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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmu Sosial dan Humaniora CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Ketahanan Nasional MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika G-Tech : Jurnal Teknologi Terapan Inferensi Sains dan Matematika UNP Journal of Statistics and Data Science Jurnal Pendidikan Matematika Economic Development Analysis Journal Limits: Journal of Mathematics and Its Applications
Suliyanto
Department Of Mathematics, Faculty Of Science And Technology, University Of Airlangga, Indonesia
Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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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.
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.
Pengaruh Suplementasi Vitamin D dan BMI terhadap LVEF dengan Pendekatan Generalized Additive Models Longitudinal Dita Amelia; Suliyanto Suliyanto; Victoria Anggia Alexandra; Adelia Frielady Yosifa; Syavrilia Alfiatur Rakhma; Agnes Happy Julianto
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3378

Abstract

Cardiovascular diseases (CVD) are the leading cause of global mortality, with Left Ventricular Ejection Fraction (LVEF) being a key indicator of heart function. This study explores the impact of vitamin D supplementation and Body Mass Index (BMI) on LVEF using Generalized Additive Models (GAM) in longitudinal data from 47 elderly patients with hypovitaminosis D undergoing orthopedic surgery. LVEF was measured before surgery and at 1, 3, and 6 months post-intervention. GAM was employed to capture nonlinear relationships between variables with working correlation structures such as Independence, Exchangeable, Unstructured, and Autoregressive-1 (AR-1). The findings revealed a significant increase in vitamin D levels and LVEF following supplementation, while BMI remained relatively stable throughout the observation period. The best GAM model with AR-1 correlation structure achieved the lowest Quasi Information Criterion (QIC) score of 443.47, indicating a complex relationship between vitamin D and LVEF and a linear relationship between BMI and LVEF. Vitamin D demonstrated a significant nonlinear effect on LVEF improvement, whereas a 1-point increase in BMI raised LVEF by 0.291%. This study underscores the importance of vitamin D supplementation in enhancing heart function among elderly patients with hypovitaminosis D, supporting the development of evidence-based health policies
Indeks Pembangunan Gender Indonesia dalam Perspektif Pendekatan Spasial dengan Pembobot Queen Contiguity Dita Amelia; Made Riyo Ary Permana; Adelia Frielady Yosifa; Ardi Kurniawan; Suliyanto
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 2 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

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 R 2 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.
Spatial Analysis of Child Violence Victims in West Java in 2024 Using Geographically Weighted Negative Binomial Regression Suliyanto Suliyanto; Dita Amelia; Lisa Amanda Putri; Aurellia Calista Anggakusuma
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40390

Abstract

Violence against children remains a critical issue in Indonesia, with West Java consistently reporting high numbers of reported child violence victims. This study examines socioeconomic factors associated with the count of reported child violence victims across 27 districts and cities in West Java in 2024, using secondary administrative data obtained from Open Data Jabar. The explanatory variables include poverty rate (X1), average years of schooling (X2), number of divorce cases (X3, Labor Force Participation Rate (X4), and Open Unemployment Rate (X5). Diagnostic tests indicate the presence of spatial heterogeneity and overdispersion, supporting the application of a Geographically Weighted Negative Binomial Regression (GWNBR) model with a child population offset. Model performance comparison based on in-sample fit criteria shows that the GWNBR model provides superior fit (deviance = 42.94, AICc = 99.87) compared to the global Negative Binomial Regression model (deviance = 48.27, AIC = 105.63). The GWNBR results reveal substantial spatial variation: average years of schooling (X2) is statistically significant across all 27 regions, while the number of divorce cases (X3) is significant in 23 regions. Poverty rate (X1) shows localized significance in 16 regions. Labor force participation rate (X4) and unemployment rate (X5) each exhibit significance in 6 regions, though with distinct spatial patterns. These findings highlight geographically varying risk structures that cannot be adequately captured by global models and underscore the importance of spatially adaptive modeling for informing region-specific child protection policies. Although the analysis relies on reported administrative data that may not fully represent the true underlying prevalence of child violence, the results provide valuable spatial insights relevant to policy development aligned with SDG 3, SDG 4, and SDG 16.
Modelling Factors Affecting the Middle Income Trap in Indonesia Using Generalized Additive Models (GAM) Dita Amelia; Suliyanto Suliyanto; Azizah Atsariyyah Zhafira; Aulia Ramadhanti; Billy Christandy Suyono; Firqa Aqila Hizbullah
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.35119

