Analisa Performa K-Means dan DBSCAN dalam Clustering Minat Penggunaan Transportasi Umum

Kristianto, Ariel (2021) Analisa Performa K-Means dan DBSCAN dalam Clustering Minat Penggunaan Transportasi Umum. Jurnal Ilmiah Elektronika dan Komputer, 14 (2). pp. 368-372. ISSN 1907-0012

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Official URL: https://journal.stekom.ac.id/index.php/elkom/artic...

Abstract

Public transportation is one of the important modes of transportation and is the backbone of transportation in Indonesia. The development of public transportation is also supported by the government, this government support is evident in the national policy, namely the National Medium Term Development Plan (RPJMN). Although public transportation is an effective mode of transportation, it also has obstacles in its development, namely how to meet customer desires in choosing a mode of transportation. There are several variables that are the focus of this research, namely age, gender, income, cost, speed, comfort, safety, efficiency and flexibility. The search for influential variables will use the K-Means and DBSCAN clustering algorithms, these two algorithms are also compared to their performance to find a better algorithm. The results of the Silhouette Coefficient show that DBSCAN has a better performance with a value of 0.99 than K-Means with a value of 0.86. The variables that affect the interest in using public transportation are the most important ones related to cost, speed, comfort, safety, efficiency and flexibility.

Item Type: Article
Uncontrolled Keywords: K-Means, DBSCAN, Clustering, Public Transportation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Information Technology
Faculty of Information Technology > Computer Engineering Department
Depositing User: P3M IKADO
Date Deposited: 03 Dec 2021 07:03
Last Modified: 21 Apr 2022 05:01
URI: http://repository.ikado.ac.id/id/eprint/170

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