Predicting the Readiness of Indonesia Manufacturing Companies toward Industry 4.0: A Machine Learning Approach

TANJUNG, SEAN YONATHAN and Yahya, Kresnayana and Halim, Siana (2021) Predicting the Readiness of Indonesia Manufacturing Companies toward Industry 4.0: A Machine Learning Approach. [UNSPECIFIED]

[thumbnail of Publikasi1_94032_7213.pdf] PDF
Publikasi1_94032_7213.pdf

Download (337kB)
[thumbnail of Publikasi4_94032_7213.pdf] PDF
Publikasi4_94032_7213.pdf

Download (2MB)

Abstract

This research discusses Indonesias readiness to implement industry 4.0. We classified the Indonesia manufacturing companies readiness, which is listed in the Indonesia Stock Exchange, in industry 4.0 based on the 2018 annual reports. We considered 38 variables from those reports and reduced them using principal component analysis into 11 variables. Using clustering analysis on the reduced dataset, we found three clusters representing the readiness level in implementing industry 4.0. Finally, we used the decision tree for analysing the classification rules. As the finding of this study, Total book value of the machine is the variable that defined the readiness of a company in industry 4.0. The bigger those values are, the more ready a company to compete in industry 4.0. The other measures, i.e., Total cost of revenue by total revenue; Direct labor cost; Total revenue/Total employee and Transportation cost/Total revenue, will define the readiness of a manufacturing company to transform into industry 4.0. or not ready to transform into industry 4.0.

Item Type: UNSPECIFIED
Uncontrolled Keywords: Industry 4.0., principal component analysis, clustering, classification, decision tree.
Subjects: H Social Sciences > HA Statistics
Divisions: Faculty of Industrial Technology > Industrial Engineering Department
Depositing User: Admin
Date Deposited: 03 Jun 2021 13:21
Last Modified: 09 Sep 2021 21:27
URI: https://repository.petra.ac.id/id/eprint/19514

Actions (login required)

View Item
View Item