Decision Support System for Indibiz Package Selection Using K-Means Clustering and Analytic Hierarchy Process

Karina  Martika; Eneng Tita Tosida; Yusma Yanti

doi:10.47194/ijgor.v6i4.434

Authors

Karina Martika
karina.martika@gmail.com
Eneng Tita Tosida
Yusma Yanti

Keywords:

Analytical Hierarchy Process, Decision Support System, Indibiz, K-Means Clustering, Web-Based System

Abstract

The rapid development of digital business in Indonesia has encouraged telecommunication providers to improve their services, particularly for small and medium-sized enterprises (SMEs). PT. Telkom Indonesia, through its Indibiz program, offers a wide variety of internet packages to support business operations. However, the diversity of available packages often leads to decision-making difficulties for both customers and internal stakeholders when determining the most suitable service based on customer needs, business scale, and financial capability. This study proposes a web-based Decision Support System (DSS) for Indibiz package selection by combining K-Means Clustering and the Analytic Hierarchy Process (AHP). K-Means is used to segment customers based on sales and usage behavior, while AHP prioritizes criteria such as speed, price, and call quota to produce recommendations. A dataset containing 6,192 Indibiz sales records from July to November 2023 was analyzed. The hybrid model was then implemented into a web-based application that enables decision-makers to visualize clustering results and determine package recommendations interactively. The experimental results demonstrate that the combination of K-Means and AHP produces more objective and consistent recommendations compared to manual selection. The DSS can help both customers and PT. Telkom Indonesia improve decision efficiency and reduce subjective bias in selecting internet packages.

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