Vol. 8 No. 02 (2025): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
This volume presents seven cutting-edge research articles in the fields of computer science and applied statistics. This edition features a diverse range of data analysis methods, from robust regression for handling outliers in poverty modeling, Random Forest-based imputation techniques for missing data, to clustering algorithms for grouping forest fire hotspots and poverty-stricken areas in Indonesia. The articles in this volume also explore the application of machine learning and deep learning, including the prediction of lignin content in rice bran using K-Nearest Neighbor with PCA preprocessing, as well as student dropout risk prediction using Long Short-Term Memory (LSTM) based on longitudinal academic performance data. Overall, the contributions in this volume demonstrate the application of modern computational methods to address real-world problems in social, environmental, agricultural, and higher education domains, making it relevant reading for researchers, data science practitioners, and policymakers.
