K-Means Clustering Analysis for Mapping Alumni Career Success Profiles to Evaluate Graduate Quality at SMKN 1 Kisaran
DOI:
https://doi.org/10.35870/ijmsit.v6i2.8631Keywords:
K-Means Clustering Method, Data Mining, Career Profile Mapping, Alumni Career Success, Graduate Quality Evaluation, SMKN 1 KisaranAbstract
The development of information and communication technology has encouraged the widespread use of data in various fields, including education. This study aims to apply the K-Means Clustering method to group alumni career data of SMKN 1 Kisaran based on predetermined indicators of career success. The research uses a quantitative approach with a data mining method, applying the K-Means Clustering algorithm as the main technique in the data analysis process. The findings indicate that the alumni career data were successfully grouped by converting categorical data into numerical weights for computational processing. The results show that the alumni data are divided into three main clusters. Cluster 1 represents alumni with a high level of career success, characterized by a short waiting period for employment and suitability between their field of work and competencies. Cluster 2 describes alumni with a moderate level of career success, indicated by a longer waiting period for employment or a mismatch between their field of work and competencies. Cluster 3 represents alumni with a low level of career success, dominated by alumni who have not yet obtained employment.
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References
Arifah, S., Sweden, E. R., & Septian, M. R. D. (2023). Analisis Perbandingan Algoritma Clustering Dalam Melakukan Segmentasi Warna Pada Citra Jajan Tradisional. Sebatik, 27(1), 70-76. https://doi.org/10.46984/sebatik.v27i1.2273
Badan Pengembangan dan Pembinaan Bahasa. (2026). Alumni. In Kamus Besar Bahasa Indonesia (KBBI). https://kbbi.web.id/alumni
Devie, Y. K., & Anamisa, R. (2020). Sistem Informasi & Implementasi Untuk Pendukung Keputusan: Studi Kasus: Sitem Rekomendasi. Media Nusa Creative (MNC Publishing).
Fatkhudin, A., Khambali, A., Artanto, F. A., & Zade, N. A. P. (2023). Implementasi Algoritma Clustering K-Means Dalam Pengelompokan Mahasiswa. Jurnal Minfo Polgan, 12(1), 777-783. https://doi.org/10.33395/jmp.v12i1.12494
FIKTI. (2023). K-Means clustering algorithm: Definition, function, and how it works. https://fikti.umsu.ac.id/algoritma-k-meansclustering-pengertian-fungsi-dan-cara-kerja/
Han, J., Kamber, M., & Pei, J. (2022). Data mining: Concepts and techniques (4th ed.). Morgan Kaufmann.
Harini, S., & Kusumawati, R. (2023). Evaluasi Clustering K-Means Dan K-Medoid Pada Persebaran Covid-19 di Indonesia Dengan Metode Davies-Bouldin Index (DBI). Jurnal Mnemonic, 6(2), 117-128. https://doi.org/10.36040/mnemonic.v6i2.6642
Kementerian Pendidikan dan Kebudayaan Republik Indonesia. (2021). Tracer study sebagai instrumen evaluasi mutu pendidikan vokasi. Jakarta: Kementerian Pendidikan dan Kebudayaan Republik Indonesia.
Novitasari, N., Nuris, N. D., & Herdiana, R. (2023). Penerapan Algoritma K-Means untuk Clustering Data Jumlah Penduduk Miskin Berdasarkan Kota/Kabupaten di Jawabarat menggunakan Rapidminer. Jurnal Informatika Terpadu, 9(1), 68–73. https://doi.org/10.54914/jit.v9i1.660
Prasetyo, E. (2020). Data mining: Concepts and applications using MATLAB. Andi Offset.
Pratama, Y., Hendrawan, H., Rasywir, E., Carenina, B. T., & Anggraini, D. R. (2022). Penerapan Algoritma K-Means clustering Untuk Mengelompokkan Provinsi Berdasarkan Banyaknya Desa/Kelurahan Dengan Upaya Antisipasi/Mitigasi Bencana Alam. Building of Informatics, Technology and Science (BITS), 4(3), 1232−1240. https://doi.org/10.47065/bits.v4i3.2549
Pratiwi, Y., & Mulyawan, M. (2023). Implementasi Algoritma K-Means untuk Menentukan Angka Harapan Hidup berdasarkan Tingkat Provinsi. Blend Sains Jurnal Teknik, 1(4), 284–294. https://doi.org/10.56211/blendsains.v1i4.233
Quipper Campus. (2026). Alumni: Definition and meaning. https://campus.quipper.com/kampuspedia/alumni
Ramadhan, R. F., Wijoyo, S. H., & Saputra, M. C. (2023). Penerapan Metode K-Means Clustering pada Ulasan Perumahan PT XYZ di Google Maps untuk Formulasi Strategi Bisnis dengan Analisis SWOT. (2023). Jurnal Pengembangan Teknologi Dan Ilmu Komputer, 7(6), 2879-2888. https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/12912
Rudini, A. (2024). Sistem informasi manajemen. CV Azka Pustaka.
Soufitri, F. (2023). Konsep sistem informasi. PT Inovasi Pratama Internasional.
Wakhidah, N. (2020). Clustering using the K-Means algorithm.
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