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Christopher Sanjaya
Institut Teknologi Bandung
Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

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Predictive Analitycs Menggunakan Machine Learning Untuk Memprediksi Waktu Keterlambatan Berdasarkan Penyebab Keterlambatan Pada PT. Kereta Api Indonesia Christopher Sanjaya; Suhono Harso Supangkat
Jurnal Sistem Cerdas Vol. 3 No. 1 (2020): Artificial Intelligence untuk Indonesia
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v3i2.59

Abstract

Abstract - PT. Kereta Api Indonesia (KAI) is a company that regulates trains in Indonesia. Railways in Indonesia still often experience delays, especially in the Cibatu Purwakarta lane which will be the object of research in this study. This research is intended as an initial stage of applying machine learning to overcome the problem of tardiness by providing the best model for predicting tardiness and what things are causing the tardiness pattern. Machine learning models considered are decision tree regression, support vector machine regression, random forest regression, ensemble learning, and gradient boosting regression. From the best machine learning techniques, a model will be made to predict the delay based on the cause of the delay. Keywords – KAI, machine learning, predict the delay, cause of delay, Cibatu Purwakarta lane
Co-Authors Suhono Harso Supangkat