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Laksana Priyo Abadi
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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KAJIAN PENERAPAN ALGORITMA C4.5, NAIVE BAYES, DAN NEURAL NETWORK DALAM PEMILIHAN DOSEN TELADAN: STUDI KASUS UNIVERSITAS INDRAPRASTA Laksana Priyo Abadi
Faktor Exacta Vol 9, No 3 (2016)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (770.175 KB) | DOI: 10.30998/faktorexacta.v9i3.813

Abstract

Improving quality of services to students with a way to do an assessment of the faculty is one way for the Universitas Indraprasta to keep competitive with competitors.In addition, the necessary supporting data as a basis for decision-making comes from parts and other agencies so that decision-making process requires a long time. For data analysis, this research using descriptive analysis techniques and instruments used to determine policy priorities is by using the Algoritma C45, Naive Bayes, and Neural Network with WEKA software. This research is expected to produce a model that can support decision making in terms of determining a lecturer with the best performance will be stated as outstanding lecturers each year.  Keywords: Grade Decision Support, Algoritma C45, Naive Bayes and Neural Network, lecturer assessment
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