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All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI The Journal of Experimental Life Sciences (JELS) CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Statistik Jurnal EECCIS Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Natural B Plantropica: Journal of Agricultural Science Jurnal Ekonomi & Studi Pembangunan Ikonomika : Jurnal Ekonomi dan Bisnis Islam Science and Technology Indonesia Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Jurnal Penelitian Pendidikan IPA (JPPIPA) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Applied Data Sciences Economic Development Analysis Journal Proceeding Of International Conference On Education, Society And Humanity Indonesian Journal of Statistics and Its Applications
Suci Astutik
Departement Of Statistics, University Of Brawijaya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Transportation Other

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Principal Component Regression Modelling with Variational Bayesian Approach to Overcome Multicollinearity at Various Levels of Missing Data Proportion Balqis, Nabila Azarin; Astutik, Suci; Solimun, Solimun
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 4 (2022): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i4.10223

Abstract

This study aims to model Principal Component Regression (PCR) using Variational Bayesian Principal Component Analysis (VBPCA) with Ordinary Least Square (OLS) as a method of estimating regression parameters to overcome multicollinearity at various levels of the proportion of missing data. The data used in this study are secondary data and simulation data contaminated with collinearity in the predictor variables with various missing data proportions of 1%, 5%, and 10%. The secondary data used is the Human Depth Index in Java in 2021, complete data without missing values. The results indicate that the multicollinearity in secondary and original data can be optimally overcome as indicated by the smaller standard error value of the regression parameter for the PCR using VBPCA method which is smaller and has a relative efficiency value of less than 1. VBPCA can handle the proportion of missing data to less than 10%. The proportion of missing data causes information from the original variable to decrease, as evidenced by immense MAPE value and the parameter estimation bias that gets bigger. Then the cross validation (Q^2 ) value and the coefficient of determination (adjusted R^2 ) are get smaller as the proportion of missing data increases. 
COVID-19 Vaccination and PPKM Policy with the Implementation of the Fuzzy Sugeno Method to Income Classification Wahyuni, Djihan; Sumarminingsih, Eni; Astutik, Suci
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 4 (2022): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i4.10096

Abstract

This study aims to determine the implementation of Fuzzy Sugeno in classifying textual data obtained from Twitter so as to determine the polarity of public opinion regarding PPKM policies and Covid-19 vaccinations. This study uses primary data via Twitter related to COVID-19 vaccination and PPKM policies in Indonesia starting from February 9, 2021 to January 17, 2022. There are several stages carried out, namely data collection, data pre-processing, data labeling, data weighting. , identification of membership functions, determination of fuzzy sets, formation of classification systems, and evaluation of classification results. The results of this study explain that Fuzzy Sugeno's performance in classifying tweets is quite good with an average accuracy of 89.13%. Meanwhile, public opinion regarding PPKM policies and Covid-19 vaccinations tends to be balanced with 36.92% of tweets classified as positive sentiments, 22.85% negative sentiments, and another 40.23% classified as neutral sentiments. In addition, the fuzzy set that is formed based on the data observation method is very well done because it is able to adjust the frequency of the data in each category. This really helps improve the performance of the built classification system. 
Bayesian IGARCH Modeling of Jakarta Composite Index Volatility Using Hamiltonian Monte Carlo Algorithm Maulana, Eka Dani; Sumarminingsih, Eni; Nurjannah; Astuti, Ani Budi; Astutik, Suci
Science and Technology Indonesia Vol. 11 No. 1 (2026): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.1.261-279

Abstract

Time series models that model volatility in financial data, especially in stock market indices such as the Jakarta Composite Index (JCI), are Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. Following the ratification of the revised Armed Forces Law in March 2025, the JCI experienced increasing volatility, indicating persistent volatility. The problems in the JCI data require a time series model that can capture persistent volatility, namely the Integrated Generalized Autoregressive Conditional Heteroskedasticity (IGARCH) model. Parameter estimation for IGARCH models generally uses the Maximum Likelihood Estimation (MLE) method, which has limitations in handling parameter uncertainty. The Bayesian approach can address parameter uncertainty through the Markov Chain Monte Carlo (MCMC) methods. Among these, Hamiltonian Monte Carlo (HMC) is more efficient than Metropolis-Hastings and Gibbs Sampling, particularly in exploring complex posterior distributions. This study utilizes daily closing price data of the Jakarta Composite Index (JCI) as the main observation variable, observed from April 3, 2023, to April 9, 2025. This study aims to construct a volatility model for the Jakarta Composite Index (JCI) using a Bayesian IGARCH model with an HMC algorithm. This research only uses the IGARCH(1,1) model. The model has a strong ability to capture the JCI’s volatility structure, and its point forecasts are stable. However, credible intervals reveal the uncertainty level, so the volatility of JCI may decrease or increase.
Flood Prediction Using Modeling Extreme Rainfall in East Java, Indonesia Irsandy, Diego; Astutik, Suci; Astuti, Ani Budi
Plantropica: Journal of Agricultural Science Vol. 11 No. 1 (2026): Februari
Publisher : Department of Agronomy, Faculty of Agriculture, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jpt.2026.011.1.2

