Penentuan Prioritas Perbaikan Jalan Menggunakan Fuzzy C-Means : Studi Kasus Perbaikan Jalan Di Kota Samarinda

Priority Road Restoration Classification Using Fuzzy C-Means: A Case Study In Samarinda City

Novianti Puspitasari* -  Department of Informatics, Universitas Mulawarman, Indonesia
Rosmasari Rosmasari -  Department of Informatics, Universitas Mulawarman, Indonesia
Stefanie Stefanie -  Department of Informatics, Universitas Mulawarman, Indonesia
Open Access Copyright (c) 2017 Jurnal Teknologi dan Sistem Komputer

One of the factors traffic accidents is caused by a damaged road. Therefore, road improvements based on the priorities scale is indispensable. This study implements the Fuzzy C-means method. The method is capable of classifying data based on the characteristics. The results showed that the FCM algorithm was able to classify the road improvements into four groups; 1, 2, 3, and 4 priorities. Based on the test results the accuracy of calculations on the data of road damage, there are 8 correct data from 9 trial data or 88.89%, which indicates that the method FCM clustering results and a precise calculation.

Keywords
fuzzy C-Means;damaged road;fuzzy clustering

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Article Info
Submitted: 2016-12-07
Published: 2017-01-30
Section: Articles
Language: ID
Statistics: 523 248
  1. H. L. Sari and D. Suranti, "Perbandingan Algoritma Fuzzy C-Means (FCM) Dan Algoritma Mixture Dalam Penclusteran Data Curah Hujan Kota Bengkulu," in Seminar Nasional Aplikasi Teknologi Informasi (SNATI), 2016.
  2. A. Ramadhani, A. Farmadi, and I. Budiman, "Clustering Data Cuaca Untuk Pengenalan Pola Perioditas Iklim Wilayah Pelaihari Dengan Metode Fuzzy C-Means," Jurnal Teknologi dan Industri (Diskontinu), vol. 3, no. 1, pp. 57-64, 2015.
  3. N. Menon and R. Ramakrishnan, "Brain Tumor Segmentation in MRI images using unsupervised Artificial Bee Colony algorithm and FCM clustering," in Communications and Signal Processing (ICCSP), 2015 International Conference on, 2015, pp. 0006-0009: IEEE.
  4. Z. Zhang and B. Gu, "Intrusion Detection Network Based on Fuzzy C-Means and Particle Swarm Optimization," in Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation, 2016, pp. 111-119: Springer.
  5. R. Vijayanandh and G. Balakrishnan, "Hillclimbing segmentation with fuzzy C-means based human skin region detection using Bayes rule," European Journal of Scientific Research, vol. 76, no. 1, pp. 95-107, 2012.
  6. Y. Zheng, B. Jeon, D. Xu, Q. Wu, and H. Zhang, "Image segmentation by generalized hierarchical fuzzy C-means algorithm," Journal of Intelligent & Fuzzy Systems, vol. 28, no. 2, pp. 961-973, 2015.
  7. Y. Aditya Nur Santoso, "Penerapan Algoritma Fuzzy C-means untuk Clustering Objek Wisata," Program Studi Sistem Informasi FTI-UKSW, 2012.
  8. G. Zhu, J. Chen, and P. Zhang, "Fuzzy c-means clustering identification method of urban road traffic state," in Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on, 2015, pp. 302-307: IEEE.
  9. T. A. Munandar and W. O. Widyarto, "Clustering Data Nilai Mahasiswa untuk Pengelompokan Konsentrasi Jurusan Menggunakan Fuzzy Cluster Means," in Seminar Nasional Aplikasi Teknologi Informasi (SNATI), 2013.
  10. L. Rusdiana, "Aplikasi Berbasis Fuzzy C-Means Dalam Penentuan Predikat Kelulusan Mahasiswa," Jurnal Ilmu Komputer, vol. 2, no. 2, pp. 1-9, 2016.
  11. R. J. E. Putra, N. Nasution, and Y. Yummastian, "Aplikasi E-Zakat Penerimaan dan Penyaluran Menggunakan Fuzzy C-Means (Studi Kasus: LAZISMU Pekanbaru)," DIGITAL ZONE: JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI, vol. 6, no. 2, 2015.
  12. A. Ahmadi and S. Hartati, "Penerapan Fuzzy C-Means dalam Sistem Pendukung Keputusan untuk Penentuan Penerima Bantuan Langsung Masyarakat (BLM) PNPM-MPd (Studi Kasus PNPM-MPd Kec. Ngadirojo Kab. Pacitan)," Berkala Ilmiah MIPA, vol. 23, no. 3, 2015.
  13. I. Irsalina, E. Supriyati, and T. Khotimah, "Clustering Gender Berdasarkan Nilai Maksimum Minimum Amplitudo Suara Berbasis Fuzzy C-Means (FCM)," Prosiding SNATIF, vol. 1, pp. 419-424, 2014.
  14. H. L. Sari and D. A. Trianggana, "Pengclusteran Data Curah Hujan Kota Bengkulu Menggunakan Fuzzy Clustering Algoritma Mixture," Jurnal Pseudocode, vol. 1, no. 1, pp. 60-71, 2014.