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All Journal International Journal of Public Health Science (IJPHS) Jurnal Ilmu Pertanian Indonesia Jurnal Ekonomi Pembangunan EKSAKTA: Journal of Sciences and Data Analysis JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi JAM : Jurnal Aplikasi Manajemen Jurnal TIMES Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Kubik Journal of Accounting and Investment JURNAL KOLABORASI JIMKesmas (Jurnal Ilmiah Mahasiswa Kesehatan Masyarakat) Al-Jabar : Jurnal Pendidikan Matematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Desimal: Jurnal Matematika MUST: Journal of Mathematics Education, Science and Technology Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Socioeconomics and Development Jurnal Informatika Universitas Pamulang Journal of Applied Food Technology J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL PENDIDIKAN TAMBUSAI Teorema: Teori dan Riset Matematika Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jambura Journal of Mathematics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) ComTech: Computer, Mathematics and Engineering Applications Journal of Information System, Applied, Management, Accounting and Research Ecces: Economics, Social, and Development Studies Inferensi Journal of Data Science and Its Applications International Journal of Science, Engineering and Information Technology Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi MATH LOCUS: Jurnal Riset dan Inovasi Pendidikan Matematika PROFETIK: Jurnal Mahasiswa Pendidikan Agama Islam SRIWIJAYA JOURNAL OF ENVIRONMENT MATHunesa: Jurnal Ilmiah Matematika VARIANSI: Journal of Statistics and Its Application on Teaching and Research Aceh International Journal of Science and Technology Jurnal Sains dan Informatika : Research of Science and Informatic STATISTIKA Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) Jurnal Pendidikan Progresif Indonesian Journal of Statistics and Its Applications JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Info Kesehatan
Fitrianto, Anwar
Departemen Statistika, Fakultas MIPA, IPB University, Bogor 16680
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Journal : journal of applied informatics and computing

 1 
Clustering Time Series Forecasting Model for Grouping Provinces in Indonesia Based on Granulated Sugar Prices Amatullah, Fida Fariha; Ilmani, Erdanisa Aghnia; Fitrianto, Anwar; Erfiani, Erfiani; Jumansyah, L. M. Risman Dwi
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8840

Abstract

Clustering time series is the process of organizing data into groups based on similarities in specific patterns. This research uses the prices of granulated sugar in each province of Indonesia. According to USDA reports, sugar consumption in Indonesia in 2023 reached 7.9 million tons. On April 26, 2024, the price of granulated sugar peaked in the Papua Mountains at Rp29,320 per kg, while the lowest price was recorded in the Riau Islands at Rp16,460 per kg. The research aims to cluster provinces based on the characteristics of granulated sugar prices and to use forecasting models for each group. Two groups were formed based on the price patterns of granulated sugar over time. The provinces of Papua and West Papua are in group 2, while the other 30 provinces are in group 1. The best model developed using the auto ARIMA method is ARIMA (2, 1, 0), with a MAPE value of 2.36% for cluster 1, and ARIMA (1, 1, 1), with a MAPE value of 2.59% for cluster 2. These values are less than 10%, indicating that the models built using the auto ARIMA method for clusters 1 and 2 are suitable for forecasting.
Identification of Latent Dimensions of Digital Readiness and Typology of Districts/Cities in Indonesia Using PCA and K-Means Clustering Sari, Jefita Resti; Fahira, Fani; Zahra, Latifah; Fitrianto, Anwar; Alifviansyah, Kevin
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11487

Abstract

Digital transformation is a key agenda in Indonesia’s national development that requires balanced readiness across regions. However, the level of digital readiness among districts and cities still varies widely, highlighting the need for a typology that can comprehensively describe existing disparities. This study aims to identify the latent dimensions of digital readiness and to develop a regional typology of Indonesian districts/cities using Principal Component Analysis (PCA) and K-Means clustering. The data were obtained from the 2024 Indonesian Digital Society Index (IMDI), which consists of four pillars—Infrastructure and Ecosystem, Digital Skills, Empowerment, and Employment—with ten sub-pillars. PCA reduced these correlated indicators into two main latent components, namely Digital Capacity and Participation and Digital Infrastructure Foundation, which together explain 70.4% of the total variance. Cluster validation using the Silhouette Score and Davies–Bouldin Index (DBI) showed that K = 2 yielded the best internal validity (Silhouette = 0.402; DBI = 0.906), but a three-cluster configuration (K = 3) was adopted to obtain a more interpretable typology of high-, medium-, and low-readiness regions (Silhouette = 0.346; DBI = 1.007). Spatial mapping reveals that high-readiness districts are concentrated in Java, Bali, and parts of Sumatra, whereas low-readiness areas dominate eastern Indonesia. These findings confirm persistent digital inequality across regions and provide a quantitative basis for targeted policy interventions, including infrastructure development, digital literacy programs, and innovation ecosystem strengthening, to support an inclusive digital transformation in Indonesia.
Household Clustering in West Java Based on Stunting Risk Factors Using K-Modes and K-Prototypes Algorithms Yusran, Muhammad; Nuradilla, Siti; Putri, Mega Ramatika; Fitrianto, Anwar; Yudhianto, Rachmat Bintang
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11508

