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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Infotech Journal PROCEEDING STIMA
Sandi Fajar Rodiyansyah
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Computer Science & IT Control & Systems Engineering Education

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Journal : PROCEEDING STIMA

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LOGIKA FUZZY DALAM SISTEM PENGAMBILAN KEPUTUSAN PENERIMAAN BEASISWA Siti Komariyah; Riza M. Yunus; Sandi Fajar Rodiyansyah
PROCEEDING STIMA PROCEEDING STIMA 2.0
Publisher : PROCEEDING STIMA

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Abstract

The decision making process in determining the right to receive the scholarship are often subjective, where there are some university students who have the ability or value that is not so different. so needed it is presence the systems that support decision making that can be used to simplify the determination of who is entitled to receive a scholarship. This system is supported by Tsukamoto fuzzy logic method that is based on the data and rules of human resources with the criteria set by the group of people. The result of this process is given to university students who are in decision-making on the basis of the acceptance of the scholarship. This software is made by using a MySQL database and IDE netbeans programme language as an instrument by which this application can help in the decision making process scholarship acceptance quickly and accurately.Keywords: Decision Making System, Scholarship, and Tsukamoto Fuzzy Logic.
NAÏVE BAYES CLASSIFICATION UNTUK PENENTUAN KELAYAKAN DONOR DARAH Sandi Fajar Rodiyansyah
PROCEEDING STIMA PROCEEDING STIMA 2.0
Publisher : PROCEEDING STIMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (377.007 KB)

Abstract

Sebelum seseorang melakukan donor darah biasanya tenaga kesehatan melakukan pemeriksaan usia, berat badan, tekanan darah, HB, denyut nadi dan suhu tubuh. Berdasarkan kriteriakriteria tersebut tenaga kesehatan menentukan apakah calon pendonor layak atau tidak melakukan donor darah. Pada penelitian ini, dilakukan implementasi naïve bayes classification untuk penentuan kelayakan donor darah tersebut. Data training yang digunakan pada penelitian ini sejumlah 25 sampel yang dibagi menjadi 2 class yaitu label “layak” sebanyak 60% dan “tidak layak” sebanyak 40%. Setelah dilakukan pengujian, penentuan kelayakan donor darah dengan menggunakan naïve bayes classification memperoleh akurasi sebesar 88%.Kata Kunci : donor darah, naïve bayes classifier
Co-Authors Abijar Algifari Budiman Budiman Dede Abdurrahman Edi Winarko Nunu Nurdiana Riza M. Yunus Siti Komariyah