Abstract

Indonesia is currently facing the risk of the Middle Income Trap (MIT), a condition in which economic growth stagnates after reaching middle-income status. This study aims to identify and model socio--economic factors affecting MIT at the provincial level in Indonesia during 2020--2023. The Generalized Additive Model (GAM) is employed to capture nonlinear and heterogeneous relationships between predictors and GRDP per capita with complex patterns that conventional linear or parametric models often fail to detect. The use of GAM in this context represents a methodological contribution, as studies applying GAM for MIT analysis in Indonesia remain very limited. This research therefore introduces a novel analytical approach by demonstrating how GAM can reveal flexible functional relationships and uncover nonlinear effects that are overlooked by traditional panel regression. GRDP per capita is modeled using six predictors: life expectancy, poverty rate, informal employment share, upper secondary education completion, food insecurity prevalence, and population density. The best model is obtained using the Gaussian family with an identity link, with five predictors showing nonlinear effects and food insecurity exhibiting a negative linear influence. The selected model demonstrates strong performance, indicated by an AIC value of 2743.279 and a R^2 of 98.6%, suggesting a very high explanatory power. In addition, the model achieves good predictive accuracy, with a MAPE of 8.04%. The findings support evidence-based policies aligned with Sustainable Development Goal (SDG) 8, promoting inclusive and sustainable economic growth.
Pemodelan Faktor yang Mempengaruhi Indeks Demokrasi Indonesia Menggunakan Spline Truncated Hanny Valida; M. Fariz Fadillah Mardianto; Dita Amelia; Suliyanto Suliyanto
Jurnal Pendidikan Matematika Vol. 3 No. 2 (2026): February
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v3i2.2478

Abstract

Penelitian ini bertujuan menganalisis faktor-faktor yang memengaruhi Indeks Demokrasi Indonesia (IDI) menggunakan pendekatan regresi spline linier terpotong nonparametrik. Data yang digunakan merupakan data sekunder cross-section dari 34 provinsi di Indonesia pada tahun 2024, dengan variabel prediktor berupa Indeks Pemberdayaan Gender, Indeks Kebebasan Pers, dan Indeks Pembangunan Manusia. Pemilihan model dilakukan menggunakan kriteria Generalized Cross Validation (GCV) untuk menentukan jumlah dan posisi knot yang optimal. Hasil analisis menunjukkan bahwa model terbaik diperoleh dengan tiga titik knot, menghasilkan nilai GCV sebesar 6,79 dan koefisien determinasi (R²) sebesar 89,37 persen. Hasil penelitian menunjukkan adanya hubungan nonlinier antara variabel prediktor dan IDI. Indeks Pemberdayaan Gender memberikan pengaruh positif pada tingkat rendah hingga menengah, namun berubah menjadi negatif pada tingkat yang lebih tinggi. Indeks Kebebasan Pers menunjukkan pengaruh positif pada tingkat rendah tetapi cenderung negatif setelah melewati titik tertentu. Sementara itu, Indeks Pembangunan Manusia memberikan pengaruh positif yang konsisten terhadap IDI. Temuan ini menunjukkan bahwa kualitas demokrasi di Indonesia dipengaruhi oleh dinamika sosial dan institusional yang kompleks.
Factors Affecting Interest in Revisiting Kare Tourism Village Based on Structural Equation Modeling M Fariz Fadillah Mardianto; Elly Pusporani; Suliyanto Suliyanto; Sri Endah Nurhidayati; Na’imatul Lu’lu’a; Marcelena Vicky Galena
Inferensi Vol 9 No 1 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i1.9951

Abstract

This research focuses on analyzing the factors that affect tourists' intentions to revisit Kare Tourism Village. Utilizing quantitative methods, primary data were gathered through questionnaires from 105 tourists who had previously visited the village. The SEM-PLS method was employed for analysis. In this study, several latent variables were identified, including facilities and services in Kare Tourism Village as exogenous latent variables, tourist satisfaction as both an endogenous latent variable and an intermediate variable, and tourist interest as the dependent variable. The findings reveal an value of 0.876 for tourist satisfaction, indicating that 87.6% of the variation in satisfaction can be explained by the model, which is considered strong. In contrast, the R² value for tourist interest is 0.548, suggesting that 54.8% of the variation in interest is explained by the model, classified as moderate. Additionally, the GoF value of 0.673 demonstrates a high model fit. Furthermore, the service variables in Kare Tourism Village significantly impact tourist satisfaction.
ANALYSIS OF FACTORS AFFECTING PNEUMONIA IN INDONESIAN TODDLERS USING NONPARAMETRIC REGRESSION WITH LEAST SQUARE SPLINE AND FOURIER SERIES METHODS Toha Saifudin; Suliyanto Suliyanto; Nabila Nurdin; Bryan Given Christiano Ginzel; Sabrina Salsa Oktavia; Jovansha Ariyawan; Mohammad Noufal Ubadah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0087-0104

