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All Journal Journal of Computer Networks, Architecture and High Performance Computing
David Fahmi Abdillah
ITB Ahmad Dahlan Lamongan
Computer Science & IT Education

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Serious Games About Indonesia’s Heroes Day for Education About Events 10 November 1945 David Fahmi Abdillah; Ilham Basri K; Titik Khotiah; Yanuangga Galahartlambang; Fery Arianto
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2005

Abstract

Heroes' Day is one of important days for Indonesia, is a day that commemorates one of the most important historical events, especially for the Indonesian people. The independence of the threatened Indonesian nation could be defended by heroes who sacrificed their lives against the invaders, where the incident coincided on November 10, 1945. but there are still many young people today who still do not understand the importance of their hero's struggle on that day, and consider Heroes' Day an ordinary holiday. The serious game is one of the game genres that is commonly used to provide learning about a topic by using games as learning media. By utilizing games as learning media, it will be easier for youth to understand the events of November 10 directly. The game is designed as a first-person shooter game developed using Unity with players playing the role of fighters against invaders on November 10, 1945. After playing, players will be given a series of questionnaires that contain events that occurred in the game and provide value to the game application. from the results of the questionnaire, the value obtained from the questionnaire was 69 and the value of the aspects of the game was 3.37.
Comparison of Machine Learning Techniques in the Classification of Parkinson’s Desease Sufferers Titik Khotiah; David Fahmi Abdillah; Ilham Basri K; Fery Arianto; Abdul Rohman
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2035

Abstract

Parkinson's disease is a progressive and relatively common neurodegenerative  disorder in the central nervous system where sufferers can have difficulty moving. This disease has a high mortality rate in the world of around 9.3 million in 2021. Meanwhile, in Indonesia, it is estimated that as many as 12,980 people die every year due to Parkinson's cases. This increase in cases of death is due to the lack of information about the initial symptoms and dangers of the disease, besides it is important to know how to prevent it early.  Early detection of Parkinson's disease can prevent symptoms of a certain age thereby increasing life expectancy. The existence of a computer-based system for diagnosing Parkinson's disease is called a classification system where the system applies the Machine Learning method. This study aims to compare the performance of algorithms in the classification system of people with computer diseases. In this study, it used methods in  Machine Learning such as K-NN, Multi Layer Percepteron (MLP), Linear Regression and Support Vector Machine (SVM).  The data set in this study was obtained using the Weka application.  The dataset used was Parkinson's Disease data  totaling 195 rows of data taken from the UCI Machine Learning Repository Datasets.  The results  of the experiment based on the four algorithms showed that  the poor performance was the Multi Layer Percepteron approach  to regression data with an RSME value of 0.459.  Meanwhile, the k-Neural Network Algorithm  is a good classification technique forParkinson's problem with an RMSE value of 0.1895.
Co-Authors Abdul Rohman Fery Arianto Ilham Basri K Titik Khotiah Yanuangga Galahartlambang