Clustering Mobilitas Masyarakat Berdasarkan Moda Transportasi Menggunakan Metode K-Means - Humam Aziz Romdhoni; Muhammad Tanzil Furqon; Sigit Adinugroho (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Peoples mobility is the movement of people from one place to another. Peoples mobility is a worthy topic to research. Because by knowing the mobility of society we can know the pattern of the route traversed, the chosen transportation mode, the duration of travel, and others. In this modern era, moving trajectory data of an individual can be known through GPS (Global Positioning System). GPS data obtained can be processed into useful information, such as what each mode of transportation used by each individual. To perform this data processing, we can use one method of data mining, which name is clustering. Clustering is chosen because GPS data for each mode of transport is considered to have almost the same characteristics, so the most appropriate method of information retrieval is by grouping. One of the popular clustering methods is k-means. In this research we can see that the cluster with k-means method has medium to high quality when k value close to quantity of transportation mode seen from the value of silhouette coefficient. From the results of accuracy testing, k-means method shows a good percentage that is 90%.