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All Journal EDUMATIC: Jurnal Pendidikan Informatika Jutsi: Jurnal Teknologi dan Sistem Informasi
Nurhaliza, Rizky
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Computer Science & IT Education

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Implementasi Metode Multi Attribute Utility Theory pada Sistem Pendukung Keputusan dalam Pemilihan Siswa Unggulan Nurhaliza, Rizky; Nurwati, Nurwati; Santoso, Santoso
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25600

Abstract

Vocational School of Al Furqon is a private school that annually holds an election of excellent students. Vocational school Al Furqon selects excellent students manually so that the results of the assessment of superior students are less effective. The purpose of our research is to produce a decision-support information system for the selection of Excellent Students at Al-Furqon Batu Bara Vocational School by building a decision-support system using the Multi-Attribute Utility Theory (MAUT) method. The type of research used is quantitative. The research method used to develop this system is the waterfall method which starts from analysis, planning, implementation, and testing. In our research stages are interviews, observations, and literature studies. There are 70 alternatives but only 9 alternatives fall into the criteria, so only 9 alternatives are processed in the calculation. The subject and object of our research is the excellent student of Al Furqon Vocational School. The results of our research are presented in the form of a Decision Support System, the selection for superior students has been successfully implemented in the form of a website that can be accessed universally and anytime using the Internet with the results of the MAUT method calculation, Tantri Agustin Damanik got the highest score, namely with a total score of 1000 and was successfully named as an excellent student according to the calculation of the MAUT method and according to predetermined criteria.
PREDIKSI PENERIMAAN BANTUAN PIP PADA SMKS AL-FURQON BATUBARA DENGAN METODE NAÏVE BAYES Aini, Nur; Handoko, Wiwin; Nurhaliza, Rizky
JUTSI: Jurnal Teknologi dan Sistem Informasi Vol 4, No 1 (2024): FEBRUARY 2024
Publisher : LPPM STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jutsi.v4i1.2971

Abstract

Abstract: The PIP program is assistance for poor students which is provided to students from families who are poor and cannot carry out learning activities at school. At Al-Furqon Private Vocational School, Batubara Regency, there are still problems in the decision-making process to determine which students are entitled to PIP scholarships, so researchers apply the Naïve Bayes method. Naive Bayes is a simple probabilistic forecasting method based on the application of Bayes' theorem (or Bayes' rule) with the assumption of independence (non-independence) in the selection of PIP recipient students with the criteria of Report Card Value, Parent's Dependents, Parent's Income, and KIP Recipients using the above calculations. The report card value is 75 dependent parents, more than 3 people with income below IDR 1,500,000 and those who do not receive PKH so that 74 people receive PIP results and 117 people do not receive results. In calculating the Naive Bayes method using Python tools, the accuracy results were 96%.Keywords: data mining; naïve bayes; scholarship pip Abstrak: Program PIP termasuk beasiswa untuk siswa tidak mampu yang disajikan kepada siswa dari keluarga miskin dan tidak bisa melaksanakan kegiatan pembelajaran di sekolah. Pada SMK Swasta Al-Furqon Kabupaten Batubara masih menghadapi masalah dalam cara mengambil keputusan untuk penentuan peserta didik yang berwenang atas bantuan PIP sehinga peneliti menerapkan pendekatan Naïve Bayes. Naive Bayes suatu metode prediksi probabilistik sederhana yang berlandaskan pada teorema Bayes dengan hipotesis independensi (non-independent) dalam pemilihan peserta didik penerima PIP dengan kriteria Nilai Raport, Tanggungan Ortu, Penghasilan Ortu, dan Penerima PKH dengan perhitungan nilai raport diatas 75, tanggungan ortu lebih dari 3 orang, penghasilan dibawah Rp 1.500.000 dan tidak menerima PKH sehingga mendapatkan hasil yang Diterima PIP sebanyak 74 orang dan yang Tidak Diterima sebanyak 117 orang. Dalam perhitungan metode Naive Bayes dengan tools jupyter notebook dari anaconda mendapatkan hasil akurasi 97%.Kata Kunci: data mining; naïve bayes; beasiswa pip
Co-Authors Nur Aini Nurwati Nurwati SANTOSO SANTOSO Wiwin Handoko