Semantic Scholar Open Access 2023 1 sitasi

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

Muhammad Isa Ansori Ririen Kusumawati M. A. Hariyadi

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Abstrak

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.

Penulis (3)

Muhammad Isa Ansori

Ririen Kusumawati

M. A. Hariyadi

Format Sitasi

APA MLA BibTeX

Ansori, M.I., Kusumawati, R., Hariyadi, M.A. (2023). Prediction of Service Level Agreement Time of Delivery of Goods and Documents at PT Pos Indonesia Using the Random Forest Method. https://doi.org/10.25008/ijadis.v4i2.1281

Akses Cepat

Lihat di Sumber doi.org/10.25008/ijadis.v4i2.1281

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 1×
Sumber Database: Semantic Scholar
DOI: 10.25008/ijadis.v4i2.1281
Akses: Open Access ✓