Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Syukron Abu Ishaq Alfarozi
Universitas Gadjah Mada
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Kajian Penggunaan Data Log Mahasiswa untuk Berbagai Permasalahan Analisis Pembelajaran Sri Suning Kusumawardani; Syukron Abu Ishaq Alfarozi
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 4: November 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1134.372 KB) | DOI: 10.22146/jnteti.v9i4.779

Abstract

An online learning system is a very crucial thing nowadays to prevent the spread of COVID-19 virus. However, this system is very difficult to maintain student motivation and engagement because there is no direct interaction between teacher and student. This study reviewed the use of student log data for the needs of learning analytics to predict student performance or drop-out trends from a course by looking at the student interaction log data with the system and student demographic data using open data, namely the Open University Learning Analytics Dataset (OULAD). From reviews of several research articles that refer to these data, we can see: 1) the common problems, i.e., prediction of drop-out student, prediction of student performance and engagement; 2) the features used during modeling, i.e., demographics and interactions, either summarized daily or weekly with various feature representations; 3) learning analysis methods that use machine learning algorithm, i.e., Decision Tree (DT), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Long Short-Term Memory (LSTM). This paper also discusses the risk mitigation process of students, planning and designing data systems that support learning analytics, and problems that are often encountered during the modeling process.
Model Berbasis CNN untuk Estimasi dan Autentikasi Copy Detection Pattern Syukron Abu Ishaq Alfarozi; Azkario Rizky Pratama
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i1.6205

Abstract

Counterfeiting has been one of the crimes of the 21st century. One of the methods to overcome product counterfeiting is a copy detection pattern (CDP) stamped on the product. CDP is a copy-sensitive pattern that leads to quality degradation of the pattern after the print and scan process. The amount of information loss is used to distinguish between original and fake CDPs. This paper proposed a CDP estimation model based on the convolutional neural network (CNN), namely, CDP-CNN. The CDP-CNN addresses the spatial dependency of the image patch. Thus, it should be better than the state-of-the-art model that uses a multi-layer perceptron (MLP) architecture. The proposed model had an estimation bit error rate (BER) of 9.91% on the batch estimation method. The error rate was 9% lower than the previous method that used an autoencoder MLP model. The proposed model also had a lower number of parameters compared to the previous method. The effect of preprocessing, namely the use of an unsharp mask, was tested using a statistical testing method. The effect of preprocessing had no significant difference except in the batch estimation scheme where the unsharp mask filter reduced the error rate by at least 0.5%. In addition, the proposed model was also used for the authentication method. The authentication using the estimation model had a good separation distribution to distinguish the fake and original CDPs. Thus, the CDP can still be used as the authentication method with reliable performance. It helps anti-counterfeiting on product distribution and reduces negative impacts on various sectors of the economy.
Co-Authors Pratama, Azkario Rizky Sri Suning Kusumawardani