Abstract

Stunting remains one of Indonesia’s most persistent public health challenges, with West Java contributing the highest number of cases due to its large population and regional disparities in household welfare. Identifying household groups vulnerable to stunting is essential for designing targeted interventions that integrate nutrition, sanitation, and socio-economic development. This study introduces a data-driven clustering framework using the K-Modes and K-Prototypes algorithms to classify 22,161 households in West Java based on 26 indicators from the March 2024 National Socioeconomic Survey (SUSENAS), encompassing food security, sanitation, drinking water access, economic conditions, social assistance, and demographics. The K-Modes algorithm was applied to categorical data, while K-Prototypes integrated numerical and categorical variables, with parameter optimization performed using a grid search and the Elbow method. Clustering performance was evaluated through the Silhouette Score, Calinski–Harabasz Index, and Davies–Bouldin Index, followed by a bootstrapped stability analysis employing the Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). Results show that K-Prototypes outperformed K-Modes, yielding a higher Silhouette Score (0.6681 compared to 0.2922), higher CH Index (13,890.6 compared to 3,976.1), and lower DBI (0.4607 compared to 1.5274), indicating superior compactness and separation. Stability testing confirmed strong robustness, with mean ARI = 0.959 and mean NMI = 0.932 across 50 bootstrap replications. The optimal five-cluster structure identified distinct socioeconomic groups, with the highest stunting risk found among households with low income, limited housing space, inadequate sanitation, and more children under five. The findings highlight the effectiveness of K-Prototypes in modeling mixed-type data and support the design of evidence-based, regionally adaptive stunting reduction strategies aligned with Presidential Regulation No. 72/2021 on the Acceleration of Stunting Reduction.
Performance of Multivariate Missing Data Imputation Methods on Climate Data Widyawati, Amalia Safira; Fitrianto, Anwar; Silvianti, Pika
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11316

