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All Journal Jurnas Nasional Teknologi dan Sistem Informasi
Hasbul Hadi
Program Studi Magister Teknologi Informasi, Fakultas Teknik, Universitas Malikussaleh
Computer Science & IT Decision Sciences, Operations Research & Management

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Development of Work Program Submission System Using Predictive Data Analytics Based on Neural Network Algorithms at PT Pos Lhokseumawe Hasbul Hadi; Nurdin Nurdin
Jurnal Nasional Teknologi dan Sistem Informasi Vol 12 No 2 (2026): Agustus 2026
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v12i2.2026.172-180

Abstract

The digital transformation within PT. Pos Indonesia KC Lhokseumawe demands a more efficient, secure, and adaptive procurement system. This study aims to develop a web-based work program submission system that integrates predictive analytics and neural network algorithms to enhance procurement efficiency and the accuracy of budget forecasting. The system is built using a React.js-based frontend architecture and a FastAPI-based backend, with MongoDB as the database. The N-BEATS model is implemented for time series-based budget forecasting, while Neural Collaborative Filtering is employed to recommend vendors based on interaction history. Evaluation results demonstrate strong performance, with an R-squared value of 0.9965 for the forecasting model and an F1-score of 73.71% for the recommendation model. This integrated system provides procurement management features, budget forecasting, and tender recommendations, and is expected to improve business process efficiency at PT significantly.
Co-Authors Nurdin Nurdin