Cluster analysis for customer segmentation based on the reasons for choosing Indihome products using the k-means method at PT. Telkom Access Witel SBU

Abstract

The Internet is a global communication network that interconnects computer

networks, facilitating the sharing of information and communication worldwide.

Therefore, Bambang Gunawan, the Director of Information and Political

Communication, Legal, and Security at the Ministry of Communication and

Information Technology, has stated that the number of internet users in Indonesia

has reached 202 million people. Consequently, this positions Indonesia as the

fourth-largest internet user in the world in the year 2020.

PT Telkom Indonesia is a State-Owned Enterprise (SOE) operating in the field of

information

technology

and

communication

(ITC)

services

and

telecommunication networks in Indonesia. IndiHome is one of the flagship

programs and projects of Telkom, Indonesia Digital Network 2015. IndiHome is a

bundled triple-play service product from Telkom, comprising high-speed

communication and data services, including home phone (voice), internet (fiber-

optic/high-speed internet), and interactive TV services (TV Cable, IPTV, &

Netflix). IndiHome services are exclusively available to homes with fiber optic

cable networks provided by Telkom FTTH (Fibre To The Home) and areas that

still rely on optical cables.

The purpose of this research is to categorize IndiHome customers based on their

reasons for using the service at PT Telkom Indonesia. The methodology employed

in this study is quantitative analysis, involving data collection through survey

techniques using Google Forms. The sample size includes 30 respondents who are

IndiHome users within the specified region. The K-Means method is applied

using SPSS for the purpose of data analysis.

Based on the research findings and analysis conducted, it can be concluded that

there are three consumer groups at PT Telkom Indonesia. Within these three

consumer groups, a total of 7 (seven) attributes or variables related to the reasons

for using IndiHome are identified. Among these variables, 7 (seven) possess a

Significance value of <0.05, and thus, they can be considered differentiating

variables between clusters. Specifically, there is one respondent in cluster 1, 18

respondents in cluster 2, and 11 respondents in cluster 3.

This clustering result can subsequently serve as a recommendation for marketing

managers at PT Telkom Indonesia to enhance their marketing system in order to

better understand the reasons behind customer usage of IndiHome.