CD Skripsi

Implementasi Klasterisasi Tingkat Kehadiran Dosen Fmipa Universitas Riau Menggunakan Algoritma K-Means

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This research analyzes the attendance levels of lecturers at FMIPA Universitas Riau using the K-Means algorithm. Lecturer attendance data for the 2021/2022 and 2022/2023 academic years, involving 124 lecturers, were obtained from the FMIPA UNRI Dean’s Office. In this study, the K-Means algorithm was employed to cluster lecturer attendance data, with the optimal number of clusters determined using the elbow method based on SSE calculations. The SSE calculation identified three optimal clusters with an SSE value of 9.5605. The clustering results revealed three groups: Cluster 1 includes 15 lecturers with an average total attendance of 291 days and an average total absence of 164 days; Cluster 2 consists of 14 lecturers with an average total attendance of 189 days and an average total absence of 267 days; and Cluster 3 comprises 95 lecturers with an average total attendance of 428 days and an average total absence of 28 days. The Silhouette Index average value obtained is 0.7801, indicating that the clustering results are quite good, as it falls within the range of 0 to 1. This study confirms that the K-Means algorithm can be effectively implemented to analyze and cluster lecturer attendance levels at FMIPA Universitas Riau.

Keywords : K-Means, clustering, Elbow Method, Silhouette Index, Euclidean Distance

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2003134719

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2025

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2003134719

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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