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.
Penjurusan merupakan hal yang wajib dan tidak dapat terelakkan dalam dunia pendidikan termasuk pada saat sekolah menengah atas (SMA).Pada SMA Negeri 2 Kabanjahe pemilihan jurusan dilakukan pada saat berada di kelas X (sepuluh). Hak dalam pemilihan jurusan itu sendiri diberikan langsung kepada siswa. Hal ini membuat banyak siswa mengalami kebingungan dalam menentukan jurusan yang akan dipilih karena adanya beberapa faktor yang mempengaruhi, diantaranya kurangnya pemahanan siswa terhadap jurusan tersebut, tuntutan orangtua bahkan sekedar mengikuti teman. Nilai akademis dapat diajukan sebagai acuan untuk mengetahui jurusan apa yang tepat bagi siswa berdasarkan nilai akademis. Hal ini membuat peneliti melakukan penelitian pada SMA Negeri 2 Kabanjahe terkait bagaimana memberikan rekomendasi penjurusan. Salah satu tehnik dalam data mining yang dapat dilakukan untuk pengelompokan yaitu clustering. Hasil penelitian ini berupa sistem yang dapat memberikan rekomendasi jurusan pada siswa baru menggunakan K-Means.
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