Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Engineering, Mathematics and Computer Science Journal (EMACS) JGGAG (Journal of Games, Game Art, and Gamification)
Shiddiqi, Hafizh Ash
Unknown Affiliation
Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics Other

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

Found 2 Documents
Search

 1 
Leveraging Support Vector Machines and Ensemble Learning for Early Diabetes Risk Assessment: A Comparative Study Shiddiqi, Hafizh Ash; Setiawan, Karli Eka; Fredyan, Renaldy
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 7 No. 1 (2025): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v7i1.12846

Abstract

Currently, diabetes is a hidden, serious threat to human lifestyles through daily food and drink, which has become a formidable global health challenge. As a contribution, this study suggests a way to use machine learning to find people with diabetes by looking at certain health parameters. It does this by using different Support Vector Machine (SVM)-based models, such as different SVMs with different kernels, such as linear, polynomial, radial basis function, and sigmoid kernels; different ensemble bagging with SVM; and different ensemble stacking with various SVM models. The findings demonstrated that utilizing a single SVM model with a linear kernel, ensemble bagging with a linear SVM, and ensemble stacking with different SVM models yielded the most accurate results, achieving 95% accuracy in both diabetes presence and absence. This lends credence to the idea that the incorporation of a linear kernel has the potential to improve the accuracy of determining whether or not diabetic illness is present.
Remake of Survival Horror Video Game and How It’s Implemented: Comparative Analysis on Original and Remake Version of Resident Evil 4 Pratama, Galih Dea; Shiddiqi, Hafizh Ash; Hermawan, Eric Savero; Novika, Andien Dwi; Ardiyanto, Elshad Ryan
Journal of Games, Game Art, and Gamification Vol. 9 No. 1 (2024)
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/jggag.v9i1.10999

Abstract

Video game is particularly known as an interactive media designed to present entertainment among its targeted users. While being released from time to time, there comes the desire to provide the outdated games to the modern audiences, hence surfaces the trend of video game remakes, which recently presented through Resident Evil 4 that serves as the newer version to the original one released in 2005. To give better understanding on the games, there is Elemental Tetrad which emphasizes on four elements like Mechanics, Story, Aesthetics and Technology. In this research, Elemental Tetrad is utilized to analyze both versions of Resident Evil 4, diving deep into how the game elements are implemented by the games while also highlighting the advances presented in the remake version compared to the original one. There are various differences of both games, such as the existence of more new mechanics, the expanded story and characterizations, slight change in the aesthetics to accommodate the realism of the remake, with all are enabled through the usage of latest RE Engine.
Co-Authors Ardiyanto, Elshad Ryan Fredyan, Renaldy Hermawan, Eric Savero Novika, Andien Dwi Pratama, Galih Dea Setiawan, Karli Eka