Designing Applications For Damage Reporting Of Public Facilities Using K-Means Clustering Algorithm
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Published:
Aug 31, 2022
Keywords:
public facilities, data mining, k-means clustering
Section
Computer Science
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Abstract
Public facilities are facilities provided for public purposes such as roads, street lighting, bus stops, sidewalks, and pedestrian bridges. The facilities provided are facilities that provide convenience for the community so that they must be maintained properly. Data mining is a process of dredging or collecting important information from large data. The data mining process often uses statistical, mathematical methods, to utilize artificial intelligence technology. The application designed uses 50 datasets which, after normalization, the number of data becomes 350 data, and after preprocessing the data used in the study is 81 data, with 4 attributes and 3 clusters. The results of the data processing resulted in the first data clustering based on the facility attributes produced as many as 29 data, the second data clustering based on the year attribute produced was 12 data, the third data clustering based on the attribute the resulting amount was 40 data
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How to Cite
Saljuni, R., Muhammad Sholahuddin, Fanema Putra Hartaret Harefa, Thines Raman, Juliansyah Putra Tanjung and N P Dharshinni (2022) “Designing Applications For Damage Reporting Of Public Facilities Using K-Means Clustering Algorithm”, Jurnal Mantik, 6(2), pp. 2610-1615. doi: 10.35335/mantik.v6i2.2900.
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[2] A. Huda, “Perkembangan Teknologi Informasi Dan Komunikasi (Tik) Terhadap Kualitas Pembelajaran Di Sekolah Dasar,” J. Pendidik. dan Konseling, vol. 2, no. 1, pp. 121–125, 2020, doi: 10.31004/jpdk.v1i2.622.
[3] Hartanto, “Text Mining Dan Sentimen Analisis Twitter Pada Gerakan Lgbt,” Intuisi J. Psikol. Ilm., vol. 9, no. 1, pp. 18–25, 2017, doi: 10.15294/intuisi.v9i1.9561.
[4] G. Gustientiedina, M. H. Adiya, and Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan,” J. Nas. Teknol. dan Sist. Inf., vol. 5, no. 1, pp. 17–24, 2019, doi: 10.25077/teknosi.v5i1.2019.17-24.
[5] Rikhza Hamdani, U. Izyah Arfianti, and M. Maulana Asegaf, “Implementasi Metode K-Means Clustering Dalam Pengelompokan Penyebaran Covid-19 Di Surabaya,” pp. 1–14, 2020.
[6] Aditya, I. Jovian, and B. N. Sari, “Implementasi K-Means Clustering Ujian Nasional Sekolah Menengah Pertama di Indonesia Tahun 2018/2019,” J. Media Inform. Budidarma, vol. 4, no. 1, p. 51, 2020, doi: 10.30865/mib.v4i1.1784.
[7] Rohmah, F. Sembiring, and ..., “Implementasi Algoritma K-Means Clustering Analysis Untuk Menentukan Hambatan Pembelajaran Daring (Studi Kasus: Smk Yaspim …,” … Sist. Inf. dan …, pp. 290–298, 2021, [Online]. Available:
https://sismatik.nusaputra.ac.id/index.php/sismatik/article/view/32
[8] H. Haviluddin, S. J. Patandianan, G. M. Putra, N. Puspitasari, and H. S. Pakpahan, “Implementasi Metode K-Means Untuk Pengelompokkan Rekomendasi Tugas Akhir,” Inform. Mulawarman J. Ilm. Ilmu Komput., vol. 16, no. 1, p. 13, 2021, doi: 10.30872/jim.v16i1.5182.
[9] M. S. Nawawi, F. Sembiring, and A. Erfina, “Implementasi Algoritma K-Means Clustering Menggunakan Orange Untuk Penentuan Produk Busana Muslim Terlaris,” … Teknol. Inf. dan …, pp. 789–797, 2021, [Online]. Available: http://prosiding.unipma.ac.id/index.php/SENATIK/article/view/1837%0Ahttp://prosiding.unipma.ac.id/index.php/SENATIK/article/viewFile/1837/1723
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[11] Satria and A. Anggrawan, “Aplikasi K-Means Berbasis Web untuk Klasifikasi Kelas Unggulan Web-based Application of K-Means for classification of Excellence,” vol. 21, no. 1, pp. 111–124, 2021.
[12] R. K. Dinata, S. Safwandi, N. Hasdyna, and N. Azizah, “Analisis K-Means Clustering pada Data Sepeda Motor,” INFORMAL Informatics J., vol. 5, no. 1, p. 10, 2020, doi: 10.19184/isj.v5i1.17071.
[13] L. Fimawahib and E. Rouza, “Penerapan K-Means Clustering pada Penentuan Jenis Pembelajaran di Universitas Pasir Pengaraian,” INOVTEK Polbeng - Seri Inform., vol. 6, no. 2, p. 234, 2021, doi: 10.35314/isi.v6i2.2096.
[14] M. Y. Rizki, F. Fania, and A. P. Windarto, “Implementasi K-Means Clustering Dalam Mengelompokkan Jumlah Penjualan Ikan Laut Di Tpi Menurut Wilayah,” JIKO (Jurnal Inform. dan Komputer), vol. 3, no. 2, pp. 69–74, 2020, doi: 10.33387/jiko.v3i2.1640.
[15] A. Kuntjoro, B. D. Setiawan, and R. S. Perdana, “Algoritme Genetika Untuk Optimasi K-Means Clustering Dalam Pengelompokan Data Tsunami,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 10, pp. 3865–3872, 2018, [Online]. Available: http://j-ptiik.ub.ac.id
[16] Dharshinni, N. P., Azmi, F., Fawwaz, I., Husein, A. M., & Siregar, S. D. (2019, July). Analysis of accuracy K-means and apriori algorithms for patient data clusters. In Journal of Physics: Conference Series (Vol. 1230, No. 1, p. 012020). IOP Publishing.
[17] Siregar, S. D., Panjaitan, B., Girsang, E., & Dabukke, H. (2019). Learning Media Using Discovery Learning Approach to Improve Student Learning Outcomes. Jurnal Pendidikan Fisika, 8(2), 120-125.
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