Prediction of Service Level Agreement Time of Delivery of Goods and Documents at PT Pos Indonesia Using the Random Forest Method

Muhammad Isa Ansori (Faculty of Science and Technology, Program Specification for Master Study in Computer Science, Universitas Islam Negeri Maulana Malik Ibrahim, Indonesia)
Ririen Kusumawati (Faculty of Science and Technology, Program Specification for Master Study in Computer Science, Universitas Islam Negeri Maulana Malik Ibrahim, Indonesia)
M. Amin Hariyadi (Faculty of Science and Technology, Program Specification for Master Study in Computer Science, Universitas Islam Negeri Maulana Malik Ibrahim, Indonesia)

International Journal of Advances in Data and Information Systems
Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems

This study aimed to predict the service level agreement travel time for goods and document shipments at PT Pos Indonesia (Persero) from the island of Java to the islands of Kalimantan, Sulawesi, Maluku and Papua. This is very important because of the high competition between the logistics industry which is getting faster and faster. The random forest method was chosen because this method is easy to use and flexible for various kinds of data. The prediction results with Random Forest in this study have a good level of accuracy, namely 83.86% of the average 4 trials. This shows that the Random Forest method is the right choice for managing the existing data model at PT Pos Indonesia.