Utilizing Clustering Methods for Categorizing Delivery Requirements Based on Analysis of E-Commerce Product Data

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Published: Dec 30, 2023
DOI: https://doi.org/10.35870/ijsecs.v3i3.1969
Keywords:
Data Mining K-Means Clustering E-Commerce Product Analysis

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Jumat Azzam Sugiarto
Universitas Pelita Bangsa
Suprapto
Universitas Pelita Bangsa
Muhamad Fatchan
Universitas Pelita Bangsa

Abstract

This study presents the implementation of the K-Means algorithm model, revealing novel insights into risk categorization in the delivery process. Two distinct clusters were identified: Cluster 1 (C0) indicating high risk, comprising 53 data points out of a dataset of 360, and Cluster 2 (C1) indicating low risk, encompassing 307 data points from the same dataset. Analysis conducted using RapidMiner Studio corroborated these findings, further delineating the cluster membership: C0 with 53 data points and C1 with 307 data points. Each cluster was characterized by optimal centroid values, recorded at 131.717 & 385.075 for C0, and 119.932 & 111.414 for C1. The model's effectiveness was assessed using the Davies-Bouldin Index, yielding a value of 0.626.

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How to Cite
Sugiarto, J. A., Suprapto, & Fatchan, M. (2023). Utilizing Clustering Methods for Categorizing Delivery Requirements Based on Analysis of E-Commerce Product Data. International Journal Software Engineering and Computer Science (IJSECS), 3(3), 545–552. https://doi.org/10.35870/ijsecs.v3i3.1969
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Vol. 3 No. 3 (2023): DECEMBER 2023
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Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Author Biographies

Jumat Azzam Sugiarto, Universitas Pelita Bangsa

Informatics Engineering Study Program, Faculty of Engineering, Universitas Pelita Bangsa, Karawang Regency, West Java Province, Indonesia

Suprapto, Universitas Pelita Bangsa

Informatics Study Program, Faculty of Engineering, Universitas Pelita Bangsa, Karawang Regency, West Java Province, Indonesia

Muhamad Fatchan, Universitas Pelita Bangsa

Informatics Study Program, Faculty of Engineering, Universitas Pelita Bangsa, Karawang Regency, West Java Province, Indonesia

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