Implementation of K-Medoids Clustering Method for Indihome Service Package Market Segmentation

Abstract

IndiHome (Indonesia Digital Home) is a leading digital fibre optic service product consisting of fibre optic internet services, landline telephones, and interactive TV services. Although the coverage of Indihome products is extensive in the city of Medan, in marketing, Indihome products have not reached the planned target. Based on data from Indihome service package users that have been received, Indihome product users only numbered 6419 customers in all STOs in Medan City. At the same time, the target was planned by PT. Telkom Access Medan, namely Marketing Indihome products, must reach 5,000 customers per month in all STOs in Medan City. Indihome product marketing is an obstacle for PT. Telkom Access Medan, because the Indihome product is a new product, the people of Medan City do not fully know what Indihome is and what facilities they get from using the Indihome service package. Therefore PT. Telkom Access Medan needs to make a plan to make a marketing strategy. The first step that needs to be done is to segment the market for the Indihome service package. This study aimed to determine the application of Data Mining using the K-Medoids Clustering method in the Indihome service package market segmentation at PT. Telkom Access Medan. With this research, it is hoped that it can provide a reference for the results of the decision so that it can help related parties to make it easier to classify the market segmentation of the Indihome service package at PT. Telkom Access Medan. Because the value of S > 0, then the calculation is stopped and ends in the 3rd iteration. Indihome service package data processing uses the k-medoids clustering method in the form of potential, potential, and not potential STO (Sentral Telephone Automated) cluster members.

Estimasi Penjualan Ice Cream Walls Menggunakan Metode Regresi Linear Berganda

“…Data Mining juga dapat mengestimasi jumlah [4]. Tujuan utama dari data mining adalah untuk memperoleh pengetahuan yang masih tersembunyi dalam bongkahan data [5].…”

“…-25722 = -185b1 -6b2 + 674b3 [5] -21577195583,65 = -6b1 -40,42b2 + 1853,40b3 [6] 93302664 = 674b1 + 1853,40b2 -224847b3 [7] Kemudian setelah melakukan proses eliminasi persamaan 5,6,7, maka diproleh nilai b0,b1,b2,b3 sebagai berikut. b0 = -1498008973 b1 = -1772605 b2 = 858054295 b3 = 7067157…”