Abstract

Climate data plays an important role in various aspects of life. However, missing data is often found, which can interfere with data processing and reduce the quality of analysis. Therefore, appropriate handling methods are needed to ensure that the analysis results remain valid. This study aims to compare the performance of several imputation methods for missing multivariate data based on the identification of actual missing data patterns, and to determine the appropriate imputation method based on the mechanism of missing data. This study also aims to apply the best method to data with actual missing data patterns to assess its effect on descriptive statistical changes required for further climatological analysis. The methods used include monthly averages, missRanger, k-Nearest Neighbor (k-NN), and Iterative Robust-Model Imputation (IRMI). The missing data information was obtained from Global Surface Summary of the Day (GSOD) data, namely temperature, precipitation, humidity, pressure, and wind speed variables with a daily frequency for 11 years, with a missing data proportion of 11.4%. The missing data patterns were then applied to relatively complete NASA Power data to evaluate the imputation results. The results show that IRMI is less capable of handling extreme missing data conditions, namely 17 completely missing rows. In contrast, k-NN, missRanger, and monthly averages provided better results in both extreme and non-extreme conditions. Of the four methods, monthly averages were chosen because they were able to overcome missing data while maintaining multivariate structure with 58% on sMAPE and 2.64% on relative difference.
Co-Authors -, Salsabila A. A., Muftih Aam Alamudi Abd. Rahman Adeline Vinda Septiani Affendi, Farit M Agus M Soleh Agus Mohamad Soleh Ahmad Syauqi Aimandiga, Carlya Agmis Aji Hamim Wigena Alfa Nugraha Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alfi Indah Nurrizqi Alfiryal, Naufalia Alifviansyah, Kevin Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amalia Kholifatunnisa Amanda, Nabila Amatullah, Fida Fariha Amelia, Reni Amir Abduljabbar Dalimunthe Amri Luthfi Najih Anadra, Rahmi Anang Kurnia Anang Kurnia Angelia, Riza Rahmah Anik Djuraidah Anisa Nurizki Annissa Nur Fitria Fathina Ardhani, Rizky Arifa, Panji Lokajaya Aristawidya, Rafika Askari, M. Aiman Asri Pratiwi, Asri Assyifa Lala Pratiwi Hamid Aulia Rifaldi, Destriana Az-Zahra, Putri Nisrina Azis, Tukhfatur Rizmah Aziza, Vivin Nur Bagus Sartono Budi Susetyo Budi Susetyo Bukhari, Ari Shobri Butar Butar, Rupmana Cahya Alkahfi Choon, Lai Ming Daswati, Oktaviyani Defri Ramadhan Ismana Deri Siswara Dessy Rotua Natalina Siahaan Dessy Siahaan Devi Permata Sari Dian Handayani Dwi Jumansyah, L.M. Risman Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Fadilah, Anggita Rizky Fahira, Fani Farit M Affendi Farit M. Afendi Farit M. Afendi Farit Mochamad Afendi Fatimah Fatimah Fauziah, Monica Rahma Febriati, Baiq Nina Fulazzaky, Tahira Ghina Fauziah Gustiara, Dela Hari Wijayanto Harismahyanti A., Andi Hasnataeni, Yunia Hasnita Hasnita Hasnita, Hasnita Heri Cahyono I Gusti Ngurah Sentana Putra I Made Sumertajaya Ilham Azagi Ilmani, Erdanisa Aghnia Imam Hanafi Indah, Yunna Mentari Indahwati Indahwati Indahwati Indahwati, Indahwati Irsyifa Mayzela Afnan Irzaman, Irzaman Ismah, Ismah Isna Shofia Mubarokah Iswan Achlan Setiawan Iswati Ita Wulandari Jamaluddin Rabbani Harahap Jap Ee Jia Jia, Jap Ee Jumansyah, L. M. Risman Dwi Jumansyah, L.M. Risman Dwi Kamila, Sabrina Adnin Kapiluka, Kristuisno Martsuyanto Kevin Alifviansyah Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Khusnia N. K. Khusnia Nurul Khikmah Kriswan, Suliana Kusman Sadik L.M. Risman Dwi Jumansyah La Ode Abdul Rahman La Ode Abdul Rahman Linganathan, Punitha lmam Hanafi M. Aiman Askari M.S, Erfiani Maisa Salsabila Manaf, Silmi Annisa Rizki Marshelle, Sean Megawati Megawati Mubarokah, Isna Shofia Muftih Alwi Aliu Muftih Alwi Aliu Muh Akbar Idris Muh. Sunan Muhadi, Rizqi Annafi Muhammad Irfan Hanifiandi Kurnia Muhammad Rizky Nurhambali Muhammad Syafiq Muhammad Yusran mutiah, siti Mutmainah, Zamrah Nabila Fida Millati Nabila Ghoni Trisno Hidayatulloh Nadira Nisa Alwani Nashir, Husnun Nisa Nur Aisyah Novi Hidayat Pusponegoro Nugraha, Adhiyatma Nur Hidayah Nur Khamidah NURADILLA, SITI Nurizki, Anisa Pangestika, Dhita Elsha Pika Silvianti Pradnya Sri Rahayu Prasetya, I Putu Gde Inov Bagus Pratiwi, Nafisa Berliana Indah Punitha Linganathan Putri Auliana Rifqi Mukhlashin Putri, Mega Ramatika Putri, Oktaviani Aisyah Rachmat Bintang Yudhianto Rachmat Bintang Yudhianto Rafika Aufa Hasibuan Rahmasari, Hazelita Dwi Rahmatun Nisa, Rahmatun Rais Ramadhan, Syaifullah Yusuf Reka Agustia Astari Reni Amelia Reni Amelia Retna Nurwulan Reyuli Andespa Riansyah, Boy Rifda Nida’ul Labibah Riska Yulianti, Riska Rizaldi Boer Rizki Manaf, Silmi Anisa Rizki, Akbar Rizqi, Tasya Anisah Sachnaz Desta Oktarin salsa bila Sari, Jefita Resti Seta Baehera Setyowati, Silfiana Lis Siau Hui Mah Siau Man Mah Silmi Annisa Rizki Manaf Siregar, Indra Rivaldi Siti Hafsah Siti Hasanah Siti Nur Azizah, Siti Nur Sofia Octaviana Sony Hartono Wijaya Suantari, Ni Gusti Ayu Putu Puteri Suliana Kriswan Sundari, Marta Tangdilomban, Claudian Tikulimbong Tangke, Nabillah Rahmatiah Titin Agustina Titin Yuniarty Yuniarty Unique DA Resiloy Uswatun Hasanah Utami Dyah Syafitri Utami, Annisa Putri Utomo, Agung Tri Vitona, Desi Vivin Nur Aziza Wahda, Aisya Wina Waliulu, Megawati Zein Wan Muhamad, Wan Zuki Azman Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Waode, Yully Sofyah Wawan Saputra Widyawati, Amalia Safira Winata, Hilma Mutiara Xin, Sim Hui Yenni Angraini Yudhianto, Rachmat Bintang Yuniarsyih R.A, Rizqi Dwi Yusuf, Fajar Athallah Zaenal, Mohamad Solehudin Zahid, Muhammad Farhan Zahra, Latifah Zein Rizky Santoso