Vol. 1 No. 3 (2026): BIMA March 2026 Issue
This issue presents various research studies discussing the application of machine learning in the fields of education, healthcare, agriculture, and public policy. In general, the articles published in this issue emphasize the importance of data-driven predictive models in improving decision-making accuracy and system efficiency.
Research in the field of education indicates that ensemble learning approaches can improve the early detection of at-risk students, particularly on imbalanced datasets. In the healthcare sector, machine learning models have proven effective for the early prediction of diseases such as diabetes and cervical cancer, with the addition of explainable AI approaches to enhance the interpretability of results. In the agricultural sector, comparative studies show that simple models can still deliver optimal performance in predicting crop yields. Meanwhile, social media-based sentiment analysis provides insights into public perceptions of government policies in a more objective manner.
Overall, this issue highlights the critical role of machine learning in addressing complex problems adaptively, accurately, and practically across various sectors.
Published:
2026-03-31
