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All Journal TEKNIK INFORMATIKA Jurnal Informatika dan Teknik Elektro Terapan
Muhamad Komarudin
Universitas Lampung
Computer Science & IT

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ANALISA KLASIFIKASI KUALITAS MAHASISWA LULUSAN BERDASARKAN JALUR PENERIMAAN MENGGUNAKAN ALGORITMA C4.5 (STUDI KASUS: UNIVERSITAS LAMPUNG) Resalina Oktaria; Muhamad Komarudin; Mona Arif Muda
JURNAL TEKNIK INFORMATIKA Vol 12, No 2 (2019): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.79 KB) | DOI: 10.15408/jti.v12i2.11171

Abstract

Universities need a quality evaluation process based on the standards of the National Accreditation Agency for Higher Education (BAN-PT) every year. Therefore, it is necessary for universities knowing the students to evaluate and to maintain the University's Education Efficiency Number (AEE). One of the standards that has been determined by BAN-PT is the quality of students that can be seen from the GPA, the accuracy of completing studies, thesis, path admission, and others. The purpose of this study is to provide information about the quality of students based on SNMPTN and SBMPTN admission with data mining techniques using RapidMiner software in the application of the C4.5 algorithm and using the research method of the Cross-Industry Standard Process for Data Mining (CRIPS-DM). The results of this study were students who has graduated of class I quality was 46% from the SBMPTN path admission, 28% of the SNMPTN path admission, and class II category was 11% from the SBMPTN path admission, and 15% from the SNMPTN path admission. The results of accuracy obtained in decision tree modeling got an accuracy value of 97.46% with an error value of 0.98% and the value of Area Under Curve (AUC) of 0.973 with an error value of 0.014 which is classified into a excellent classification. 
PERANCANGAN MICROSERVICE BERBASIS REST API PADA GOOGLE CLOUD PLATFORM MENGGUNAKAN NODEJS DAN PYTHON Royyan Fajrul Falah; Muhamad Komarudin
Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3s1 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3s1.3506

Abstract

Di Indonesia, penyakit penting pada daun padi ialah hawar daun bakteri, penyakit tungro, bercak daun, dan hawar pelepah daun. Penyakit-penyakit tersebut sangat berpengaruh terhadap hasil panen dan kualitas panen dari komoditas padi. Berdasarkan masalah diatas, salah satu cara penganggulangannya adalah dengan membuat sebuah aplikasi yang dapat mendeteksi penyakit daun padi. Aplikasi pendeteksi penyakit daun padi ini bernama RIFSA (Rice Farmer Assistant) berbasis mobile. Untuk mendukung aplikasi tersebut, dibuatlah sistem microservice berbasis REST API menggunakan NodeJS dan Python pada Google Cloud Platform. Microservice berbasis REST API telah berhasil dibuat menggunakan NodeJS dan Python dengan fitur yaitu Authentication, Hasil Panen, Inventaris, Keuangan, dan Penyakit.
Co-Authors Mona Arif Muda Resalina Oktaria Royyan Fajrul Falah