Main Article Content
Abstract
The purpose of this research is to determine the readiness of schools in implementing the Smart School system through various stages. One of the concepts of a Smart City involves integrating information and communication technology into the learning process at every school to create Smart Schools. However, not all schools are ready to implement this technology because it requires suitable technology to support the quality of teaching and learning. Another issue is the absence of information systems that can facilitate administrative tasks and the teaching and learning process. The use of the K-Means method is beneficial for clustering schools based on their stages, characteristics, and readiness to implement the Smart School system. This helps identify schools with the highest level of readiness. This research demonstrates that the use of K-Means can identify school readiness based on the established stages related to the Smart School system. It also can pique students' interest in developing and boosting the school's reputation as the best technology-based school.
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Copyright (c) 2024 Aida Nisa, M. Khairul Anam, Helda Yenni, Parlindungan Kudadiri, Gunadi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
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References
M. K. Anam, A. Yunianta, H. J. Alyamani, Erlin, A. Zamsuri, and M. B. Firdaus, “Analysis and Identification of Non-Impact Factors on Smart City Readiness Using Technology Acceptance Analysis: A Case Study in Kampar District, Indonesia,” Journal of Applied Engineering and Technological Science, vol. 5, no. 1, pp. 1–17, 2023, doi: 10.37385/jaets.v5i1.2401.
N. Chotpittayanon, J. Angsukanjanakul, V. Jintalikhitdee, and N. Phasuk, “The Success Factors For the Sustainable Smart City Development in Thailand,” in Proceedings on Engineering Sciences, Faculty of Engineering, University of Kragujevac, 2024, pp. 109–118. doi: 10.24874/PES06.01.013.
Isabella and E. Agustian, “Implementing Digital Literacy Policies and the Challenges of Towards Smart City in Palembang City,” Journal of Governance and Local Politics (JGLP), vol. 5, no. 2, pp. 122–132, 2023, doi: 10.47650/jglp.v5i2.936.
A. Hasibuan and oris krianto Sulaiman, “Smart City , Konsep Kota Cerdas Sebagai Alternatif Penyelesaian Masalah Perkotaan Kabupaten / Kota,” Buletinutama Teknik, vol. 14, no. 2, pp. 127–135, 2019.
A. I. Khan and S. Al-Habsi, “Machine Learning in Computer Vision,” Procedia Comput Sci, vol. 167, no. 2019, pp. 1444–1451, 2020, doi: 10.1016/j.procs.2020.03.355.
A. U. Zailani, A. Perdananto, Nurjaya, and Sholihin, “Pengenalan Sejak Dini Siswa SMP Tentang Machine Learning Untuk Klasifikasi Gambar Dalam Menghadapi Revolusi 4.0,” KOMMAS: Jurnal Pengabdian Kepada Masyarakat, vol. 1, no. 1, pp. 7–15, 2020.
Forum New Education, “Smart Education in Smart Cities and Smart Regions,” Center for innovative education, 2017.
Z. T. Zhu, M. H. Yu, and P. Riezebos, “A research framework of smart education,” Smart Learning Environments, vol. 3, no. 1, 2016, doi: 10.1186/s40561-016-0026-2.
M. Sampebua and S. Mangiwa, “The Design Smart School Application to Increase Education in Junior High School,” International Journal of Computer …, vol. 15, no. 10, pp. 154–165, 2017.
J. R. Batmetan, M. Nur, O. S. Turang, M. M. Sumampouw, and G. M. Lahengking, “IT Infrastructure Library Framework Approach to the Measurement of e-Government Maturity,” Lahengking International Journal of Information Technology and Education (IJITE), vol. 1, no. 2, pp. 119–128, 2022, doi: 10.62711/ijite.v1i2.51.
Dr. M. R. Taghva, Dr. M. T. T. Fard, Dr. S. M. Taheri, and S. Omidinia, “Success Factors for Smart Schools Emphasizing the Role of Information Technology: A Case Study,” International Journal of Engineering and Technology, vol. 11, no. 4, pp. 731–739, 2019, doi: 10.21817/ijet/2019/v11i4/191104065.
Lukman and A. Z. Ibad, “Pemilihan Metode Dan Media Pembelajaran Dalam Blended Learning,” Jurnal Ilmiah Promis, vol. 1, no. 2, pp. 86–94, 2020.
