J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika <p>Jurnal Ilmiah Teori dan Aplikasi Statistika</p> en-US jstat@unipasby.ac.id (Muhammad Athoillah) statistika@unipasby.ac.id (Sari Cahyaningtias) Sun, 31 Dec 2023 23:40:33 +0700 OJS 3.3.0.10 http://blogs.law.harvard.edu/tech/rss 60 Penerapan Model Arfima-Garch Menggunakan Variasi Estimasi Parameter Pembeda D Pada Data Long Memory https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8041 <p>Emas menjadi salah satu aset keuangan bagi negara dan menjadi komponen cadangan moneter global untuk perdagangan dan perlindungan ketika menghadapi krisis keuangan secara tiba-tiba. Beberapa data ekonomi sering mengalami ketergantungan atau dependensi jangka panjang (long memory). Salah satu model yang mampu mengatasi masalah tersebut adalah model <em>Autotegressive Fractionally</em> <em>Integrated Moving Average</em> (ARFIMA). Ada beberapa metode yang digunakan untuk menentukan estimasi parameter pembeda d yaitu metode <em>Geweke and Porter</em> <em>Hudak</em> dan metode <em>Rescaled Range Statistics</em> (R/S). Pada beberapa tipe data runtun waktu terkadang mengalami pengelompokan volatilitas (residual tidak konstan). Metode yang dapat digunakan untuk mengatasi masalah tersebut adalah metode <em>Generalized Autoregressive Conditional Heteroskedasticity</em> (GARCH). Tujuan dari penelitian ini adalah untuk memodelkan harga emas antam produksi PT. Aneka Tambang menggunakan metode ARFIMA-GARCH serta membandingkan metode estimasi parameter pembeda d terbaik dari model tersebut. Hasil penelitian ini menunjukan model terbaik dilihat dari nilai AIC untuk dgph = 0, 105 adalah ARFIMA(1,d,1)-GARCH(1,1) dan model terbaik untuk dR/S = 0, 288 adalah ARFIMA(1,d,1)-GARCH(1,1). Tingkat akurasi peramalan didasarkan pada nilai MAPE. Nilai error validasi model ARFIMA-GARCH dengan dgph = 0, 105 adalah MAPE=3,474%, sedangkan model ARFIMA-GARCH dengan dR/S = 0, 288 adalah MAPE=3,444%.</p> Isran K Hasan, Muhammad Janur; Nurwan Nurwan Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8041 Sun, 31 Dec 2023 00:00:00 +0700 Pemodelan Regresi Data Panel Harga Beras di Wilayah Indonesia Bagian Barat https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8061 <p>Beras merupakan kebutuhan pokok atau utama bagi masyarakat di Indonesia. Kenaikan harga beras berpengaruh sangat signifikan dalam berbagai aspek yang dapat mempengaruhi kebijakan ekonomi pemerintah. Sentra beras nasional didominasi oleh wilayah Indonesia bagian barat. Pemenuhan jumlah beras di setiap wilayah dilakukan oleh sentra beras melalui pendistribusian ke wilayah-wilayah lain. Harga pada wilayah yang merupakan sentra beras mempengaruhi harga beras di setiap wilayah-wilayah sekitarnya. Oleh karena itu, peramalan harga beras dibutuhkan. Penelitian ini bertujuan untuk melakukan pemodelan harga beras dengan metode Regresi Data Panel di Wilayah Indonesia Bagian Barat. Model Regresi Data Panel adalah hasil dari penggabungan data cross section dan time series. Dalam penelitian ini, pemodelan dibangun dengan menggunakan data dari semua provinsi di Indonesia bagian barat (cross sectional) pada beberapa tahun sebelumnya dengan tingkat bulanan (time series), sehingga pemilihan metode yang sesuai adalah menggunakan regresi data panel. Model Regresi Data Panel yang terpilih adalah REM (Random Effect Model) dengan rata-rata MAPE sebesar 3.28%. Pemodelan harga beras yang terbentuk dapat digunakan sebagai acuan dalam peramalan harga beras kedepannya, sehingga penentuan kebijakan ekonomi dapat dilakukan secara tepat.</p> Yogi Adam Firdaus , Ngatini Ngatini, Sekarsari Utami Wijaya Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8061 Sun, 31 Dec 2023 00:00:00 +0700 Hubungan Faktor Demografis dengan Kejadian Malaria di Kecamatan Wewewa Timur: Pendekatan Analisis Chi-Square https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/7907 <p>Pendekatan chi-square dalam analisis faktor risiko kesehatan telah menjadi topik yang menarik dan relevan dalam penelitian terkini. Malaria, sebagai penyakit infeksi menular yang ditularkan melalui gigitan nyamuk Anopheles betina, masih menjadi ancaman bagi masyarakat di beberapa daerah di Indonesia, termasuk Kecamatan Wewewa Timur. Meskipun kasus malaria di kecamatan ini mengalami penurunan dari tahun 2018 hingga 2021, namun pada tahun 2022, kasusnya kembali mengalami peningkatan. Dalam upaya untuk memahami lebih lanjut tentang