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All Journal Limits: Journal of Mathematics and Its Applications Inferensi
Suliyanto, Suliyanto
Universitas Airlangga
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

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Modeling Youth Development Index in Indonesia Using Panel Data Regression for Binary Response with Random Effect Widyangga, Pressylia Aluisina Putri; Suliyanto, Suliyanto; Mardianto, M. Fariz Fadillah; Sediono, Sediono
Inferensi Vol 8, No 2 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i2.21734

Abstract

Indonesia has the largest youth population in Southeast Asia, yet its Youth Development Index (YDI) ranks only fifth in the region. This study aims to fill the gap in empirical research by modeling the YDI in Indonesia using binary logit and binary probit regressions with random effects, based on panel data from 34 provinces during 2020–2022. The YDI categories are defined according to the national target of 57.67 set by the Ministry of Youth and Sports Affairs. The analysis reveals that the binary probit model performs better than the binary logit model, with a classification accuracy of 93.14% and a McFadden R-squared of 0.4064. Gender Inequality Index (GII) and Expected Years of Schooling (EYS) significantly affect the likelihood of achieving the YDI target. These results highlight the critical role of gender equality and education in advancing youth development in Indonesia. The binary probit model provides a practical tool for policymakers to predict and evaluate the effectiveness of development programs targeting youth outcomes. This research not only contributes methodologically to the study of youth development using advanced econometric models but also offers policy-relevant insights that support the strategic goals of Indonesia Emas 2045. By identifying key leverage points such as gender equity and education access, the findings reinforce the importance of inclusive and evidence-based planning to nurture a generation of resilient, empowered, and high-performing youth who can lead Indonesia toward a prosperous future.
Indeks Pembangunan Gender Indonesia dalam Perspektif Pendekatan Spasial dengan Pembobot Queen Contiguity Amelia, Dita; Permana, Made Riyo Ary; Yosifa, Adelia Frielady; Kurniawan, Ardi; Suliyanto, Suliyanto
Limits: Journal of Mathematics and Its Applications Vol 21, No 2 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v21i2.20260

Abstract

Isu gender menjadi fokus global karena ketimpangan dalam hak-hak dan kontribusi laki-laki dan perempuan dalam pembangunan. Pencapaian Indeks Pembangunan Gender (IPG) menjadi tolok ukur penting dalam upaya mencapai kesetaraan gender dan pembangunan manusia yang inklusif di Indonesia. Penelitian ini bertujuan untuk memodelkan Indeks Pembangunan Gender di Indonesia dengan pendekatan regresi spasial dengan variabel-variabel yang diduga mempengaruhi IPG. Metode yang digunakan dalam penelitian ini adalah regresi spasial dengan pembobot Queen Contiguity. Berdasarkan penelitian yang telah dilakukan dengan tiga jenis pemodelan didapatkan model terbaik dalam pemodelan Indeks Pembangunan Gender di Indonesia adalah model regresi spasial error dengan nilai AIC sebesar 154,950 dan nilai R2 sebesar 0,6643. Analisis spasial mengungkapkan adanya korelasi dan heterogenitas spasial antar wilayah, menyoroti pentingnya mempertimbangkan aspek spasial dalam merancang kebijakan untuk meningkatkan pembangunan gender di Indonesia. Dengan demikian, upaya perbaikan dan kesetaraan gender sebaiknya diterapkan dengan mempertimbangkan variabilitas spasial serta fokus pada aspek-aspek yang telah diidentifikasi melalui pemodelan ini.
Modeling the Percentage of Tuberculosis Cure in Indonesia Using a Multivariate Adaptive Regression Spline Approach Novianti, Dita Aris; Marwanda, Nadia Dwi; Saifudin, Toha; Suliyanto, Suliyanto
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20344

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium Tuberculosis. After India, Indonesia is the country with the second highest number of TB sufferers in the world. TB prevention efforts in Indonesia have been carried out, even since 1995. However, in general, 2006-2022 the TB cure in Indonesia tends to experience a downward trend. Therefore, it is important to know what variables have a significant effect and how the pattern relates to the percentage of TB cures. We urgently need this information to optimize TB handling efforts and achieve Sustainable Development Goals (SDGs) point 3, which focuses on good health and well-being. For that purpose, this study used the Multivariate Adaptive Regression Spline (MARS) approach. MARS is considered more flexible in overcoming cases of predictor variables that do not form a certain pattern to their response variables and can accommodate possible interactions between predictor variables. The best model was obtained at BF=18,MI=2, and MO=0 with minimum GCV value is 37.053 and R^2 is 91.6%, with significant predictor variables are food management sites meet the requirements according to standards, complete treatment, smoking population over 15 years, families with healthy latrines, and districts/municipalities implement healthy living germas policy. The significance of the nine predictors should prioritize enhancing the quality of health services for example ensuring a fair distribution of complete treatment for TB patients.
Co-Authors Dita Amelia Kurniawan, Ardi Mardianto, M. Fariz Fadillah Marwanda, Nadia Dwi Novianti, Dita Aris Permana, Made Riyo Ary Saifudin, Toha Sediono, Sediono Widyangga, Pressylia Aluisina Putri Yosifa, Adelia Frielady