Abstract

Pneumonia is the leading cause of death among children under five, with the highest prevalence in Indonesia found in West Papua Province (75%) and the lowest in North Sulawesi (0.3%). This study aims to analyze the factors influencing the prevalence of pneumonia in Indonesian toddlers using nonparametric regression approach by comparing Least Square Spline (LS-Spline) and Fourier Series. Data sourced from the Indonesian Ministry of Health website, consisting of 34 provinces in Indonesia in 2023, with one response variable (Y) and five predictor variables (X). The analyzed factors include the coverage of vitamin A supplementation, malnutrition rates, low birth weight prevalence, measles immunization coverage, and exclusive breastfeeding rates. The analysis was conducted by modeling with nonparametric Least Square Spline regression using up to three optimal knot points, then performing analysis using nonparametric regression with the Fourier series approach. The two methods were compared based on GCV and R², with the best model having lower GCV and higher R². The results showed that LS-Spline was better than Fourier Series, with a GCV value of 233.16 and a coefficient of determination of 92.5%. The findings reveal that the relationships between predictor factors and pneumonia prevalence are nonlinear, with varying influence patterns across different variable ranges. These results indicate that LS-Spline has a strong ability to explain data variability. The Fourier series is limited in this study because it is best suited for periodic data, unlike pneumonia data and its causal factors which do not show such patterns. The weakness of the Fourier Series in this study lies in its suitability for periodic data, while pneumonia cases and their causal factors do not follow such patterns. This study offers insights into health policy making to reduce pneumonia cases, improve their lives, in line with the SDGs target on Good Health and Well-being.
FORECASTING THE INFLATION RATE IN INDONESIA USING ARIMA-GARCH MODEL Toha Saifudin; Suliyanto Suliyanto; Fitriana Nur Afifa; Aini Divayanti Arrofah; Doni Muhammad Fauzi; Fachriza Yosa Pratama; Isryad Yoga Adyatma
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0955-0970

Abstract

Inflation is a key economic indicator that affects purchasing power, economic growth, and financial stability. Accurate forecasting is essential for policymakers to implement effective monetary and fiscal policies. However, traditional models like ARIMA (Autoregressive Integrated Moving Average) mainly capture general trends and often fail to address inflation volatility. This study enhances inflation forecasting accuracy by applying the ARIMA-GARCH hybrid model, which combines trend estimation with volatility modelling. Focusing on Indonesia’s inflation patterns using recent data, it addresses a gap in existing research. This type of research uses quantitative methods, and the data were obtained from the official website of Bank Indonesia. The dataset consists of 240 monthly Indonesian inflation data points spanning from September 2004 to August 2024. The ARIMA (0,1,1)-GARCH (2,0) model is used to analyze inflation trends and volatility dynamics. The model evaluation shows strong predictive performance, with a Mean Absolute Percentage Error (MAPE) of 2.73% and Root Mean Squared Error (RMSE) of 0.74 for training data. Testing data results in a MAPE of 18.95% and RMSE of 0.702, which remains within an acceptable range. These findings highlight the importance of incorporating volatility modelling in inflation forecasting to enhance economic decision-making. A reliable forecast mitigates economic uncertainty, thereby providing a stronger foundation for achieving long-term economic growth. This study contributes by demonstrating the practical application of ARIMA-GARCH in Indonesia’s inflation modelling, providing valuable insights for policymakers in managing inflation-related risks.
Co-Authors Adelia Frielady Yosifa Adelia Frielady Yosifa Adelia Putri Andini Aditya Syarifudin Akbar Agnes Happy Julianto Aini Divayanti Arrofah Aini Divayanti Arrofah Alfi Nur Nitasari Alfredi Yoani Ameliatul 'Iffah Ana, Elly Andreas, Christopher Anisa Laila Azhar Ardi Kurniawan Aulia Ramadhanti Aurellia Calista Anggakusuma Azizah Atsariyyah Zhafira Billy Christandy Suyono Bryan Given Christiano Ginzel Dhyana Venosia Diah Puspita Ningrum Dinnara Chairana Aisha Dita Amelia Dita Amelia Dita Amelia Dita Amelia Dita Amelia Doni Muhammad Fauzi Eko Tjahjono Elly Pusporani Fachriza Yosa Pratama Faya Najwatus Silma Fina Insyiroh Firqa Aqila Hizbullah Fitriana Nur Afifa Gabriella Agnes Budijono Hanny Valida Isryad Yoga Adyatma Jovansha Ariyawan Kimberly Maserati Siagian Kurniawan, Ardi Leni Sartika Panjaitan Lisa Amanda Putri M. Fariz Fadillah Mardianto Made Riyo Ary Permana Maelcardino Christopher Justin Mahfudhotin Mahfudhotin Marcelena Vicky Galena Marwanda, Nadia Dwi Mochamad Rasyid Aditya Putra Mohammad Noufal Ubadah Muhammad Rosyid Ridho Az Zuhro Mutyaravica, Astrid Nabila Nurdin Nadinta Kasih Amalia Suryono Nadya Lovita Hana Trisa Nafla Nara Yonay Najwa Khoir Aldawiyah Na’imatul Lu’lu’a Novianti, Dita Aris Nur Chamidah Nuzulia Anida Permana, Made Riyo Ary Rere Fetri Damanik Rindiani Ahmada Alisiah Sabrina Salsa Oktavia Salma Bethari Andjani Sumarto Sediono, Sediono Slavina Sri Endah Nurhidayati Sugha Faiz Al Maula Syavrilia Alfiatur Rakhma Toha Saifudin Utsna Rosalin Maulidya Victoria Anggia Alexandra Widyangga, Pressylia Aluisina Putri Yosifa, Adelia Frielady Zah, Alfian Iqbal