Yudi Agusta, “K-Means – Penerapan, Permasalahan dan Metode Terkait,” Jurnal Sistem dan Informatika, vol. 3, no. Februari, pp. 47–60, 2007.
K. Fatmawati and A. P. Windarto, “Data Mining: Penerapan Rapidminer Dengan K-Means Cluster Pada Daerah Terjangkit Demam Berdarah Dengue (Dbd) Berdasarkan Provinsi,” Computer Engineering, Science and System Journal, vol. 3, no. 2, p. 173, 2018, doi: 10.24114/cess.v3i2.9661.
M. K. Anam, I. Y. Pasa, K. D. kusuma Wardhani, L. Efrizoni, and M. B. Firdaus, “K-Means Clustering to Identity Twitter Build Operate Transfer (BOT) on Influential Accounts,” ComTech: Computer, Mathematics and Engineering Applications, vol. 14, no. 2, pp. 143–154, 2023, doi: 10.21512/comtech.v14i2.10620.
N. T. Hartanti, “Metode Elbow dan K-Means Guna Mengukur Kesiapan Siswa SMK Dalam Ujian Nasional,” Jurnal Nasional Teknologi dan Sistem Informasi, vol. 6, no. 2, pp. 82–89, 2020, doi: 10.25077/teknosi.v6i2.2020.82-89.
M. L. Sibuea and A. Safta, “Pemetaan Siswa Berprestasi Menggunakan Metode K-Means Clustring,” Jurteksi, vol. 4, no. 1, pp. 85–92, 2017, doi: 10.33330/jurteksi.v4i1.28.
M. W. Putri, I. M. Nur, and R. Wasono, “Implementasi Spectral Clustering Algorithm untuk Penelompokan Sasaran Vaksinasi Covid-19 di Indonesia,” Jurnal Statistika, vol. 10, no. 1, pp. 26–31, 2022, doi: 10.26714/jsunimus.10.1.2022.26-31.
D. Radixavendra Quinthara, A. Charis Fauzan, and M. Maariful Huda, “Penerapan Algoritma K-Modes Menggunakan Validasi Davies Bouldin Index Untuk Klasterisasi Karakter Pada Game Wild Rift,” Journal of System and Computer Engineering (JSCE), vol. 4, no. 2, pp. 123–135, 2023, doi: 10.61628/jsce.v4i2.802.
M. N. Zhafar, K. Usman, and F. Akhyar, “Penerapan Metode Clustering Dengan Algoritma K-Means Untuk Analisa Persebaran Varian Covid-19 (Studi Kasus Kelurahan Antapani Kidul),” in e-Proceeding of Engineering, 2023, pp. 4257–4264.
M. F. J. Muttaqin, “Cluster Analysis Using K-Means Method to Classify Sumatera Regency and City Based on Human Development Index Indicator,” in Seminar Nasional Official Statistics, 2022, pp. 967–976.
C. Oktarina, K. Anwar Notodiputro, and Indahwati, “Comparison of K-Means Clustering Method and K-Medoids on Twitter Data,” Indonesian Journal of Statistics and Its Applications, vol. 4, no. 1, pp. 189–202, 2020, doi: 10.29244/ijsa.v4i1.599.
M. R. Taghva, M. T. T. Fard, S. M. Taheri, and S. Omidinia, “Success Factors for Smart Schools Emphasizing the Role of Information Technology: A Case Study,” International Journal of Engineering and Technology, vol. 11, no. 4, pp. 731–739, Aug. 2019, doi: 10.21817/ijet/2019/v11i4/191104065.
N. A. Razak, H. A. Jalil, S. E. Krauss, and N. A. Ahmad, “Studies in Educational Evaluation Successful implementation of information and communication technology integration in Malaysian public schools : An activity systems analysis approach,” Studies in Educational Evaluation, vol. 58, no. April, pp. 17–29, 2018, doi: 10.1016/j.stueduc.2018.05.003.
M. N. N. Lee and S. S. Thah, “Building and Sustaining National ICT/Education Agencies,” Building and Sustaining National ICT/Education Agencies, 2016, doi: 10.1596/26265.
R. Snehkunj, K. Vachiyatwala, and C. Author, “Data Analysis Using Pandas Library of Python,” 2022.
S. S. Nagari and L. Inayati, “Implementation of clustering using k-means method to Determine nutritional status,” Jurnal Biometrika dan Kependudukan, vol. 9, no. 1, p. 62, Jun. 2020, doi: 10.20473/jbk.v9i1.2020.62-68.