PREDIKSI TINGKAT PRSENTASI MAHASISWA BARU MASUK SEBAGAI MAHASISWA AKTIF DI STIKOM UYELINDO KUPANG MENGGUNAKAN ROUGH SET
Keywords:
Data Mining, Rough Set, Acceptance of New Students, Prediction, Qualitative MeasureAbstract
Acceptance of new students is the most important part of STIKOM UYELINDO Kupang as one of the benchmarks for the progress of the campus in the future. In the process of admitting new students (PMB), prospective new students must go through several stages of registration until the stage of filling out the KRS, so that the students concerned are legitimately declared as active students of STIKOM UYELINDO KUPANG. However, many cases occur that not all students arrive at the final stage of filling in the KRS to be declared as active students. Problems that occur result in the division responsible for new students difficult to predict that prospective students concerned in the process of admitting new students, will go through the process until the status of filling KRS or not, and also affect the prediction of the number of new student achievement. This study aims to find out and recognize the pattern of classification of new student registration status so that the level of presentation of new students entering the STIKOM UYELINDO KUPANG can be made by applying the rough set algorithm. In the process of applying Rough Set, it will produce a rule as a rule or pattern for classification of new student registration status data. The data used in this study is the data of new student registration in 2017-2019 with a total record of 869 records. The results of this study are expected to be an important input for the responsibility of new students and high school education institutions, in the strategy of screening new students to achieve the target of better new student admissions.
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