SISTEM INFORMASI CLUSTERING KUALITAS PROGRAM STUDI MENGGUNAKAN OLAP (ONLINE ANALYTICAL PROCESSING) DAN K-MEDOIDS

GHUFRON, Ghufron and Surarso, Bayu and Gernowo, Rahmat (2020) SISTEM INFORMASI CLUSTERING KUALITAS PROGRAM STUDI MENGGUNAKAN OLAP (ONLINE ANALYTICAL PROCESSING) DAN K-MEDOIDS. Masters thesis, School of Postgraduate.

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Abstract

Penelitian tentang analisis data pada perguruan tinggi saat ini sangatlah penting dan memiliki banyak manfaat. Penelitian tersebut didasarkan belum adanya analisis data secara realtime data warehouse perguruan tinggi mengakibatkan informasi yang didapat kurang efektif. Oleh karena itu dibutuhkan sistem yang mampu melakukan klaster data kualitas program studi pada perguruan tinggi.Online Analytical Processing (OLAP) dan K-medoidsclustering digunakan pada clustering kualitas program studi. OLAP sistem digunakan untuk menganilis data dilakukan proses Extract, Transform dan Loading kemudian data dimasukkan kedalam data warehouse sedangkan K-medoids digunakan untuk klaster data kualitas program studi untuk mengelompokkan program studi masuk kategori baik maupun program studi cukup. Penelitian ini menghasilkan sistem informasi untuk melakukan analisa data realtime serta pengambilan keputusan strategis terhadap data akademik dan non akademik dan K-medoids clustering digunakan untuk mengklaster kualitas program studi termasuk klaster baik maupun program studi cukup untuk evaluasi perguruan tinggi kedepannya, dengan menggunakan pengujian evaluasi klasterdavies bouldin indexklaster data terbaik yaitu 0,4 yang dapat melakukan clustering kualitas program studi secara realtime. Kata kunci: clustering, data warehouse, OLAP, k-medoids, davies bouldin index Research on data analysis at tertiary institutions is now very important and has many benefits. The research is based on the absence of data analysis in realtime at the college data warehouse, resulting in the information obtained is less effective. Therefore we need a system that is able to cluster data quality in study programs at tertiary institutions. Online Analytical Processing (OLAP) and K-medoids clustering are used in clustering the quality of study programs. OLAP system is used to analyze the data in the process of Extract, Transform, and Loading then the data is entered into the data warehouse while K-medoids are used to cluster study program quality data to classify study programs into both good and sufficient study programs. This research resulted in an information system for analyzing real-time data and strategic decision making on academic and non-academic data and K-medoids clustering is used to cluster the quality of study programs including both good clusters and study programs for future college evaluations, by using cluster evaluation testing davies The best Bouldin cluster data index is 0.4 which can cluster the quality of study programs in real-time. Keywords:clustering, data warehouse, OLAP, k-medoids, davies bouldin index.

Item Type:Thesis (Masters)
Uncontrolled Keywords:clustering, data warehouse, OLAP, k-medoids, davies bouldin index
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:School of Postgraduate > Master Program in Information System
ID Code:82239
Deposited By:INVALID USER
Deposited On:08 Jan 2021 15:28
Last Modified:08 Jan 2021 15:28

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