KLASTERISASI TUGAS AKHIR MAHASISWA FAKULTAS ILMU KOMPUTER UNIVERSITAS SRIWIJAYA MENGGUNAKAN METODE K-MEANS

MAREVIN, YOLANDA and Kurniati, Rizki and Primanita, Anggina (2024) KLASTERISASI TUGAS AKHIR MAHASISWA FAKULTAS ILMU KOMPUTER UNIVERSITAS SRIWIJAYA MENGGUNAKAN METODE K-MEANS. Undergraduate thesis, Sriwijaya University.

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Abstract

The final project is an important stage in a student's study journey, which often requires exploration and in-depth understanding in a discipline. This research aims to cluster final project topics based on the attributes of student final project titles, especially at the Faculty of Computer Science, Sriwijaya University, using the K-means clustering method. The data analyzed comes from the faculty library in the time span of 2016 to 2023. The data was processed and weighted using TF-IDF method, then reduced using UMAP technique. Topic analysis was also conducted by utilizing the wordcloud generated from the clustering. The clustering results show that the optimal cluster is located in the 7th cluster, with a silhouette score of 0.3515.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Data Mining, Klasterisasi, K-Means Clustering, TF-IDF, Tugas Akhir, UMAP
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75.5.A142 Computer science. Information society. Information technology. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76 Computer software Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.76.I58.A3115 Computer science. Computers. Intelligent agents (Computer software) Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.B45 Big data. Machine learning. Quantitative research. Metaheuristics. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Yolanda Marevin
Date Deposited:	20 May 2024 08:27
Last Modified:	20 May 2024 08:27
URI:	http://repository.unsri.ac.id/id/eprint/144592

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