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All Journal Buletin Statistika dan Aplikasi Terkini Journal of Research Applications in Community Services
Solikhah, Arifatus
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ANALISIS FAKTOR-FAKTOR PENENTU KEMISKINAN DI KALIMANTAN TIMUR: Perbandingan Model Weighted Logistic Regression, Naive Bayes, dan Regresi Binomial Solikhah, Arifatus
BESTARI BPS Kalimantan Timur Vol. 3 No. 02 (2023): Bestari Edisi 6
Publisher : BPS Kalimantan Timur

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Abstract

This study aims to analyze the factors influencing household poverty status in East Kalimantan by comparing three models: Weighted Logistic Regression (WLR), Naive Bayes, and Binomial Regression with a generalized logit link function (glogit). The data used were obtained from the National Socioeconomic Survey (SUSENAS) conducted in March 2023. Parameter estimation was performed using a Bayesian approach with the Hamiltonian Monte Carlo (HMC) algorithm through the RStan program. The analysis results indicate that the number of household members, place of residence, education level of household head, employment status of household head, age of household head, and dependency ratio are significant variables affecting household poverty status in East Kalimantan. The comparison of the three models' performance shows that the WLR and Naive Bayes models are better at detecting poor households compared to the Binomial Regression with a generalized logit link function model, despite the Binomial Regression model showing higher overall accuracy. These findings provide important insights into the determinants of poverty and the effectiveness of various models in handling unbalanced binary data.
ANALISIS ELASTISITAS PDRB KALIMANTAN TIMUR PERIODE 2011-2023: PENDEKATAN BAYESIAN PRINCIPAL COMPONENTS LOG-LINEAR REGRESSION Solikhah, Arifatus
BESTARI BPS Kalimantan Timur Vol. 4 No. 02 (2024): Bestari Edisi 8
Publisher : BPS Kalimantan Timur

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This study investigates the elasticity of East Kalimantan's Gross Regional Domestic Product (GRDP) at constant prices 2010 to five economic indicators using a Bayesian Principal Components Log-linear Regression (PCLR) model for the 2011-2023 period. The indicators used include the import volume of non-crude oil fuel, employed population, median value of the Composite Stock Price Index (CSPI), electricity consumption, and China's energy consumption. Principal component analysis yields the Economic Fundamental Indicator explaining 76.1436% and the Fuel Import Indicator explaining 20.6950% of the total data variability of 96.8386%. Estimation results show that a one-unit increase in the Economic Fundamental Indicator and Fuel Import Indicator will increase the GRDP at constant prices by 7.17% and 2.01% respectively. The model satisfies the residual normality assumption based on the Shapiro-Wilk test with a p-value of 0.9871 and shows no significant autocorrelation with a Durbin-Watson statistic of 1.4486. These findings imply the importance of strengthening regional economic fundamentals through labor market optimization, energy infrastructure development, increased integration with the national capital market, and economic diversification to reduce vulnerability to external shocks. Keywords: GRDP at constant prices elasticity, Principal Components Log-linear Regression, East Kalimantan, Bayesian method
Pelatihan Penggunaan Software Q-GIS Pemetaan Spasial dan Pengenalan Program Regresi Nonparametrik di BPS Provinsi Kalimantan Timur Sifriyani, Sifriyani; Fauziyah, Meirinda; Dani, Andrea Tri Rian; Wahyuningsih, Sri; Prangga, Surya; Istiqomah, Nurul; Solikhah, Arifatus
Journal of Research Applications in Community Service Vol. 2 No. 4 (2023): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v2i4.2326

Abstract

Perkembangan teknologi saat ini harus didukung dengan kemahiran seorang ahli untuk adaptasi melalui visualisasi data dan penyajian hasil analisis kesimpulan yang tepat. Untuk mendukung kemahiran tersebut dilaksanakan sharing knowledge antar stakeholder dengan akademisi guna mendukung pembuatan kebijakan. Hal ini menjadi salah satu alasan pelaksanaan kegiatan pengabdian masyarakat. Beberapa software open sourceyang dapat digunakan untuk visualisasi data pemetaan yaitu Q-GIS dan analisisnya menggunakan I-Regs. Tujuan pelaksanaan kegiatan adalah memberikan kesempatan untuk sharing knowledge penggunaan Q-GIS dan I-Regs yang dapat digunakan untuk proses pengolahan data dan visualisasi bagi instansi terkait, memberikan pengenalan penggunaan software I-Regs, dan meningkatkan pengetahuan isu terkini bagi kedua belah pihak. Subjek (mitra) dari kegiatan ini 100 peserta yang terdiri dari staff BPS, mahasiswa dan dosen Jurusan Matematika FMIPA UNMUL. Berdasarkan hasil analisis diperoleh kesimpulan bahwa terdapat perbedaan rata-rata nilai ujian sebelum dan sesudah mengikuti pelatihan artinya kegiatan pelatihan memiliki pengaruh yang signifikan dalam meningkatkan kinerja para staff.
Co-Authors Dani, Andrea Tri Rian Fauziyah, Meirinda Nurul Istiqomah Sifriyani, Sifriyani Sukamto, Ika Sumiyarsi Surya Prangga