Jurnal Pengembangan Rekayasa dan Teknologi
Vol 16, No 2 (2020): Desember 2020

Implementasi Metode Fuzzy K-Means untuk Cluster Judul Skripsi Mahasiswa

Ahmad Rifa'i ([SINTA ID : 6677633] Universitas Semarang)
Galet Guntoro Setiadji (Universitas Semarang)

Article Info

Publish Date
15 Dec 2020

Abstract

Clusters are a way of classifying data which can later be used as information and processed using data mining methods with certain algorithms. From here the author wants to try to use data in the form of thesis titles or final assignments from students, which later can be grouped from these results. So that the existing data can be processed using a data mining method, namely Fuzzy K-Means (FKM).The data used in this study uses thesis data of students majoring in information technology. As a comparison, the data is also processed using K-Means, from the K-Means calculation, the average cluster is 1.014 and the DBI validity is 0.725. Meanwhile, for the calculation of Fuzzy K-Means, the cluster average is 0.069 and the DBI validity is 0.304

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Journal Info
Jurnal Pengembangan Rekayasa dan Teknologi
Website

Abbrev

jprt

Publisher

Universitas Semarang

Subject

Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Mechanical Engineering Transportation

Description

Jurnal Pengembangan Rekayasa dan Teknologi ( JPRT ) is a scholarly refereed research journal that aims to promote the theory and practice of technology, innovation, and engineering management. The journal links engineering, science, and management disciplines. It addresses the issues involved in the ...