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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pendidikan Matematika
Valida, Hanny
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Transportation Other

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MODELING DEMOCRACY INDEX IN INDONESIA WITH MULTIVARIATE ADAPTIVE REGRESSION SPLINE APPROACH Saifudin, Toha; Suliyanto, Suliyanto; Nugraha, Galuh Cahya; Valida, Hanny; Nahar, Muhammad Hafidzuddin; Fortunata, Regina
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2347-2358

Abstract

Democracy is a system of government where citizens participate in political decision-making through freely elected representatives. To measure the quality of democracy in Indonesia, the Indonesian Democracy Index (IDI) is used as a composite indicator reflecting various aspects of political freedoms, civil liberties, and governance. The IDI score declined from 6.71 in 2022 to 6.53 in 2023, the lowest in 14 years, indicating disruption in Indonesia’s democracy. Therefore, it is necessary to identify the root causes of the disruption in Indonesia’s democracy through several indicators. This study analyzes the relationship between predictor variables, including socio-economic and development indicators, and IDI using the Multivariate Adaptive Regression Spline (MARS) approach. This study uses the MARS method by considering six predictor variables, namely the Human Development Index (HDI), Gender Empowerment Index (GEI), Information and Communication Technology Development Index (ICT-DI), Press Freedom Index (PFI), Poverty Depth Index (PDI), and High School Completion Rate (HSCR). The data used is secondary data from 34 Indonesian provinces in 2023 obtained from the Statistics Indonesia-BPS. The results showed that the best model was obtained with a combination of BF = 12, MI = 3, and MO = 1 resulting in a GCV value of 11.27 and R2 of 80%. MARS model interpretation identifies the significant influence of social and economic indicators on IDI and is able to explain 80% of data variability. The significance test shows that all predictor variables significantly affect the IDI, with the highest level of importance on the ICT-DI variable. Therefore, improving ICT-DI in each province needs to be a major concern as a strategic step to improve the democracy index in Indonesia and support the achievement of Sustainable Development Goal 16 on peace, justice, and strong institutions.
Mapping Food Insecurity: Spatial Modelling of Undernourishment Prevalence in Indonesia using Geographically Weighted Regression Saifudin, Toha; Chamidah, Nur; Ramadhina, Fidela Sahda Ilona; Al Hasri, Ilham Maulana; Trisa, Nadya Lovita Hana; Valida, Hanny; Setyawan, Muhammad Daffa Bintang
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32063

Abstract

Undernourishment is a major global issue, with significant impact observed in Indonesia. A method of assessing the prevalence of energy deficiency resulting from inadequate nutrition is through the Prevalence of Undernourishment (PoU) index. From 2019 to 2022, Indonesia's PoU increased gradually, reaching 10.21% in 2022, indicating growing undernourishment and unstable food availability. This study aims to utilize Geographically Weighted Regression (GWR) to identify and analyze the factors contributing to undernourishment. The data were obtained from the Central Bureau of Statistics (BPS) in 2024, covering 38 provinces in Indonesia. This study examined six factors: per capita spending, access to potable water, mean years of schooling, access to adequate sanitation, college participation rate, and mean food expenditure. The findings show that the GWR model outperformed the conventional model, demonstrating greater explanatory power by accounting for 96.1% of the spatial variation in undernourishment and achieving the lowest AIC value of 176.7052. These findings highlight the need for region-specific food security policies, particularly in eastern Indonesia. The results can inform targeted government interventions and guide future spatial econometric research on food security.
Analisis Hubungan Media Pembelajaran Konvensional dan Digital terhadap Learning Gain dan Partisipasi Aktif Siswa pada Pelajaran Matematika dengan Uji Chi-square dan Cramer’s V Valida, Hanny; Kurniawan, Ardi
Jurnal Pendidikan Matematika Vol. 3 No. 1 (2025): November
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v3i1.2193

Abstract

Penelitian ini bertujuan untuk menganalisis hubungan antara media pembelajaran konvensional dan digital terhadap learning gain dan partisipasi aktif siswa pada mata pelajaran Matematika di SD Kusuma Putra Surabaya. Penelitian menggunakan pendekatan kuantitatif dengan jenis komparatif. Sampel terdiri atas 40 siswa kelas 5 yang dibagi menjadi dua kelompok berdasarkan jenis media pembelajaran yang digunakan. Data dikumpulkan melalui tes (pre-test dan post-test) serta observasi partisipasi aktif. Analisis dilakukan menggunakan uji Chi-square untuk mengetahui signifikansi hubungan dan koefisien Cramer’s V untuk menentukan kekuatan hubungan antarvariabel. Hasil penelitian menunjukkan adanya hubungan yang signifikan. antara media pembelajaran dan learning gain siswa (p-value = 0,004; Cramer’s V = 0,27), namun tidak terdapat hubungan signifikan antara media pembelajaran dan partisipasi aktif siswa (p-value = 0,924; Cramer’s V = 0,0039). Dengan demikian, media digital memiliki hubungan yang signifikan dengan peningkatan hasil belajar, namun tidak menunjukkan hubungan yang berarti dengan tingkat partisipasi aktif siswa.
PREDICTION OF THE INDONESIA COMPOSITE INDEX (ICI) USING THE ARCH GARCH APPROACH AND THE FOURIER SERIES Fadillah Mardianto, M. Fariz; Valida, Hanny; Putri, Farah Fauziah; Fauzi, Doni Muhammad; Pusporani, Elly
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/barekengvol20iss1pp0271-0286

Abstract

The Indonesia Composite Index (ICI) is a key indicator of stock market performance in Indonesia, often experiencing high volatility due to various domestic and global economic factors. In recent years, ICI has shown a significant upward trend, influenced by both local and international factors. In 2024, from June to October, the ICI saw a notable increase, reaching its highest value since 2020 at Rp 7,670. Despite fluctuations in stock prices, the rise in ICI reflects a positive outlook for the Indonesian stock market, attracting both domestic and foreign investors. This study aims to predict ICI movements using ARIMA-GARCH and Fourier Series approaches. The ARIMA model is employed to analyze time series data, while the ARCH-GARCH model addresses heteroskedasticity in residual variance. For comparison, the Fourier Series Estimator is applied to capture seasonal patterns in the data. Although ICI volatility is driven by a range of external macroeconomic and geopolitical factors, this study focuses on univariate modeling to evaluate the predictive capability of the index’s own historical movements, without involving exogenous variables. The data used comes from Investing.com. Weekly ICI data from March 2020 to June 2024 is used, split into training and testing sets. The analysis results indicate that the ARIMA-GARCH method provides higher accuracy, with a Mean Absolute Percentage Error (MAPE) of 5% (out-sample), compared to the Fourier Series method, which has a MAPE of 8.57%. This suggests that ARIMA-GARCH is more effective in predicting ICI trends, reflecting its ability to account for volatility and market changes more accurately.
Co-Authors Al Hasri, Ilham Maulana Ardi Kurniawan Elly Pusporani Fadillah Mardianto, M. Fariz Fauzi, Doni Muhammad Fortunata, Regina Nahar, Muhammad Hafidzuddin Nugraha, Galuh Cahya Nur Chamidah Putri, Farah Fauziah Ramadhina, Fidela Sahda Ilona Setyawan, Muhammad Daffa Bintang Suliyanto Suliyanto Toha Saifudin Trisa, Nadya Lovita Hana