faktor-faktor yang mempengaruhi kejadian malaria di Kecamatan Wewewa Timur, penelitian ini menggunakan pendekatan chi-square(χ²) yang termasuk dalam uji non-parametrik digunakan untuk menentukan apakah terdapat perbedaan yang signifikan antara distribusi frekuensi yang diamati (observed frequencies) dengan distribusi frekuensi yang diharapkan (expected frequencies) dalam satu atau lebih kategori melibatkan 400 data primer yang diambil di wilayah tersebut. Hasil penelitian menunjukkan bahwa terdapat lima faktor yang secara signifikan berhubungan dengan kejadian malaria di Kecamatan Wewewa Timur, yaitu jenis kelamin, usia, pekerjaan, penggunaan kelambu, dan tingkat pendidikan. Temuan ini memberikan wawasan yang berharga dalam perumusan kebijakan dan strategi penanggulangan malaria yang lebih efektif dan tepat sasaranTop of Form</p> Maria Agustina Kleden, Junaldo Umbu Moto , Robertus Dole Guntur Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/7907 Sun, 31 Dec 2023 00:00:00 +0700 Comparison of K-Means and K-Medoids Clustering for Grouping The Sub-Districts In Bojonegoro Regency Based On Educational Supporting Factors https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8079 <p>Education in Bojonegoro is currently still uneven. This is because efforts to equalize education that have been carried out have many obstacles. The obstacle that often occurs is that people who are in remote areas and far from urban areas have difficulty accessing education services. Therefore, regional grouping needs to be done so that the Bojonegoro district government can pay attention to regional clusters that need education improvement. This study used the K-Means and K-Medoids methods to group sub-districts in Bojonegoro district based on educational supporting factors. K-Means is one of the unsupervised learning methods used to analyze data by grouping. Meanwhile, K-Medoids is a partition grouping method that groups a set of n objects into a number of k clusters. The data used in this study is secondary data obtained from the Bojonegoro district Education Office in the form of data on education supporting factors which include the number of schools, the number of educators, and the number of learning groups (ROMBEL) in 2022 in each sub-district in Bojonegoro district. From the research results, it was found that the K-Means method was better than the K-Medoids method. The results of grouping using K-Means obtained as many as 5 clusters, cluster 1 consists of 1 sub-district, cluster 2 consists of 7 sub-districts, cluster 3 consists of 1 sub-district, cluster 4 consists of 12 sub-districts and cluster 5 consists of 7 sub-districts. Based on the characteristics of each cluster obtained, it is expected to be used as input for the Education office for equal distribution of education in Bojonegoro district.</p> Alif Yuanita Kartini Kartini, Syarif Husen Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8079 Sun, 31 Dec 2023 00:00:00 +0700 Fuzzy C-Means for Regional Clustering in East Java Province Based on Human Development Index Indicators https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8240 <p>The Human Development Index (HDI) is the UN's key metric for gauging human advancement within a country, blending vital elements like per capita income, life expectancy, and education. In Indonesia, the HDI assesses societal well-being, with East Java's HDI lagging behind national and governmental targets despite mitigation efforts. To address this, the study utilizes Fuzzy C-Means clustering to classify East Java's regions based on HDI indicators, revealing five optimal groups via pseudo-F-statistic analysis. One-way MANOVA confirms variations among these groups, while One-Way ANOVA validates the significance of the four HDI indicators in categorization. The HDI-based categorization denotes Group 3 as high-status, Group 1 as low-status, Group 2 as moderately high-status, Group 4 as moderate, and Group 5 as moderately low-status. Consequently, it's advised that the government concentrates on improving low-HDI groups to uplift East Java's populace. This research can serve as a cornerstone for policymakers and stakeholders in their efforts to enhance the HDI in this region.