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All Journal Teknika Jupiter Jurnal Informatika Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) INOVTEK Polbeng - Seri Informatika JMM (Jurnal Masyarakat Mandiri) Jurnal Publika Pengabdian Masyarakat SIENNA
Rini Nurlistiani
Institut Informatika Dan Bisnis Darmajaya
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Journal : Jurnal Informatika

 1 
DATA MINING DENGAN ALGORITMA NEURAL NETWORK DAN VISUALISASI DATA UNTUK PREDIKSI KELULUSAN MAHASISWA Neni Purwati; Rini Nurlistiani; Oscar Devinsen
Jurnal Informatika Vol 20, No 2 (2020): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v20i2.2273

Abstract

Graduating on time is the desire of all students, not only that graduating on time is an advantage for both parties, namely students and educational institutions. But the graduation status of students when predicted does not always produce predictions early, so that it can result in graduation not on time. This research was conducted using data of students who graduated for 4 years from 2016-2019. The classification method is an approach to grouping data in data mining, namely classifying data. This classification method can also be used to make predictions for information that has not been previously known. The classification data mining method that will be used is the neural network algorithm. Visualization to display recapitulation data visually more interesting and neural network algorithm to predict student graduation which is difficult to do manually. Attributes used in training data consist of Jenis Kelamin, Asal, Kelas, Jurusan, Umur, IPK, Tanggal Yudicium, Tahun Yudicium and Class Hasil. The attributes that become parameters are 9 attributes, of which 8 are predictor attributes and 1 are results attributes. Training and testing data by changing parameters, namely: Hidden Layer Size: 3, Training Time: 500, Learning Rate: 0.3, Momentum: 0.2 produces a classification showing the level of accuracy using a neural network algorithm is 92.83%. Displays some very complete reporting recapitulation, so that predictions and visualization of the data can help in graduating students and provide recommendations for appropriate actions and must be done by management or the authorities to make decisions.
AUDIT E-LEARNING DENGAN FRAMEWORK COBIT 5.0 DI MASA PANDEMI COVID-19 Rini Nurlistiani; Neni Purwati; Supri Yanto
Jurnal Informatika Vol 21, No 1 (2021): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v21i1.2873

Abstract

The first Coronavirus Disease-2019 (COVID-19) outbreak appeared in Wuhan, China on December 01, 2019 and was declared a pandemic by WHO (world health organization) on March 11, 2020[1]. This condition requires all levels of society to stay at home (WFH), worship, work and study all at home. So that educational institutions are also required to follow government regulations and innovate learning processes that must continue when natural disasters or global pandemics occur through online learning with the aim of improving the quality of learning. Darmajaya Institute of Informatics and Business uses information technology in the form of online learning media called E-Learning for students and lecturers. This of course makes students and lecturers have to adapt in using the information technology. This E-Learning technology is used intensely by students and lecturers (both permanent and external lecturers) of IIB Darmajaya, so that in conditions in the field there are many shortcomings in the E-Learning service at IIB Darmajaya. One way to measure the governance and capability level of E-Learning services at IIB Darmajaya is to conduct a governance audit on the E-Learning services. In this study, a governance framework is needed in the form of Control Objective for Information and Related Technology 5 (COBIT 5.0) which can provide benefits for an agency in achieving strategic goals and optimizing services from information technology.Keywords—Audit Tata Kelola, E-Learning, COBIT 5.0, Maturity Level, Capability Level.
Co-Authors Agus Rahardi Alpenda Yuda Utama Andrean Danofic anggalia wibasuri Anggawidia Wibaselppa Ayu Firdhayanti Erland Nur Syihab Halimah Halimah handoyo widi nugroho Hendra Kurniawan Neni Purwati Oscar Devinsen Rizky Amalia Sasya Nadira Suci Mutiara Supri Yanto Sushanty Saleh Wasilah Wasilah