Penerapan Metode K – Means Clustering untuk Menentukan Kepuasan Mahasiswa terhadap Fasilitas Sarana dan Prasarana Kampus di STMIK Kaputama Binjai

Authors

  • Dicha Mutia Dhani Sekolah Tinggi Manajemen Informatika dan Komputer Kaputama
  • Relita Buaton Sekolah Tinggi Manajemen Informatika dan Komputer Kaputama
  • I Gusti Prahmana Sekolah Tinggi Manajemen Informatika dan Komputer Kaputama

DOI:

https://doi.org/10.62951/bridge.v2i3.170

Keywords:

Student Satisfaction, Campus Facilities, K-Means Clustering, STMIK Kaputama

Abstract

Technological advancements in the era of globalization demand improvements in the quality of academic services and educational facilities in institutions. STMIK Kaputama is committed to creating a conducive academic environment by providing optimal facilities. This study aims to determine student satisfaction with campus facilities using the K-Means Clustering method. Data were obtained from recapitulated survey reports and questionnaires filled out by students in 2024. The K-Means Clustering method was chosen for its ability to group students based on their similar preferences for campus facilities. The results show that, in general, students are fairly satisfied, though their preferences for specific facilities vary. These findings can be used to make recommendations for the improvement and development of campus facilities, help STMIK Kaputama allocate resources more efficiently, and plan strategies to enhance the quality of facilities to meet student expectations.

Downloads

Download data is not yet available.

References

Ajin, V. W., & Kumar, L. D. (2016, Mei). Data besar dan algoritma pengelompokan. In Proceedings of the 2016 International Conference on Advances in Research on Integrated Navigation Systems (RAINS) (pp. 1-5). IEEE.

Andriani, D. P., Setyanto, N. W., & Kusuma, L. T. (2017). Desain dan analisis eksperimen untuk rekayasa kualitas. Malang: UB Press.

Arikunto, S. (2002). Prosedur penelitian: Suatu pendekatan praktik. Jakarta: Rineka Cipta.

Ary, H. G. (1996). Administrasi sekolah (administrasi pendidikan makro). Jakarta: Rineka Cipta.

Bararah, I. (2020). Pengelolaan sarana dan prasarana pendidikan dalam meningkatkan kualitas pembelajaran. Jurnal MUDARRISUNA: Media Kajian Pendidikan Agama Islam, 10(2), 351-370.

Bhatia, P. (2019). Data mining and data warehousing (1st ed.). India: Cambridge.

Chapman, P., et al. (2000). CRISP-DM: Step-by-step data mining guide (v.10). SPSS Inc.

Fakhri, D. A., Defit, S., & Sumijan. (2021). Optimalisasi pelayanan perpustakaan terhadap minat baca menggunakan metode K-means clustering. Jurnal Informasi dan Teknologi, 3(3), 160-166.

Gupta, G. K. (2014). Pengantar data mining dengan studi kasus. Prajurit Pembelajaran PHI Ltd.

Hossain, M. Z., Akhtar, M. N., Ahmad, R. B., & Rahman, M. (2019). A dynamic K-means clustering for data mining. Indonesian Journal of Electrical Engineering and Computer Science, 13(2), 521-526.

Jain, M., & Verma, C. (2014). Mengadaptasi K-means untuk clustering di big data. Jurnal Internasional Aplikasi Komputer, 101(1), 19-24.

Oktarian, S., Defit, S., & Padang, P. I. Y. (2020). Klasterisasi penentuan minat siswa dalam pemilihan sekolah menggunakan metode algoritma K-means clustering. Jurnal Informasi dan Teknologi, 2(3), 68-75.

Pawening, R. E. (2021). Algoritma K-means untuk mengukur kepuasan mahasiswa menggunakan e-learning. Journal of Technology and Informatics (JoTI), 3(1), 27-33.

Pramudiono, I. (2007). Algoritma Apriori. Online. Retrieved from http://datamining.japati.net/cgi-bin/indodm.cgi

Purwadi, P., Ramadhan, P. S., & Safitri, N. (2019). Penerapan data mining untuk mengestimasi laju pertumbuhan penduduk menggunakan metode regresi linier berganda pada BPS Deli Serdang. Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika Dan Komputer), 18(1), 55-61.

Rohiat. (2010). Manajemen sekolah. Bandung: Refika Aditama.

Rohman, A., & Rochcham, M. (2020). Implementasi algoritma K-means untuk clustering kepuasan mahasiswa terhadap pelayanan akademik. Neo Teknika, 6(2), 42-45.

Sunardi, S., Fadlil, A., & Kusuma, N. M. P. (2022). Implementasi data mining dengan algoritma Naïve Bayes untuk profiling korban penipuan online di Indonesia. Jurnal Media Informatika Budidarma, 6(3), 1562-1572.

Published

2024-08-06

How to Cite

Dicha Mutia Dhani, Relita Buaton, & I Gusti Prahmana. (2024). Penerapan Metode K – Means Clustering untuk Menentukan Kepuasan Mahasiswa terhadap Fasilitas Sarana dan Prasarana Kampus di STMIK Kaputama Binjai. Bridge : Jurnal Publikasi Sistem Informasi Dan Telekomunikasi, 2(3), 229–243. https://doi.org/10.62951/bridge.v2i3.170

Similar Articles

1 2 3 4 5 > >> 

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)