</p> Marita Qori'atunnadyah Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8240 Sun, 31 Dec 2023 00:00:00 +0700 Investigating the Impact of Mobile Legends Gameplay on Students' Academic Performance with Ordinal Logistic Regression https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/7567 <p>The development of information technology and online games, such as Mobile Legends Bang Bang, has spread to various segments of society in Indonesia, including children, students, and university students. Although the government has supported the e-sports industry, research on the influence of interest in playing Mobile Legends on students' academic performance is still limited. Therefore, this research aims to identify the impact of interest in playing Mobile Legends and the significant factors affecting students' academic performance. We used the ordinal logistic regression method in our analysis, a statistical technique to measure the relationship between independent variables and ordinal dependent variables, such as academic performance levels categorized as low, moderate, or high GPA. Our analysis results in two models: low Cumulative Grade Point Average (GPA) and moderate GPA. The significant factors are the level of interest, including the 'very interested' and 'interested' categories, and Gender with the category 'male.' Our analysis also indicates that the obtained model provides good results and is acceptable since all the explanatory variables are statistically significant. </p> Irawan Irawan, Nurul Fitriyani, I Gede Adhitya Wisnu Wardhana, Irwansyah Irwansyah, Zulhan Widya Baskara Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/7567 Sun, 31 Dec 2023 00:00:00 +0700 Clustering Villages in the Mountain Areas in West Java Based on Tourism Potential Using K-Prototype Algorithm https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8167 <p>Cluster analysis is a multivariate analysis method used to group objects based on their similar characteristics. In general, in the clustering process only use numerical or categorical data. But, sometimes we also encounter cases that use both numerical and categorical data. Therefore, the algorithm that can be used is K-Prototype. K-Prototype is a development of K-Means that can be used on large data with numerical and categorical types. The basis of K-Prototype development is to measure the distance between the object and its centroid prototype. The number of prototypes depends on the number of clusters formed. In this study, researchers use this algorithm to group mountainous villages in West Java based on their tourism potential, in order to find out the potential that needs to be developed based on five components, namely Attractions, Access, Accommodation, Amenities and Awareness. Based on the Silhouette and McClain Index, the optimal number of clusters is two. Cluster 1 consists of 103 villages and cluster 2 consists of 703 villages. Cluster 1 are villages that are generally better in the Access, Awareness and Amenities, but are still lacking in the Attraction and Accommodation components compared to villages in cluster 2.</p> Ainun Salsabila Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8167 Sun, 31 Dec 2023 00:00:00 +0700 Kernel Nonparametric Regression Modeling with the Nadaraya-Watson Estimator (Case Study: Fertility in the Southern Sumatra Region) https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8248 <p>Fertility is a live birth, namely the release of a baby from a woman's womb with signs of life such as screaming, breathing, a throbbing heart, and so on. The source of this research data comes from the publication of the official website of the Central Statistics Agency (BPS). This study aims to model and predict fertility data in 2020 with kernel nonparametric regression using the Nadaraya-Watson estimator. The nonparametric kernel model shows the relationship between fertility (Y) and the percentage of underage women at first marriage , the percentage of women 15-49 years who do not use traditional KB or conventional methods , the number of active family planning participants , the number of couples of childbearing age , the percentage of the average length of schooling , and the total expenditure per capita based on Gaussian kernel function and bandwidth values. Based on the results of the analysis, the independent variables that have a significant effect are , , , on the dependent variable with the optimum bandwidth value of 0.490 and the value of R<sup>2</sup> of 99.6%, and the MSE value of 0.332. Modeling fertility is important as it helps understand and predict population trends. It provides insights into the potential number of births in a population in the future. This information can be used for policy planning, including health, educations, and social policies.