https://jurnal.unipasby.ac.id/index.php/jstatistika/issue/feedJ Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika2024-12-31T00:00:00+07:00Muhammad Athoillah[email protected]Open Journal Systems<p>Jurnal Ilmiah Teori dan Aplikasi Statistika</p>https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/9837Optimization of Raw Material Supply Scheduling to Maximize Storage Utilization at Company X2024-12-21T16:04:58+07:00Karina Rahmawati[email protected]Hery Murnawan[email protected]<p><em>This study focuses on optimizing the raw material supply scheduling at Company X, a business in the food and beverage industry, to maximize storage utilization. Company X faces challenges in balancing raw material demand with limited storage capacity, leading to issues such as stock shortages or overstocking. The current inventory management practices have proven ineffective in meeting consumer demand efficiently. This research utilizes a quantitative methodology, focusing on numerical data analysis to address the research objectives. Through this approach, measurable data are collected and examined to provide clear insights into patterns, relationships, and trends. The quantitative method ensures objectivity and precision, making it ideal for evaluating factors such as raw material supply schedules, storage capacity, and demand fluctuations, thereby supporting data driven decision-makingThrough the analysis of sales data and raw material requirements, this research aims to develop a more effective scheduling strategy that aligns supply with demand while optimizing storage space. The findings of this study offer potential solutions for improving operational efficiency, reducing waste, and enhancing the overall supply chain performance. By implementing optimized supply scheduling, Company X can ensure smoother operations and better meet consumer needs, thus maximizing value across the entire supply chain.</em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/9836Optimization of Spare Part Inventory for Mask Production Machines at PT. XYZ to Enhance Productivity2024-12-19T14:32:44+07:00Dony Mahardhika[email protected]Hery Murnawan[email protected]<p><em>This study focuses on the optimization of spare part inventory for mask production machines at PT. XYZ with the aim of enhancing productivity and reducing operational costs. The research identifies key failure points in the mask machines, including issues with the conveyor system, pulley pulls, and ultrasonic sealers, which were the main contributors to production downtime. This study adopts a quantitative research approach, focusing on the systematic collection and analysis of numerical data to draw conclusions and provide objective insights into the issues being studied</em><em>. </em><em>By applying inventory management concepts such as safety stock, service levels, and periodic reviews, the study determines the optimal spare part inventory levels required to ensure component availability and minimize the risk of stockouts. The implementation of the PDCA (Plan-Do-Check-Act) method further improves machine maintenance processes, leading to an increase in machine effectiveness levels. Additionally, effective inventory management reduces waste due to over-purchasing and mismanagement of spare parts. The findings highlight that by optimizing spare part inventory and improving machine maintenance, PT. XYZ was able to reduce downtime, minimize operational costs, and enhance overall productivity, contributing to greater efficiency and profitability.</em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/9722Potential Productivity of Quail Farming in Ngaliyan, Pulutan, Wonosari, Gunungkidul2024-11-14T12:14:26+07:00Annida Purnamawati[email protected]Wawan Nugroho [email protected]Raffi Fa`Iq Firjatullah [email protected]Mochamad Akbar Garudea Syahroni [email protected]<p><em>Quails are a type of poultry with significant productivity potential that can be developed and improved through enhanced care to achieve optimal production. This study aims to analyze the factors influencing the production of laying quail farms in Ngaliyan, Pulutan, Wonosari, Gunungkidul. If low egg production becomes an obstacle for farmers, it can hinder efforts to increase productivity and meet consumer demand. The purpose of this research is to identify the various factors influencing quail egg production. The study employs a mixed-method approach, combining qualitative and quantitative techniques, with multiple linear regression analysis. The results indicate that income from quail egg production is IDR 193.011.950 per business period (15 months). Multiple linear regression analysis shows that both independent variables, feed cost (X₁) and labor cost (X₂), have a significant effect on quail egg production (Y), with a significance level of <0.001. The feed cost variable (X₁) has a dominant positive influence, while labor cost (X₂) has a negative influence. The relationship between the two independent variables and egg production is 88.1%, with 11.9% influenced by other factors outside of the study. The regression model used is strong and valid, demonstrating the significant impact of both independent variables on the dependent variable.</em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8562Analysis of Public Perception of Dynastic Politics in the 2024 Presidential and Vice Presidential Elections in Indonesia with a Chi-Square Approach2024-06-07T16:16:50+07:00Firda Aulia Pratiwi[email protected]Nur Chamidah[email protected]Naura Qathrunnada Bi Arafah[email protected]Bintang Alyaa Sabila[email protected]Sheila Sevira Asteriska Naura[email protected]<p><em>The phenomenon of dynastic politics in the 2024 Presidential and Vice Presidential Elections has become a hot issue in Indonesia. Dynastic politics is the inheritance of power in the family to maintain political influence, which has the potential to threaten democracy and state development. This study aims to identify the relationship between public perceptions of dynastic politics based on the characteristics of respondents, in line with SDGs point 16, namely, peace, justice and resilient institutions, if dynastic politics is not transparent it can hinder good governance. Data was obtained through questionnaires distributed to 210 respondents, then analyzed using the Chi-Square test to measure the relationship between public perceptions of dynastic politics and the characteristics of gender, profession, and region of residence. The results of the analysis show that public perception does not have a significant relationship with gender, but is significantly related to profession and region of residence on one of the statements, namely agreeing that the existence of political dynasties has a negative impact on Indonesian democracy.