Writer / NIM
ARFIN USMAN KILO / 531409084
Study Program
S1 - SISTEM INFORMASI
Advisor 1 / NIDN
MOHAMMAD HIDAYAT KONIYO, ST., M.Kom. / 0016047303
Advisor 2 / NIDN
LILLYAN HADJARATIE, S.Kom., M.Si / 0017048001
Abstract
A lot of data that involved in an organization can cause difficulties, or even error at the worse case, in the analyzing process. One of the solutions is using Data Mining, by having agglomerative clustering as the clustering technique. Agglomerative clustering will be used to cluster the students' academic data of Engineering Faculty of Universitas Negeri Gorontalo. The researcher defines the class to the result of the clustering of students' academic data become 16 clusters which is only at gap 1.41. From 1224 students, there are 623 or 51% students who form the cluster. The characteristic of each cluster is showed from the amount of excellent characteristic percentage of each cluster. The minimum percentage of characteristic was 60%. 60% was not considered as the characteristic of the cluster. The information gained from 16 cluster that were formed after being analyzed was almost all students come from Gorontalo city, who were schooled in SMK, from local selection, prefer to choose informatics engineering strata 1. The other information is that only at 11th cluster, which consist of civil engineering department as much as 82% of students, have high GPA (3.00-4.00), while their parents' income only
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