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All Journal CESS (Journal of Computer Engineering, System and Science) Jurnal Teknik Komputer AMIK BSI
Mugi Raharjo
STMIK NUSA MANDIRI
Computer Science & IT

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Implementasi Metode Decision Tree Klasifikasi Data Mining Untuk Prediksi Peminatan Jurusan Robotika oleh Mahasiswa Mugi Raharjo; Ridwan ridwan; Jordy Lasmana Putra; Tommi Alfian Armawan Sandi
JURNAL TEKNIK KOMPUTER Vol 5, No 2 (2019): JTK - Periode Agustus 2019
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (445.881 KB) | DOI: 10.31294/jtk.v5i2.4852

Abstract

Specialization of majors in a study program becomes something important must be an option for a student, for that they must think carefully before choosing the majors. Because later this thing can determine the success or failure of a student to understand what they learned to apply to during the final project. In the past few years there has been a question about the problem of electing majors in the Computer Technology Study Program. Because almost every year the majority of interest voters in majors are interested in computer network majors rather than robotics majors. majoring in majors, so the authors analyzed and retrieved data from 145 student samples in the electronic practicum course and chose 7 attributes in this study because this course was very influential on the interest in the robotics department in the Computer Technology study program. The author uses the classification tree Decision method to predict interest in students. Therefore, with this research, the authors hope that in the future with the results of this analysis can be found a solution to the problem of why students are more inclined to choose the interests of departments other than robotics, whether due to factors or other factors. Keywords: Computer Technology, Analysis, Classification
Prediksi Penyakit Liver Dengan Menggunakan Metode Decision Tree dan Neural Network Popon Handayani; Elah Nurlelah; Mugi Raharjo; Panji Madya Ramdani
CESS (Journal of Computer Engineering, System and Science) Vol 4, No 1 (2019): Januari 2019
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (621.274 KB) | DOI: 10.24114/cess.v4i1.11528

Abstract

Penyakit Liver merupakan penyakit dimana disebabkan oleh berbagai faktor yang merusak hati, seperti virus,penggunaan alkohol dan lainnya. Dalam hal penanganan pasien pada tahap awal sangatlah penting untuk kelangsungan pasien dan penyakit hati tidak mudah ditemukan pada stadium awal. Untuk itu kami melakukan sebuah penelitian dengan menggunakan dua metode yaitu metode Decision Tree dan  Metode Neural Network untuk mengetahui nilai akurasinya. Berdasarkan hasil perbandingan, diperoleh neural network terbaik dalam mendeteksi penyakit hati.
Co-Authors Elah Nurlelah Jordy Lasmana Putra Panji Madya Ramdani Popon Handayani Ridwan ridwan Tommi Alfian Armawan Sandi