Multiple Linear Regression for Predicting the Ship Booking Time: A Case Study at PT. Samudera Indonesia

Tri Basuki, Kurniawan and Aldi, Alvino (2023) Multiple Linear Regression for Predicting the Ship Booking Time: A Case Study at PT. Samudera Indonesia. Journal of Data Science, 2023 (24). pp. 1-14. ISSN 2805-5160

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A statistical method called multiple linear regression (MLR), or just multiple regression, makes use of many explanatory variables to forecast the value of a response variable. We studied PT. Samudera Indonesia, a company in the shipping sector, for this paper. One of the companies providing services for maritime transportation is this one, which deals with the inflow and outflow of commodities. Our study focuses on the application of ship docking time prediction at PT. Samudera Indonesia, which is situated at Boom Baru port in Palembang. This research makes use of historical data on the ship's docking time during the preceding three (3) years, utilizing multiple linear regression techniques. Using the company's dataset for the years 2018 to 2020 which consists of 70% training data and 30% testing data the experiment was conducted and recorded. The model's performance has yielded very positive results, as evidenced by the 1.132 RSME (root mean square error) number, 1.075 absolute error, and 1.01% relative error. These numbers closely matched the initial figures that the company had documented.

Item Type: Article
Uncontrolled Keywords: Data Mining, Production Prediction, Multiple Linear Regression Algorithm
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA76 Computer software
Depositing User: Unnamed user with email
Date Deposited: 05 Dec 2023 04:05
Last Modified: 05 Dec 2023 04:05

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