Department of Informatics, Universitas Mulawarman, Indonesia
BibTex Citation Data :
@article{JTSISKOM12842, author = {Novianti Puspitasari and Rosmasari Rosmasari and Stefanie Stefanie}, title = {Penentuan Prioritas Perbaikan Jalan Menggunakan Fuzzy C-Means : Studi Kasus Perbaikan Jalan Di Kota Samarinda}, journal = {Jurnal Teknologi dan Sistem Komputer}, volume = {5}, number = {1}, year = {2017}, keywords = {fuzzy C-Means;damaged road;fuzzy clustering}, abstract = { 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. }, issn = {2338-0403}, pages = {7--14} doi = {10.14710/jtsiskom.5.1.2017.7-14}, url = {https://jtsiskom.undip.ac.id/article/view/12842} }
Refworks Citation Data :
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.
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