CLASTERIZATION OF DEVELOPER ACTIVITY DATA USING K-MEDOIDS METHOD (Case Study: PT. Kedata Digital Indonesia)

DAWAN, MARTINUS (2022) CLASTERIZATION OF DEVELOPER ACTIVITY DATA USING K-MEDOIDS METHOD (Case Study: PT. Kedata Digital Indonesia). Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

ABSTRACT Every organization or company in achieving a success of course there are several supporting factors and one of them is the performance of a good and quality developer. The differences can be in the aspects of discipline, independence, hard work, communication skills, good time management and collaboration between teams. With these differences, it is necessary to monitor so that problems do not occur which can later hinder the running of the company's business processes and the products produced. The purpose of this research is to implement the K-Medoids algorithm to determine the level of inhibition of a developer. The K-Medoids method is a partitional clustering method with the aim of finding the number of cluster sets among data objects that most closely resemble an object in the data set. So you can see the size of the data that can affect the performance of the developer. From the results of the analysis, it can be concluded that: the value of developer activity per year, namely in 2021 in good condition, an increase score of 1.69 compared to 2020 has a lower value of 1.05. It is necessary to know what causes developer performance to decline. Based on the analysis of K-Medoids Clustering developers can be grouped into 4 clusters namely strong structure, good structure, weak structure, and bad structure. The developer performance is not optimal, there is cluster 2 so it is necessary to know the cause of the declining developer performance. Keywords: Grouping, K-Medoids, Trello.

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 11 Apr 2022 01:33
Last Modified: 11 Apr 2022 01:33
URI: http://eprints.uty.ac.id/id/eprint/9650

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