Abstract

Extreme value theory (EVT) is a statistical method that is concerned with the analysis of the extreme values of a distribution. EVT is often used to model the behavior of rare and extreme events, such as floods caused by extreme rainfall phenomena. There are two methods for identifying the movement of extreme values, namely Block Maxima (BM) and Peaks over Threshold (POT). The Generalized Extreme Value (GEV) distribution has three parameters and is used to model the distribution of extreme values using the BM method. On the other hand, the classic method of EVT does not capture uncertainty in the data. The Bayesian method is one of the statistical methods that can use information from data and prior knowledge. This research aims to model EVT-BM using a Bayesian approach for rainfall data at eleven weather stations in Jawa Timur. The result shows that all rainfall distributions at different weather conditions have a value of the parameter shape equal to 0, which implies a Weibull distribution. This paper also provides return level of 6 months, 2, 5, and 10 years respectively.
Pengenalan Peluang dan Regresi Linier Sederhana pada Siswa di Sanggar Wira Damai Malaysia Astutik, Suci; Darmanto, Darmanto; Nur Silviyah Rahmi; Rismania Hartanti Putri Yulianing Damayanti; Alya Fitri Syalsabilla; Aurora Gema Bulan Octavia
ABDI: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 8 No 1 (2026): Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : Labor Jurusan Sosiologi, Fakultas Ilmu Sosial, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/abdi.v8i1.1246

Abstract

Tujuan dari kegiatan pengabdian masyarakat ini adalah agar siswa dapat meningkatkan kompetensi dalam melakukan pengolahan data statistik, khususnya teori peluang dan analisis regresi sebagai bekal siswa di masyarakat. Sasaran kegiatan pengabdian ini adalah siswa di Sanggar Wira Damai Malaysia. Pengabdian masyarakat dilakukan melalui pemberian materi dan diskusi tentang pemahaman dan aplikasi teori peluang dan analisis regresi, guna meningkatkan produktivitas dan keberlanjutan Sanggar Wira Damai Malaysia. Kegiatan pengabdian masyarakat diikuti sebanyak 28 orang peserta didik di Sanggar Wira Damai Malaysia. Untuk mengetahui sejauh mana efektivitas pelaksanaan kegiatan pengabdian masyarakat ini, dilakukan evaluasi melalui observasi deskriptif siswa sebelum dan setelah kegiatan. Selanjutnya untuk mengetahui apakah pengabdian masyarakat ini dapat meningkatkan kemampuan siswa secara signifikan, dilakukan uji t berpasangan. Hasil dari uji berpasangan menunjukkan bahwa tidak terdapat perbedaan yang signifikan antara sebelum dan setelah pemberian materi (p value > 0,05). Hal ini karena materi baru bagi siswa dan keterbatasan kemampuan siswa dalam berhitung.
The Clustering of Provinces in Indonesia by The Economic Impact of Covid-19 using Cluster Analysis: Pengelompokkan Provinsi di Indonesia dengan Ekonomi Terdampak Covid-19 Menggunakan Analisis Cluster Pusdiktasari, Zerlita Fahdha; Sasmita, Widiarni Ginta; Fitrilia, Wulaida Rizky; Fitriani, Rahma; Astutik, Suci
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p117-129

Abstract

The Covid-19 pandemic has hit Indonesia since March 2020. Several policies have been issued by the Indonesian government to reduce the level of the spread of Covid-19. This policy has an impact on various fields of life, especially the economic sector in various sectors. This study was conducted to analyze the grouping of provinces whose economies are at risk of being affected by Covid-19 based on various economic sectors, namely the unemployment rate, the percentage of poor people, the provincial minimum wage, and the occupancy rate of hotels using cluster analysis. Cluster analysis was performed using several hierarchical methods, namely Simple, Complete, Average, and Centroid Linkage and Ward. The Cophenetic correlation coefficient (rCoph) was used to determine the best method, while the number of clusters was determined based on the Dunn, Connectivity, and Silhoutte indexes. The analysis result shows that Average Linkage is the best method with two clusters. The first cluster consists of all provinces in Indonesia except Papua, whose economy is highly at risk of being affected by Covid-19, characterized by a low percentage of the poor and a low provincial minimum wage, as well as high levels of open unemployment and hotel occupancy rates. Meanwhile, the second cluster consists of the Province of Papua, which is an economic group with a low risk of being affected by Covid-19. By looking at the impact of the Covid-19 disaster, the government can make recovery efforts and generalize economic recovery policies due to Covid-19 which have an impact on the economy of almost all provinces in Indonesia.
Haversine-Based Geographically Weighted Panel Regression of Human Development in Gorontalo (2016–2025) Debora Dwi Kurniawati; Henny Pramoedyo; Suci Astutik; Friansyah Gani
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40886

