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All Journal Jurnal Teknik Informatika (JUTIF) PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Pratama, Pangeran Fadillah
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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DEVELOPMENT OF AUGMENTED REALITY APPLICATION FOR GEOMETRY LEARNING USING THE MARKER BASED TRACKING METHOD Pratama, Pangeran Fadillah; Hamzah, Muhammad Luthfi; Idria Maita; Megawati, Megawati; Ahsyar, Tengku Khairil
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1928

Abstract

The role of teachers in implementing innovative and creative learning models in the era of industrial revolution 4.0 is an important influence in attracting student’s attention to achieve learning goals. Student’s lack of interest and motivation to learn is a factor in the difficulty of understanding basic mathematical concepts, especially geometric material. Apart from that, it can be seen from the student’s enthusiasm for learning who easily get bored when studying using books alone. The aim of this research is to develop and apply an Android-based augmented reality (AR) application to increase student’s interest in learning and deliver more interactive material. This application uses a marker based tracking method which was developed using the Unity program. The results of application testing using a black box showed that all application features were used successfully without errors. The pre-test and post-test of 19 grade 6 students regarding understanding of geometry material before and after using AR obtained an increase from 60.53 to 86.84. The system usability scale (SUS) test was aimed at teachers and students by providing 10 statements to assess user satisfaction with the application which received a score of 77.84 in the acceptable category. Evaluation of application usability using 3 matrices, namely learnability, obtained a result of 94%, user efficiency in completing tasks was 0.19 goal /sec, and the error matrix obtained a value of 0.44.
Random Forest Optimization Using Particle Swarm Optimization for Diabetes Classification Pratama, Pangeran Fadillah; Rahmadani, Desvita; Nahampun, Rahma Sani; Harmutika, Della; Rahmadeyan, Akhas; Evizal, Muhammad Fikri
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 1 No. 1: PREDATECS July 2023
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v1i1.809

Abstract

Diabetes mellitus is a chronic degenerative disease caused by a lack of insulin production in the pancreas or the body's ability to use insulin less effectively. According to a report by the World Health Organization (WHO), 4% of the total deaths in the world are caused by diabetes. The International Diabetes Federation (IDF) notes that in 2013 there has been an increase in diabetes sufferers. Indonesia is the seventh place with the largest number of cases of diabetes mellitus. In this study, the method used to classify diabetes is using a random forest algorithm with Particle Swarm Optimization (PSO) optimization. This study resulted in an accuracy of the random forest classification algorithm of 78.2% and 82.1 using PSO optimization with an increase in value of 3.9%. It can be concluded that PSO optimization can provide a better increase in classification accuracy values when compared to the random forest algorithm without PSO optimization
Co-Authors Ahsyar, Tengku Khairil Evizal, Muhammad Fikri Hamzah, Muhammad Luthfi Harmutika, Della Idria Maita Megawati - Nahampun, Rahma Sani Rahmadani, Desvita Rahmadeyan, Akhas