ANALYSIS OF THESIS ADVISING PATTERN IN MASTER PROGRAM ON FACULTY OF AGRICULTURE IPB USING DATA MINING APPROACH

Lilis Syarifah, Imas Sukaesih Sitanggang, Pudji Muljono

Abstract


The thesis is student study report which is accomplished as a requirement of graduation for Master program. Selecting study’s topic and advisors influence implementation of the study. Therefore, study’s topic is able to improve academic institution quality, however a large number of thesis documents on the repository cause difficulty to get information related to advisor’s expertness and the frequent or rare topic is former studied. Association rule mining can be used to mine information on the related item. This study aims to analyze advising patterns system in Master program on Agriculture based on supervisors and their topic research on metadata thesis of IPB repository and text documents of summary using data mining approach. The datas were collected from the repository of Bogor Agricultural University website and processed using R language programming. Pattern result of the reseach were that the most popular association on supervisor was occurred at support value of 0.00793 or equivalent to 7 theses and four popular topics were Botanical insecticide, Global warming, Upland Rice, and Land Use Change. The analysis result could be useful information to be reference or suggest future research or appropriate supervisor among agricultural.

Keywords


Apriori Algorithm, Association Rule Mining, Bogor Agricultural university, Text Mining

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References


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DOI: http://dx.doi.org/10.17509/edulib.v8i2.12321

DOI (PDF): http://dx.doi.org/10.17509/edulib.v8i2.12321.g8150

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.