</em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/9591Three–Phase Traffic Light Petri Net Model Using The Modified Norwegian System 2024-11-14T12:11:24+07:00Tomi Tristono [email protected]Setiyo Daru Cahyono[email protected]Pradityo Utomo[email protected]Mochamad Sidqon[email protected]Sudarno[email protected]Daniel Wahyu Suprayoga Prabowo[email protected]Hendro Susilo[email protected]<p><em>Petri nets can be used to model the behavior of traffic light signals. The Petri net model also makes it possible to provide synchronization of several traffic light phases. The Petri net model can represent the modified Norwegian system signal, which lights up in the sequence green, yellow, red, yellow, and then goes back to green again. The yellow signal flashes twice in each traffic light cycle modified Norwegian system. This study aims to examine the Petri net model of traffic lights with three phases using the modified Norwegian system. Methods for validating and verifying the correctness of the Petri net model us</em><em>ed several Place-Invariants, boundedness properties on the Petri net, conservation, coverability trees for various signal conditions, and simulation. Based on the study results, the Place-Invariant and the Petri net properties can represent that the model is correct and feasible. The simulation also presents the correct sequence of modified Norwegian system signals.</em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/9416Weibull Regression Survival Analysis on the Rate of Recovery of Thyphoid Fever Patients: Case Study of RSUD Haji Makassar2024-07-31T23:39:55+07:00Nurul Maghfira[email protected]Bobby Poerwanto[email protected]Hardianti Hafid[email protected]<p><em>Survival analysis is a statistical method used in studying survival related to time, from the beginning of the study to the end of the study. The purpose of survival analysis is to determine the relationship between survival time and independent variables in research that are thought to affect survival time. This study uses weibull regression survival analysis to see the factors that significantly affect the recovery rate of patients with typhoid fever at the Makassar Hajj Hospital in 2022. The results of the analysis of factors that have a significant effect on the rate of recovery of patients with typhoid fever are heartburn. Patients with a history of having heartburn have a hazard ratio value of 1.779, which means that patients with typhoid fever who experience heartburn have a faster recovery rate of 1.779 times compared to patients who do not experience heartburn. </em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8737Analysis of Environmental and Productivity Factors with the Number of Dengue Hemorrhagic Fever and Obesity Cases in Indonesia2024-11-14T12:04:56+07:00Abu Hanifah Al Faruqy[email protected]A'yunin Sofro[email protected]<p><em>Dengue Hemorrhagic Fever (DHF) is a frequently occurring disease in tropical regions. This is due to the disease vector being the Aedes aegypti mosquito, whose habitat is in tropical environments. Obesity has become a global issue worldwide. Patients with obesity have a stronger immune response due to increased inflammation in circulation. As a result, blood vessels may become wider than usual. This triggers plasma leakage and exacerbates DHF, potentially leading to Severe Dengue Syndrome (SDS). Both of these diseases have various triggering factors such as environmental and productivity-related aspects. In this study, multivariate linear regression analysis will be employed to identify which factors are significant for both diseases. The linear regression analysis will use simultaneous and partial Wilks' Lambda tests. Based on the research findings, it is stated that there are four predictor variables significant for the levels of DHF and obesity, namely, Air Quality Index (</em><em>), productivity (</em><em>), poverty rate (</em><em> ), and the number of health centers (</em><em>).</em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistikahttps://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/9318Generalized Poisson Regression Modeling on the Number of Infant Deaths in East Nusa Tenggara Province in 20222024-11-14T12:16:49+07:00Robertus Guntur[email protected]Maria Ririanti da Rato[email protected]<p><em>The number of infant deaths in East Nusa Tenggara (NTT) Province is still above the national average. This research was conducted to investigate the Generalized Poisson Regression (GPR) model for addressing the overdispersion in the Poisson regression model of the number of cases of infant deaths and to explore the potential factors influencing the number of infant deaths in the province. </em><em>The variable used is the number infant mortality as a response variable, and the number of predictor variables that are thought to influence the response variable. The data used is secondary data obtained from the publication by the Central Statistics Agency of ENT Province from each of the 22 cities/regencies. The study shows data on the number of cases of infant mortality experienced overdispersion with a ratio between deviance and degrees of freedom of 3.578. Modeling with GPR shows that the model with 5 independent variables produces an optimal model with an AIC value of 184.145. Those variables are the percentage of households with access to adequate sanitation, the percentage of births assisted by parties other than medical personnel, the number of teenagers who received reproductive health counseling, the percentage of the population aged 0-59 months who received incomplete immunization, and the number of health facilities. </em></p>2024-12-31T00:00:00+07:00Copyright (c) 2024 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika