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Jurnal Statistika dan Aplikasinya
Published by Universitas Negeri Jakarta
ISSN : -     EISSN : 26208369     DOI : https://doi.org/10.21009/JSA.041
Core Subject : Economy, Science, Education, Agriculture, Social,
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Social Sciences Other
Jurnal Statistika dan Aplikasinya JSA is dedicated to all statisticians who wants to publishing their articles about statistics and its application. The coverage of JSA includes every subject that using or related to statistics.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 23 Documents
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Search results for , issue "Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya" : 23 Documents clear
Klasifikasi Pemilih dalam Pemilu 2019 di Indonesia Menggunakan Regresi Logistik Multinomial dan Chi-Square Automatic Decision Tree (CHAID) Yekti Widyaningsih; Curie Nabilah Nasution
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06201

Abstract

General Elections (Elections) in Indonesia are conducted once in every 5 years. This paper focused on the election of the president and his representatives. Voters in elections are regulated by law. There are many aspects of voter’s background that influence voters in making decisions during elections. In this paper, the focus is on voter background factors in geographical, demographic, and socio-economic aspects. The geographical aspect is the region where voters live; demographic aspects are gender, age, recent education, marital status, and religion; socioeconomic aspects are the household expenses, household income, personal expenses, type of work, type of residence, and status of residence. There are 3 categories of voter decisions in the election, namely candidate pair A, candidate pair B, and refuse to vote. The objectives of this paper are to find out what variables significantly influence voters in making decisions during elections, and to classify voters based on the significance of variables in geographical, demographic, and socio-economic aspects related to voter choice in elections. Multinomial logistic regression analysis is used to answer the first objective, while the CHAID (Chi-Square Automatic Decision Tree) decision tree is used to answer the second objective. Through multinomial logistic regression analysis, it can be seen that the variable type of region, age, recent education, religion, household expenditure, household income, house type and home status influence voter decisions in elections. Through the CHAID decision tree, the results obtained are 5 types of voters based on a decision tree of several independent variables that are significant to the dependent variable.
Pemodelan Regresi Logistik Berbasis Backward Elimination Untuk Mengetahui Faktor yang Mempengaruhi Tingkat Kemiskinan di Indonesia Tahun 2021 Alfi Indah Nurrizqi; Erfiani; Indahwati; Anwar Fitrianto; Reni Amelia
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06202

Abstract

Kemiskinan seringkali berhubungan dengan masalah kesejahteraan dan menjadi salah satu masalah utama di Indonesia. Kondisi ekonomi akibat Covid-19 berdampak pada tingkat kemiskinan di masyarakat. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang memengaruhi tingkat kemiskinan di Indonesia tahun 2021 menggunakan regresi logistik biner. Regresi logistik biner digunakan untuk memodelkan hubungan antara variabel respon yang terdiri dari dua kategori dengan satu atau lebih variabel prediktor. Hasil penelitian ini menunjukkan proporsi tingkat kemiskinan rendah lebih tinggi dibandingkan tingkat kemiskinan tinggi. Terdapat 18 provinsi dengan tingkat kemiskinan rendah serta 16 provinsi dengan tingkat kemiskinan tinggi. Faktor-faktor yang berpengaruh terhadap kategori pada tingkat kemiskinan yaitu Indeks Pembangunan Manusia (X1) dan Gini Ratio (X2). Ketepatan klasifikasi dari model sebesar 83.33%, yang artinya model baik digunakan.
Statistical Downscaling Menggunakan Pengelompokan Expectation-Maximization pada Data CFSRv2 Rizka Pitri; Ayu Sofia; Siswanto
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06203

Abstract

General Circulation Model (GCM) is a numerical model that produce a number of data from various climate parameters that are used to estimate climate, one of which is precipitation. GCM is a global scale data and has high resolution. So, the GCM cannot consider the local-scale areas with a higher resolution than the GCM. Therefore, to be able to use the GCM for estimating the local rainfall, namely Statistical Downscaling (SD). SD is a technique used to get the relationship between global-scale (GCM) and local-scale data. SD use the GCM which consist of dependent variables that have multicollinearity. So in this research, the principal component regression (PCR) and partial least square regression (PLSR) will be used to reduce the multicollinearity. In addition, to reduce the RMSEP and increase the correlation value, a clustering technique will be applied before modeling, namely Expectation-Maximization (EM) clustering. This research use CFSRv2 data as GCM and local rainfall data at four rainfall stations in West Java (January 2011 to December 2017). Based on this research, PCR is a good modeling than PLSR and EM clustering get the lower RMSEP and higher correlation value than without clustering before modeling. The conclusion is PCR with EM clustering is a good method for estimating local rainfall using the SD technique especially rainfall in West Java and CFSRv2 data.
Pemodelan Geographically Weighted Regression pada Kasus Stunting di Provinsi Nusa Tenggara Timur Tahun 2020 Marcella Gloria Leto Bele; Elvira Mustikawati Putri Hermanto; Fenny Fitriani
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06204

