywords
subject: PH Sensor
  topic: keywords
creator: Adi Winarno
creator: akhmad solikin
creator: Muhammad Risyaf
rights: Copyright (c) 2024 Adi Winarno, akhmad solikin, Muhammad Risyaf https://creativecommons.org/licenses/by-sa/4.0
date: 2024-09-16
publication date: 2024-09-16
starting page: 75
ending page: 78
doi: 10.36456/best.vol6.no2.9535

Design and Construction of Power Monitoring and Circuit Breaker Devices for PLN Customers based on IoT
type: item
description: Along with the modern Indonesian society's need for electricity consumption, the level of electricity consumption continues to increase. Electricity consumption among postpaid PLN customers with single-phase connections is often poorly regulated due to inadequate monitoring of power usage and frequent payment delays between the 1st and 20th of each month. This study involved the development of a monitoring device designed to track power usage for single-phase PLN customers. Additionally, an electricity circuit breaker was created that can be controlled remotely via the officer's smartphone. This monitoring system uses PZEM-0004T as the sensor. The voltage, current, power and energy data will be read by the sensor and then sent by the ESP8266 to the Internet of Things (IoT) based Blynk Website. This breaker tool uses a relay as an electrical circuit breaker on the customer side. With this tool, it is possible to reduce illegal use of PLN electricity and reduce the number of arrears in customer electricity bill payments to PLN.
subject: Contents of the Journal
  topic: section
subject: electrical power monitoring
  topic: keywords
subject: PZEM-004T
  topic: keywords
subject: Internet of Things (IoT)
  topic: keywords
subject: Breaking Device
  topic: keywords
creator: Sagita Rochman
creator: Afif Nuril Musthofa
creator: Muchammad Rizky Firmansyah
rights: Copyright (c) 2024 Sagita Rochman, Afif Nuril Musthofa, Muchammad Rizky Firmansyah https://creativecommons.org/licenses/by-sa/4.0
date: 2024-09-16
publication date: 2024-09-16
starting page: 69
ending page: 74
doi: 10.36456/best.vol6.no2.9442