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Menampilkan 1–2 dari 2 artikel
Comparative Analysis of Multiple Linear Regression and Random Forest in Predicting Student Academic Performance
Digital Business Intelligence Journal
Vol 2
, No 1
(2026)
This study aims to compare the performance of Multiple Linear Regression (MLR) and Random Forest Regression (RFR) in predicting student performance based on academic scores. Student performance is defined as the average of math scores, Reading Scores, and writing scores. This study uses a quantitative approach with a comparative design based on predictive modeling. The data used is secondary data from the Student Prediction dataset obtained through the Kaggle platform, which was processed using...
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Internet of Things Vulnerabilities in E-Commerce Supply Chains: A Literature Review Approach to Identifying and Addressing Security Risks
Digital Business Intelligence Journal
Vol 1
, No 2
(2025)
his study aims to explore the implementation of Internet of Things (IoT) technologies within the e-commerce supply chain using a systematic and comprehensive Systematic Literature Review (SLR) approach. By critically analysing a broad range of recent studies, it systematically identifies implementation patterns, integration barriers, and strategic opportunities that support efficiency and adaptability in digital supply chains. Findings reveal that IoT plays a pivotal role in enhancing logistics...
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DOI