</p> Muhammad Arib Alwansyah Arib Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8248 Sun, 31 Dec 2023 00:00:00 +0700 Model Persamaan Struktural Faktor – Faktor Yang Mempengaruhi Kepuasan Masyarakat Dalam Pemeriksaan Kesehatan di UPTD Puskesmas Pasir Putih Sawangan Depok https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8042 <p>Salah satu faktor penting kepuasan masyarakat pada layanan kesehatan adalah mutu layanan. Mutu pelayanan yang berhubungan dengan medis, mewakili tingkat kesempurnaan pelayanan medis melalui terciptanya rasa kepuasan pada setiap masyarakat. Pada penelitian ini kepuasan masyarakat diukur dengan adanya mutu pelayanan yang mempunyai kaitan dengan kualitas pelayanan dan kompetensi pegawai di Puskesmas Pasir Putih kota Depok. Penelitian ini bertujuan untuk mengetahui pengaruh langsung kualitas pelayanan terhadap kepuasaan masyarakat, untuk mengetahui pengaruh langsung kompetensi pegawai terhadap kepuasan masyarakat, untuk mengetahui pengaruh tidak langsung antara kualitas pelayanan terhadap kepuasan masyarakat melalui kompetensi pegawai, dan pengaruh total antara kualitas pelayanan, kompetensi pegawai terhadap kepuasan masyarakat. Jumlah sampel pada penelitian ini adalah 379 responden yang ditentukan dengan menggunakan teknik <em>accidental sampling</em><em>, </em>dimana responden yang dipilih <em> </em>adalah masyarakat yang mendapatkan pelayanan kesehatan di UPTD Puskesmas Pasir Putih. Teknik analisis yang digunakan adalah <em>Structural Equation Modelling (SEM). </em>Berdasarkan hasil analisis diperoleh bahwa terdapat pengaruh langsung kualitas pelayanan terhadap kepuasan masyarakat, terdapat pengaruh langsung kompetensi pegawai terhadap kepuasan masyarakat, terdapat pengaruh tidak langsung antara kualitas pelayanan masyarakat melalui kompetensi pegawai, dan terdapat pengaruh total antara kualitas pelayanan dan kompetensi pegawai terhadap masyarakat di UPTD Puskesmas Pasir Putih.</p> Nisa Utari , Besse Arnawisuda Ningsi, Irvana Arofah Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8042 Sun, 31 Dec 2023 00:00:00 +0700 Analysis of the Timeliness of Graduation of FMIPA College KIP Students at Bengkulu University Using Binary Logistic Regression https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8233 <p>Previous studies that discuss the timeliness of graduating students are generally more focused on the student population as a whole, without considering the influence of specific scholarship programs such as KIP Kuliah. This study aims to obtain a model of the timeliness of student graduation and obtain factors that affect the timeliness of graduating KIP Kuliah students of FMIPA Bengkulu University using the Binary Logistic Regression method. The results of this study are expected to provide valuable information for KIP Kuliah managers of Bengkulu University in improving the effectiveness of the KIP Kuliah scholarship program and helping KIP Kuliah students of FMIPA Bengkulu University to graduate on time. In this study, Binary Logistic Regression method is used because the response variable has a nominal binary scale. Based on the results of the discussion of the research conducted, a Binary Logistic Regression model of the timeliness of graduating KIP Kuliah students of FMIPA Bengkulu University is obtained with factors that have a significant influence on the timeliness of graduating KIP Kuliah students of FMIPA Bengkulu University is the origin of the S1-Physics, S1-Biology and S1-Statistics study programs and GPA. Then the classification results using Binary Logistic Regression have a classification accuracy rate of 77.97%. So it can be concluded that the classification of the timeliness of graduating students of FMIPA Bengkulu University in the Binary Logistic Regression model is good enough.