Determining Zoning of Areas Affected by Flood Disasters in Medan City Using Silhouette Coefficient and Davies Bouldin Index Analysis
DOI:
10.29303/jpm.v19i3.6707Published:
2024-05-30Downloads
Abstract
Several sub-districts are cities that are pretty or even very vulnerable to flood disasters. Therefore, the Government must observe which areas are highly prone to flooding to anticipate safety precautions. One of the relevant methods for handling this case is k-means clustering using the Silhouette Coefficient and Davies-Bouldin Index evaluation. This research uses a quantitative approach using the Silhouette Coefficient and Davies Bouldin Index Analysis method. Based on the research that has been carried out, the results can be obtained that cluster 1 consists of the sub-districts of Medan Polonia, Medan Johor, Medan Selayang, Medan Baru, Medan Tuntungan and Medan Barat. Cluster 2 only has one member, namely the Medan Maimun sub-district; Cluster 3 consists of Medan Sunggal and Medan Belawan sub-districts, and Cluster 4 consists of Medan Marelan, Medan Helvetia and Medan Timur sub-districts. The results of the clustering evaluation that was carried out obtained a Silhouette Coefficient value of 0.505539942 and a Davies-Bouldin Index value of 0.30055. This means that the grouping carried out in this research is accurate.
Keywords:
Clustering; Davies Bouldin Indeks; K-Means; SilhouetteReferences
Heryana, A. (2020). Pengertian dan Jenis-Jenis Bencana. Jakarta: Universitas Esa Unggul..
Nuryanti, N., Tanesib, J. L., & Warsito, A. (2018). Pemetaan Daerah Rawan Banjir dengan Penginderaan Jauh dan Sistem Informasi Geografis di Kecamatan Kupang Timur Kabupaten Kupang Provinsi Nusa Tenggara Timur. Jurnal Fisika: Fisika Sains Dan Aplikasinya, 3(1), 73-79.
Binawan, B. P., & Junaedi, D. (2017). Aplikasi GIS Klasifikasi Tingkat Kerawanan Banjir Wilayah Kabupaten Bandung Menggunakan Metode Weighted Product. Indonesia Journal on Computing (Indo-JC), 2(1), 59-70.
Statistik, B. P. (2022). Badan Pusat Statistik.
Tampubolon, A. O., Siagian, A., & Ardiani, F. (2018). Uji Daya Terima dan Kandungan Zat Gizi Dodol Dengan Penambahan Terung Ungu (Solanum Melongena) Dan Kulit Buah Pepaya (Carica Papaya L) (Doctoral dissertation).
Pramuji, S. E., & Putri, V. S. (2020). Meninjau Efektivitas Penegakan Hukum Penataan Ruang dalam Rangka Mewujudkan Tertib Tata Ruang. Jurnal Pertanahan, 10(1)..
Alamsyah, B., Nuraini, C., & Suwarno, B. (2022). STRATEGI MANAJEMEN MITIGASI BENCANA PESISIR PANTAI TIMUR SUMATERA UTARA. PUBLISH BUKU UNPRI PRESS ISBN, 1-81.
Yana, M. S., Setiawan, L., Ulfa, E. M., & Rusyana, A. (2018). Penerapan Metode K-Means dalam Pengelompokan Wilayah Menurut Intensitas Kejadian Bencana Alam di Indonesia Tahun 2013-2018. Journal of Data Analysis, 1(2), 93-102.
Swindiarto, V. T. P., Sarno, R., & Novitasari, D. C. (2018, September). Integration of fuzzy C-means clustering and TOPSIS (FCM-TOPSIS) with silhouette analysis for multi criteria parameter data. In 2018 International Seminar on Application for Technology of Information and Communication (pp. 463-468). IEEE.
Suyanto, D. (2017). Data Mining untuk klasifikasi dan klasterisasi data. Bandung: Informatika Bandung.
Murti, M. A. W. K. (2017). Penerapan metode K-means clustering untuk mengelompokan potensi produksi buah–buahan di provinsi daerah istimewa yogyakarta. Universitas Sanata Dharma.
Yulian, E. (2018). Text mining dengan k-means clustering pada tema LGBT dalam arsip tweet masyarakat Kota Bandung. Jurnal Matematika “MANTIK, 4(1), 53-58.
Handoyo, R., Mangkudjaja, R., & Nasution, S. M. (2014). Perbandingan metode clustering menggunakan metode Single Linkage dan K-means pada Pengelompokan Dokumen. Jurnal Sifo Mikroskil, 15(2), 73-82.
Saikhu, A., & Gita, Y. B. (2013). Implementasi Deteksi Outlier pada Algoritma Hierarchical Clustering. SEMNASTEKNOMEDIA ONLINE, 1(1), 07-45.
Dehotman, B. J. (2018). Peningkatan hasil evaluasi clustering davies-bouldin index dengan penentuan titik pusat cluster awal algoritma k-means (Doctoral dissertation, Thesis, Universitas Sumatera Utara, Medan)..”
Renard, F. (2017). Flood risk management centred on clusters of territorial vulnerability. Geomatics, Natural Hazards and Risk, 8(2), 525-543.
Meiylimdra Arini Peirmatadeivi, Ruilly A. Heindrawan, S.Kom, M.Eing. 2013. “Kabeil, Karakteiristik Peilanggan Teileipon Mojokeirto), Meingguinakan Cluisteiring Som Dan K-Meians Uintuik Meinguirangi Keisalahan Klasifikasi Peilanggan Peiruisahaan Teileikomuinikasi (Stuidi Kasuis : Pt. Teilkom." Juirnal Teiknik Pomits 1(1).
Sari, N. N. (2018). K-Affinity Propagation (K-AP) Clustering Untuk Klasifikasi Gempa Bumi (Studi Kasus: Gempa Bumi di Indonesia Tahun 2017).
Hardaningrum, O., Sulaeman, C., & Supriyana, E. (2016). Zonasi Rawan Bencana Gempa Bumi Kota Malang Berdasarkan Analisis Horizontal Vertical To Spectral Ratio (HVSR)”. In dalam Prosiding Seminar Nasional MIPA (pp. 170-175).
License
Copyright (c) 2024 Novi Eliza, Ismail Husein, Sajaratud Dur
This work is licensed under a Creative Commons Attribution 4.0 International License.
The following terms apply to authors who publish in this journal:
1. Authors retain copyright and grant the journal first publication rights, with the work simultaneously licensed under a Creative Commons Attribution License 4.0 International License (CC-BY License) that allows others to share the work with an acknowledgment of the work's authorship and first publication in this journal.
2. Authors may enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., posting it to an institutional repository or publishing it in a book), acknowledging its initial publication in this journal.
3. Before and during the submission process, authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website), as this can lead to productive exchanges as well as earlier and greater citation of published work (See The Effect of Open Access).
Downloads
How to Cite