Abstract

Spatial disparities in human development indicate that socioeconomic factors may influence development outcomes differently across locations. This study aims to analyze spatially varying relationships between the Human Development Index and its key determinants in districts and cities in Gorontalo Province, Indonesia, during the period 2016--2025. The analysis uses balanced panel data and models human development as a function of mean years of schooling, life expectancy at birth, and real per capita expenditure. A geographically weighted panel regression approach is applied, with spatial relationships modeled using great-circle distances and an adaptive kernel weighting scheme, while a fixed-effects panel model serves as the global reference. The results reveal a clear spatial heterogeneity in the effects of the explanatory variables, where education consistently shows the strongest positive influence on human development in all regions, followed by health conditions. Economic expenditure exhibits a weaker and spatially varying effect and is not influential in the provincial capital. These findings underscore the importance of accounting for spatial heterogeneity in regional development analyses and support the formulation of place-based human development policies tailored to local conditions.
Co-Authors Abdullah Abdullah Abu Bakar Sambah, Abu Bakar Achmad Efendi Alya Fitri Syalsabilla Ani Budi Astuti Ani Budi Astuti Ari Purwanto Sarwo Prasojo Atiek Iriany Aulia, Silvia Intan Aurora Gema Bulan Octavia Azizah, Laila Nur Balqis, Nabila Azarin Bestari Archita Safitri Budiarti, Laelita Damayanti, Rismania Hartanti Putri Yulianing Darmanto Darmanto Darmanto Darmanto Debora Dwi Kurniawati Dewi Kurnia Sari Dewi, Vita Rosiana Diego Irsandy Djihan Wahyuni effendi, Achmad Elok Pratiwi Eni Sumarminingsih Evellin Dewi Lusiana, Evellin Dewi Fachri Faisal Fahimah Fauwziyah Fairuz Zada Zayyana Fakhrunnisa, Atmadani Rahayu Fernandes, Adji Achmad Rinaldo Fitriani, Suci Fitrilia, Wulaida Rizky Friansyah Gani Handayani, Sri Heni Kusdarwati Henny Pramoedyo Henny Pramoedyo Henny Pramoedyo Husnul Khatimah Irsandy, Diego Ismi Chai Runnisa Isnani Darti Kusdarwati, Heni Lee, Muhammad Hisyam Lestari, Dwi Retno Loekito Adi Soehono Loekito Adi Soehono Lusia, Dwi Ayu Lusiana, Evelin Dewi Maharani, Adinda Gita Maisaroh, Ulfah Mashfia, Fidia Raaihatul Masrokhah, Dwi Maulana, Eka Dani Meilina Retno Hapsari Meilinda Trisilia Muhammad, Alifiandi Rafi Nanda Rizqia Pradana Ratnasari, Nanda Rizqia Pradana Negara, Nur Aminah Kusuma Ni Wayan Surya Wardhani Ni Wayan Surya Wardhani Nisa Dwirahma Widhiasih Novi Nur Aini Nur Iriawan Nur Silviyah Rahmi Nurjannah Nurjannah Nurjannah Ola, Petrus Kanisius pramoedyo, henny Pratama, Muhamad Liswansyah Pusdiktasari, Zerlita Fahdha Qurrotu A’yun Nafidah Rahma Fitriani Rahma Fitriani Rahmi, Nur Silviyah Ramifidisoa, Lucius Risda, Intan Fadhila Rismania Hartanti Putri Yulianing Damayanti Rohma, Usriatur Rozy, Agus Fachrur Salsabila, Imelda Saniyawati, Fang You Dwi Ayu Shalu Sasmita, Widiarni Ginta Sera Yunarizal P Setiarini, An Nisa Dwi Shahuneeza Naseer, Mariyam Siti Nurmardia Abdussamad Solimun, Solimun Sugiono Sugiono Sumarminingsih, Eni Susanto, Mohammad Hilmi Susi Wuryantini Syalsabilla, Alya Fitri Theresia Mitakda, Maria Bernadetha Tiza Ayu Virania Viera Wardhani Wahyuni, Djihan Widiarni Ginta Sasmita Wulaida Rizky Fitrilia Wulaida Rizky Fitrilia Zamelina, Armando Jacquis Federal Zerlita Fahdha Pusdiktasari