</p> Riki Crisdianto Riki Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8233 Sun, 31 Dec 2023 00:00:00 +0700 Diversification of Jakarta Islamic Index (JII) Stock Optimal Portfolio for the Period 2018-2023 https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8339 <p>Investment is placing funds into an asset to gain profits in the future through changes in asset prices or capital gains. In Indonesia, stock investment, primarily through the Indonesia Stock Exchange (BEI), is popular among the public. BEI offers various indices, including the Jakarta Islamic Index (JII), which has garnered significant attention. JII comprises stocks of companies that adhere to Sharia principles. In investment, careful analysis is crucial to avoid errors in stock selection. Diversification is a strategy that involves spreading investments across several stocks, aiming to maximize profits while minimizing risks. While the easiest way for investors to enter the stock market is by purchasing the best-performing single stock, relying solely on one stock can be risky if its price drops. This research compares investment outcomes between single-stock and diversified portfolios of two or three stocks, selected based on the Sharpe, Treynor, and Jensen indices. The research analyzes the closing stock prices within the JII index from March 2018 to February 2023. The study results show that diversifying investments across multiple stocks can reduce investment risks, even though it may reduce profit potential.</p> Khairul Alim, Bayun Matsaany, Anisa Rahmawati Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8339 Sun, 31 Dec 2023 00:00:00 +0700 Forecasting PT Triputra Agro Persada Tbk (TAPG) Share Prices Using Multivariate Time Series Analysis https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8344 <p>An increase in the price of crude palm oil (CPO) positively affects the share prices of companies engaged in the palm oil industry. PT Triputra Agro Persada Tbk (TAPG) 2021 was recorded as one of the companies with the CPO business that received the most significant capital gain. Prediction or forecasting of stock prices in the future is crucial for investors as a consideration before deciding to invest. Many kinds of research on stock price prediction have been carried out previously using univariate methods. Univariate modeling cannot represent the influence of other variables on stock prices. Forecasting with the influence of other variables can be done with multivariate time series analysis. This study aims to analyze the multivariate time series of TAPG stock prices and the factors that influence them. Based on the research results, data on TAPG stock prices and CPO prices are cointegrated, so the multivariate time series model used is the vector error correction model (VECM). In the VECM model, the optimum lag used is lag 11. In the long run, CPO prices significantly affect TAPG stock prices.</p> Dwi Sulistiowati, Maya Sai Syahrul, Maya Sai Syahrul, Iswan Rina Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8344 Sun, 31 Dec 2023 00:00:00 +0700 Identifying Factors that Influence Life Expectancy in Central Java Using Spatial Regression Models https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8375 <p>Life Expectancy is an average calculated over several years, assuming that mortality remains constant as age increases. It serves as a metric to gauge the success of population health development at the urban level and overall well-being, particularly in terms of health. Various indicators, including socioeconomic conditions, environmental factors, and health indicators, influence the highs and lows of life expectancy. This study in Central Java Province's 35 districts and cities aims to identify crucial components impacting life expectancy through a process-oriented spatial regression analysis. Additionally, the research endeavors to determine the optimal spatial regression equation for modeling life expectancy in the province. Spatial regression, a linear regression development method falling under the point element model, is employed. Utilizing two independent variables selected from seven, the study explores spatial regression equations using SAR, SEM, and SARMA area approaches. Data sourced from BPS in 2020 reveals that the SAR model, with a p-value of 0.02183, is apt for identifying spatial effects on Central Java's life expectancy. The Open Unemployment Rate (X<sub>4</sub>) and the Percentage of Poor Population (X<sub>6</sub>) emerge as significant spatial factors influencing life expectancy in Central Java.</p> prizka rismawati arum Copyright (c) 2023 J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika https://jurnal.unipasby.ac.id/index.php/jstatistika/article/view/8375 Sun, 31 Dec 2023 00:00:00 +0700