Ekstraksi Pola Hubungan Penerimaan Mahasiswa Baru Dengan Sebaran Wilayah Asal Sekolah Menggunakan ARM Algoritma Apriori
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Competition between Private Universities (PTS) to get new students increasingly tight course, making the marketing department at any educational institution undertake various promotional model that is exciting and innovative, plus competitors from new opening cooperation Asean Economic Community (AEC). One of the breakthrough strategies undertaken apart from the various models of the promotion is to open up the new student registration database that has been saved to be sufficiently large. The goal is to get a pattern of relationships between data on the attributes of the student database. Patterns can provide prefix information (knowledge base) as a base to get a map of the area students who apply to the Banks Association Institute. To get the pattern diekstark database using data mining techniques with association rule mining and algorithms priori.this research uses secondary data that already exists in Marketing Bureau and the Bureau of PTI, the entire database of students who enroll in PERBANAS Institute in period of 3 years (2013-2015. The results of data processing using data mining, can describe patterns of relationships between data attributes are selected, which describes the distribution area prospective students who apply and are accepted on any existing courses at the Institute Banks Association. This pattern can be used to help define marketing strategies on the Bureau to create a campaign targeted at high school and equivalent territory of origin as prospective new student Perbanas Institute. Keywords: extract the data, students, data mining, data patterns, associations, algorithms apriori
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deden deden prayitno, “Ekstraksi Pola Hubungan Penerimaan Mahasiswa Baru Dengan Sebaran Wilayah Asal Sekolah Menggunakan ARM Algoritma Apriori”, JuTISI, vol. 3, no. 1, Apr 2017.
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This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial used, distribution and reproduction in any medium.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.