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All Journal Xplore: Journal of Statistics
Tania Amalia Darsono
Department of Statistics, IPB
Decision Sciences, Operations Research & Management Engineering Mathematics

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Segmentasi Mahasiswa S1 IPB terhadap Sistem Peminjaman Sepeda Tania Amalia Darsono; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 2 No. 1 (2018): 30 Juni 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (270.104 KB) | DOI: 10.29244/xplore.v2i1.74

Abstract

IPB is the one campus that realize the Green Campus program. One of the elements in Green Campus is Green Transportation. In realizing this Green Transportation, IPB has several programs that include the Green Bike program. There are rules in implementation the Green Bike program related to the borrowing system. Because of the borrowing system, it is necessary to make the segmentation of S1 IPB students on bicycle borrowing system. Segmentation of respondent's characteristic used two step clustering method and the result is 3 optimal clusters. Then segmentation on respondent's preference to bicycle borrowing system used k-means method and the result is 2 optimal clusters. Segmentation of bicycle borrowing system based on respondent's characteristic and respondent's preference is 6 combinations of cluster using cross tabulation.
Segmentasi Mahasiswa S1 IPB terhadap Sistem Peminjaman Sepeda Tania Amalia Darsono; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Green Campus is one program of IPB. One element of Green Campus is Green Transportation. There are programs in Green Transportation, one of the programs is Green Bike. There are rules in Green Bike program which were related to the system of borrowing. Based on the rules, so it was required to make segmentation of undergraduate students IPB on bicycle borrowing system. This research used data of undergraduate students IPB on bicycle borrowing system’s preferences and characteristics of respondents. Segmentation on characteristics of respondents using two step cluster method. The distance that was used in two step cluster is log-likelihood and to determinate the optimal clusters using BIC. There are 3 optimal clusters formed and quality of clustering is fair (coefficient Silhouette = 0.3). Then segmentation on bicycle borrowing system’s preferences using kmeans method. The distance that was used in k-means is euclid and there are 2 optimal clusters formed (based on the Pseudo-F value). Based on segmentation on bicycle borrowing system by combining characteristics and preferences of respondents, there are 6 cluters formed.
Co-Authors Aam Alamudi Utami Dyah Syafitri