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All Journal JuSTISe: Journal Data Science, Technology, Informatics and Security
Julian Utami
Universitas Kebangsaan Republik Indonesia

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Aplikasi Mobile Multi-Algoritma AI untuk Bisnis Konveksi Julian Utami; Oscar Hadikaryana; Iim Abdurrohim
Journal Data Science, Technology, Informatics and Security Vol 2 No 2 (2024): Journal Data Science, Technology, Informatics and Security (Desember 2024)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v2i2.4311

Abstract

Small and medium-sized garment enterprises often struggle with manual production recording and payroll estimation, leading to inefficiency. This study develops a mobile application integrating multiple artificial intelligence algorithms to improve business prediction accuracy. The research employed a Research and Development (R&D) method with a Rapid Application Development (RAD) approach. Eight years of historical production and payroll data were analyzed using three algorithms: Linear Regression, Random Forest Regression, and KMeans Clustering. The results indicate that the application enhanced recording efficiency, Random Forest outperformed Linear Regression on fluctuating data, and K-Means effectively recommended the best-performing employees. In conclusion, the system contributes to digitalization and data-driven decisionmaking in the garment sector.
Co-Authors Iim Abdurrohim Oscar Hadikaryana