Abstract

Stunting or short toddlers is one of the problems that Indonesia is currently facing. Based on data from the Indonesia Health Profile in 2020, the highest prevalence of stunting in Indonesia in 2020 was in the East Nusa Tenggara Province. The occurrence of stunting in each district/city has the possibility of having different characteristics from one region or another which is referred to as regional heterogeneity or spatial heterogeneity. This research was conducted to determine the factors that influence stunting cases in each district/city of East Nusa Tenggara Province. This research uses the Geographically Weighted Regression (GWR) method to model stunting cases in each district/city of East Nusa Tenggara Province. The factors that significantly affect stunting in districts/cities in East Nusa Tenggara Province spatially with α =10% percentage of infants receiving complete immunization, the percentage of poor people, the percentage of infants receiving exclusive breastfeeding, the percentage of women who have graduated from senior high school, and the percentage of women who have ever married underage. The modeling of stunting cases in East Nusa Tenggara Province using the GWR method obtained R2 of 99,25% larger than the OLS model of 52,1%, and the AIC of the GWR model of 59,8105 smaller than OLS model.
Identifikasi Karakteristik Perokok Aktif di Provinsi Sumatera Barat Tahun 2020 dengan Model Logistik Biner Fizza Anindhita; Muhammad Hasbi
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06205

Abstract

Cigarettes are one of the most popular products in society. Based on BPS data, the percentage of the population aged over 15 years who smoked in 2020 was 28,69 percent. Expenditure per capita to determine the order of the second largest after food and beverages, and greater than grains. This makes cigarettes one of the primary needs for most people. West Sumatra Province is one of the areas that promote smoking bans with various regional regulations related to smoking bans. However, this is not very fruitful, the number of smokers in West Sumatra is still higher than the national average of 30,08 percent in 2020. The dominant result obtained is that the majority of smokers in West Sumatra are male. Men are 11,5 times more likely to be active smokers than women. Smokers in West Sumatra are also dominated by residents with primary education status and below, which is 47 percent of the total smokers and has the greatest opportunity to be active compared to other educational statuses, which is 6,9 times. These results are expected to be determined to determine policies so that cigarette consumption in West Sumatra Province can be reduced.
Analisis Kepemilikan Jaminan Kesehatan Penduduk Usia Produktif di Provinsi Kalimantan Tengah 2021 Menggunakan Regresi Logistik Biner Hazanul Zikra
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06206

Abstract

Pemerintah Provinsi Kalimantan Tengah terus mendorong untuk mencapai Universal Health Coverage (UHC) melalui kepemilikan jaminan kesehatan, terutama bagi penduduk usia produktif (15-64 tahun). Survei Sosial Ekonomi Nasional (Susenas) 2021 menunjukkan, persentase penduduk Kalimantan Tengah yang memiliki fasilitas jaminan kesehatan sebesar 65,50 persen. Capaian ini masih belum sesuai dengan target pemerintah untuk mewujudkan kepemilikan jaminan kesehatan bagi minimal 95 persen dari penduduk. Penelitian ini bertujuan untuk menganalisis sejumlah faktor yang diduga memengaruhi kepemilikan jaminan kesehatan bagi penduduk Kalimantan Tengah tahun 2021 menggunakan metode regresi logistik biner. Data yang digunakan bersumber dari Susenas Maret 2021. Hasil analisis menunjukkan klasifikasi tempat tinggal (perkotaan atau perdesaan), status bekerja, status perkawinan, jenis kelamin, umur, dan kepemilikan rekening tabungan berpengaruh signifikan terhadap kepemilikan jaminan kesehatan bagi penduduk usia produktif di Kalimantan Tengah tahun 2021.
IMPLEMENTASI IMRPOVED CHI-SQUARE AUTOMATIC INTERACTION DETECTION PADA KLASIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI LITERASI INFORMASI GENERASI MUDA Zian Bula; Resmawan Resmawan; La Ode Nashar; Salmun K. Nasib
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06207

