Pemanfaatan K Means Clustering dalam Pengelompokan Judul Skripsi

Authors

  • Nisar Nisar Institut Informatika dan Bisnis Darmajaya
  • Wasilah IIB Darmajaya Bandar Lampung
  • Haris Kusumajaya IIB Darmajaya Bandar Lampung

DOI:

https://doi.org/10.5281./4444/5.jupiter.2022.04

Abstract

Thesis is a term used in Indonesia to describe scientific writing. Thesis is in the form of a written explanation of the results of undergraduate research that discusses phenomena in certain fields of science using applicable rules. In this case study, data mining analysis was carried out using the K Means clustering method. The criteria used to classify thesis titles with K-Means are rpm, name, title, supervisor. The increasing number of students and variations in thesis titles cause difficulties in grouping thesis data. This study aims to classify the thesis data of students of the informatics engineering study program IIB Darmajaya. Grouping is done using an algorithm. K-Means Clustering. The process of calculating the K-Means clustering algorithm uses a simple application built using the PHP programming language and MySQL database.

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Published

2022-04-15

How to Cite

Nisar, N., Wasilah, & Haris Kusumajaya. (2022). Pemanfaatan K Means Clustering dalam Pengelompokan Judul Skripsi. JUPITER: Jurnal Penelitian Ilmu Dan Teknologi Komputer, 14(1), 19–26. https://doi.org/10.5281./4444/5.jupiter.2022.04

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Articles