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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics LEMMA: Letters Of Mathematics Education MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Martabe : Jurnal Pengabdian Kepada Masyarakat Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Varian Pelita Eksakta Majalah Ilmiah Matematika dan Statistika (MIMS) Journal of Applied Data Sciences Journal of Science and Technology MATHunesa: Jurnal Ilmiah Matematika Journal of Mathematics UNP UNP Journal of Statistics and Data Science Mathematical Journal of Modelling and Forecasting Journal of Statistics and Data Science
Devni Prima Sari
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : journal of applied informatics and computing

 1 
Hierarchical Clustering of Education Indicators in Papua Island: A Ward’s Method Approach Prastika, Ifa; Sari, Devni Prima
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9740

Abstract

Education development aims to ensure inclusive, equitable education and increase learning opportunities for all Indonesian citizens. Papua Island is still not an island with a high education level; data on education indicators indicate this in each Regency / City on the island of Papua, with a value below the national average. Identifying districts/cities is needed to improve education, so clustering is carried out using the Ward method. This research aims to group and map regencies/cities on the island of Papua based on education indicators. The results of this study are expected to be a consideration and benchmark for the government in making decisions regarding education in districts/cities on the island of Papua, considering the region's characteristics. This is an applied research with the data type used, namely secondary data on education indicators in Papua Island in 2022. Data sources are obtained from the official website of the Central Bureau of Statistics of each province on the island of Papua. Four education indicators are taken into account in this research, namely the School Participation Rate (SPR), the Gross Enrollment Rate (GER), the Net Enrollment Ratio (NER), and the Average Years of Schooling (AYS), which are then detailed into 10 variables. The cluster analysis process uses Euclidean distance and cluster validation using the Dunn Index. The results showed that 3 clusters formed. Cluster 1 consists of 27 districts/cities; this first group is classified as a high level of education. Cluster 2 consists of 7 districts/cities with a medium level of education, and Cluster 3 has eight districts/cities with a low level of education—cluster results based on the highest Dunn Index validation value of 0.414.
Regional Clustering in Sumatera Based on Walfare Indicators Using Fuzzy C-Means Putri, Rahma Dana; Sari, Devni Prima
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10103

Abstract

Welfare refers to a condition in which individuals have sufficient means to meet both physical and spiritual needs. In Indonesia, welfare is a national goal, yet Sumatra experiences the highest development disparity, contributing to unequal welfare distribution across regions. This study aims to cluster regions in Sumatra based on welfare indicators using the Fuzzy C-Means (FCM) method, analyze cluster characteristics, and provide policy recommendations for decision-makers. FCM is used because it accommodates uncertainty and allows each data point to belong to more than one cluster, making it suitable for welfare analysis. Cluster validity was tested using Partition Coefficient Index (PCI) and Silhouette Coefficient, both indicating that the optimal number of clusters is two. The results show that Cluster 1 consists of 62 regions with relatively higher welfare conditions, while Cluster 2 includes 92 regions with lower welfare characteristics. One notable member of Cluster 2 is Ogan Komering Ulu, with a high membership degree of 0.869. Recommended policies include improving access to clean water and healthcare, enhancing education, strengthening local economies, and delivering targeted social assistance to underdeveloped areas. For Cluster 1, sustainable development efforts should be maintained.
Digital Gold Price Prediction on Indogold Platform Using Generalized Autoregressive Conditional Heteroskedasticity Model Devni Prima Sari; Siti Syadza Najiba
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13524

Abstract

The digital gold market in Indonesia has experienced significant growth, with transaction values reaching IDR 53.3 trillion during January–November 2024, representing a 556 percent increase compared to the previous year. Despite this rapid growth, digital gold prices exhibit high volatility characterized by volatility clustering and conditional heteroskedasticity that conventional time series models cannot adequately capture. Although the GARCH model has been widely applied to predict physical gold prices, no prior study has specifically examined digital gold price volatility on Indonesian fintech-based trading platforms. This study aims to construct a univariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model based solely on historical price movements to predict digital gold prices on the Indogold platform and evaluate its predictive accuracy. Accordingly, the proposed model relies exclusively on historical price data and does not incorporate external macroeconomic variables, such as exchange rates, inflation, interest rates, or international gold prices. The data used consisted of weekly closing prices of digital gold on the Indogold platform from January 5, 2020, to December 29, 2024, totaling 261 observations. Analysis was conducted using RStudio software through logarithmic return calculation, data splitting via trial and error (selected proportion 80%:20%), Augmented Dickey-Fuller stationarity testing, ARMA order identification through ACF and PACF plots followed by AIC-based model selection, ARCH-LM effect testing, GARCH model estimation, and Ljung-Box and ARCH-LM diagnostic testing. The best model identified was ARMA(2,2)-GARCH(1,1) with the conditional variance equation σₜ² = 0.000073 + 0.405334εₜ₋₁² + 0.476482σₜ₋₁². The model passed all diagnostic tests with Ljung-Box p-value = 0.3362 and ARCH-LM p-value = 0.9999. Prediction accuracy evaluation on the test data yielded MAPE = 1.8141%, which is categorized as highly accurate according to Lewis (1982), indicating strong price forecasting performance; however, its suitability as an investment decision-making tool requires further evaluation of return, risk, and trading strategy performance beyond price accuracy alone.
Co-Authors Abda Abda Adellia, Clara Febby Adhitya Ronnie Effendie, Adhitya Ronnie Afifah Humayrah Amelia Nurul Medika Anggraini, Fira Anisa 1004 arsilla uswatunnisa Danardono Danardono Dedi Rosadi Deswita, Siska Dina Agustina Dina Fakhriyana Emmelia Safani Fadhilah Fitri Fadhilah Fitri Fadil Ahmat Zikran Febri, Fera Malianis Filfiqri, Hamimatul Gulo, Trimodesman Hardinsyah Gusvira Widuri irwandi irwandi Jayawarsa, A.A. Ketut Jeri Jefrianto Lestari, Adika Risky Maulani Meutia Rani Media Rosha Mei Syarah Anis Miftha Delinda Muhammad Rashif Hilmi nur hafizah Pepi Novianti Prastika, Ifa Pratama, Tasya Putri Puja Ermiati Putri, Elisa Ananda Putri, Muthiara Hazimah Putri, Rahma Dana Putriyana Nursal Rara Sandhy Winanda Riri Indriani Rohadatul Aisy Sadli, Wanda Hamidah Siti Syadza Najiba Soleha, Annisa Sukra Hamna Sumita, Nurmaya Tessy Octavia Mukhti Tri Rahmayani Ulfasari Rafflesia Ulfasari Rafflesia Wardah Hasna Afifah Wardana, Yuni Yolandafitri Zulvia Yuki Fitria