Open AccessPenerapan Metode K-Medoids Untuk Pengelompokkan Kondisi Jalan Di Kota Semarang
Author(s) -
Siti Asmiatun,
Nur Wakhidah,
Astrid Novita Putri
Publication year - 2019
Publication title -
jatisi (jurnal teknik informatika dan sistem informasi)/jatisi: jurnal teknik informatika dan sistem informasi
Language(s) - English
Resource type - Journals
eISSN - 2503-2933
pISSN - 2407-4322
DOI - 10.35957/jatisi.v6i2.193
Subject(s) - transport engineering , medoid , data collection , computer science , engineering , cluster analysis , statistics , mathematics , artificial intelligence
Road conditions in Indonesia specifically in the city of Semarang are more often damaged during the rainy season. If needed it will not be repaired users can increase fuel usage and vehicle maintenance until it passes through traffic safety. One of the solutions to these problems is to provide up-to-date information on the surface of the road so that the department can repair roads quickly. This study discusses the grouping of road data using the k-medoids method. Road condition data collection uses an accelerometer sensor that supports data according to mobile devices. From the data used, the number of 638 data was successfully grouped into 3 clusters which could indicate the level of frequency of roads that were good, lightly damaged and heavily damaged