Abstract

Information Literacy skills are needed to find quality sources and manage and sort information so that it can be used to improve the quality of life and community empowerment. The number of factors that affect information literacy causes the need for classification. The method used is Improved Chi-Square Automatic Interaction Detection (Improved CHAID), which aims to classify influencing factors with Information Literacy abilities. This study uses primary data, namely 237 Mananggu Young Generation (15-24 years), with Information Literacy as the dependent variable. The independent variables consist of reading interest, reading habits, gender, digital literacy, information needs, critical thinking, and information-seeking behavior. Based on the Improved CHAID analysis, the factors that significantly affect information literacy are Reading Habits (83%), Information Needs (89%), and Critical Thinking (94%). The classification performance of Testing Data is 40%, with a classification accuracy of 77% or from 95 samples, there are 73 samples that are properly classified. The sensitivity of 78% shows that the classification results are able to predict samples that have information literacy, 74% specificity indicates that the classification results are able to predict samples that do not have information literacy, and Press's Q 27.38 indicates a stable classification or statistically significant.
Pemodelan Produk Domestik Regional Bruto di Indonesia dengan Regresi Nonparametrik Menggunakan Estimator Spline Luh Putu Safitri Pratiwi; I Made Pasek Pradnyana Wijaya
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06208

Abstract

The implementation of PPKM results in a decrease in community activities, hampers mobility and ultimately disrupts overall economic activity. So it is necessary to have a study that can explain the extent of economic development in Indonesia due to COVID-19 with a model. The modeling used in this research is nonparametric regression modeling with spline estimator. The purpose of this study is to determine the descriptive statistics of GRDP data in all provinces in Indonesia as an indicator of the rate of economic growth in Indonesia and to model the GRDP in Indonesia using nonparametric regression estimator spline. The results obtained in this study are the best nonparametric spline regression model with three knot points with a GCV value of 5199284230 and an R2 of 98.61 percent.
Implementasi Regresi Robust untuk Mengetahui Faktor-Faktor yang Mempengaruhi Produksi Padi di Indonesia M. Paris Ramdoni Rasantaka; Mochamad Fahmi Ashshidiqi; Riska Yulianti; Zahrah Zeinawaqi; Edy Widodo
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06209

Abstract

Seiring dengan pertambahan jumlah penduduk tentu akan membutuhkan ketersediaan bahan pangan pokok masyarakat yang semakin meningkat pula. Padi sebagai salah satu komoditas utama bahan pangan pokok masyarakat Indonesia tentu menjadi perhatian penting bagi pemerintah Indonesia. Menurut penilaian dari The Global Food Safety Initiative (GFSI) terjadi penurunan nilai indek ketahanan pangan di Indonesia sebesar 2.2% di tahun 2021. Hal ini diikuti dengan banyak dilakukannya eksploitasi terhadap lahan pertanian seperti di Jawa Tengah yang menjadi salah satu lumbung padi di Indonesia. Ketergantungan masyarakat Indonesia terhadap nasi sebagai makanan pokok membawa tantangan yang besar dalam mengelola ketahanan atau ketersediaan padi di Indonesia. Untuk itu dalam penelitian ini akan digunakan analisis regeresi robust dalam melakuakn analisis untuk mengetahui faktor-faktor yang mempengaruhi produksi padi di Indonesia berdasarkan literatur terdahulu yang menjadi landasan seperti luas panen, realisasi pupuk, rata-rata curah hujan, produksi benih padi, dan jumlah tenaga kerja sektor pertanian. Dari hasil analisis yang didapatkan diketahui bahwa yang berpengaruh signifikan terhadap produksi padi dari faktor yang ada yaitu luas panen dan produksi benih padi.
Penerapan Analisis Regresi Logistik Ordinal pada Asuransi Kredit Perdagangan Domestik Kelvin Gunawan; Ruhiyat; I Gusti Putu Purnaba
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06220

Abstract

One of the main activities that support the national economy is domestic trade. However, domestic trade is faced with various risks. One risk is that the buyer fails to fulfil his obligation to pay. The seller can overcome this risk by purchasing a domestic trade credit insurance product from an insurance company. The premium rate must be calculated correctly so that the insurance company does not suffer losses. Premium rates can be grouped based on several factors. Ordinal logistic regression analysis can be used to group premium rates and identify factors that affect premium rate groups. The maximum likelihood method can be used to estimate the parameters of the ordinal logistic regression model. In this study, two logit models were produced, and the premium rate group was significantly affected by the payment tenor, central credit limit, and the type of commodity. Overall, the classification accuracy value generated from the ordinal logistic regression model that has been built is 57.45%.

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