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Journal : Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi

Implementation of Virtual Reality in Game Platformer Suharyadi, Heri; Sani, Dian Ahkam; Sarwani, Mohammad Zoqi
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 5 No. 1 (2020)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.882 KB) | DOI: 10.25139/inform.v5i1.2327

Abstract

The realization of virtual reality is implemented on an application in the form of a game that will load the genre of platform games, where the genre of this game is highly respected by lovers of games on the Android platform. The hardware used to create virtual reality in this platformer game is an android device that has a gyroscope sensor, virtual reality cardboard, and computer devices. The software uses unity, blender, and Microsoft visual studio as a code editor. The making of this virtual reality game using the gyroscope sensor as full control of character movements that serve to minimize the device needed to play virtual reality games on Android to make it easier and more practical to play. The test results state that virtual reality can be implemented on Android games and the gyroscope sensor functions well as the main movement control in the game
Social Media Analysis Using Probabilistic Neural Network Algorithm to Know Personality Traits Sarwani, Mohammad Zoqi; Sani, Dian Ahkam
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 6 No. 1 (2021)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (237.903 KB) | DOI: 10.25139/inform.v6i1.3307

Abstract

The Internet creates a new space where people can interact and communicate efficiently. Social media is one type of media used to interact on the internet. Facebook and Twitter are one of the social media. Many people are not aware of bringing their personal life into the public. So that unconsciously provides information about his personality. Big Five personality is one type of personality assessment method and is used as a reference in this study. The data used is the social media status from both Facebook and Twitter. Status has been taken from 50 social media users. Each user is taken as a text status. The results of tests performed using the Probabilistic Neural Network algorithm obtained an average accuracy score of 86.99% during the training process and 83.66% at the time of testing with a total of 30 training data and 20 test data.
OPTIMIZING K-MEASN ALGORITHM USING PARTICLE SWARM OPTIMIZATION TO GROUP STUDENT LEARNING PROCESSES Hariyanto, Rudi; Sarwani, Mohammad Zoqi
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 6 No. 1 (2021)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1208.578 KB) | DOI: 10.25139/inform.v6i1.3459

Abstract

In the implementation of learning, several factors affect the student learning process, including internal factors, external factors, and learning approach factors. For example, the physical and spiritual condition of students. Physiological aspects (body, eyes and ears and talents of students, student interests). External factors, for example, environmental conditions around students, family, teachers, community, friends) Thus, learning achievement is significant because educational institutions' success can be seen from how many students learning achievement. This research's first focus is to do student clustering based on their learning process using 11 parameters. Second, using the PSO algorithm to get maximum clustering results. The research data were obtained from vocational secondary education institutions in the city of Pasuruan. The data is obtained from the results of school reports and questionnaires as much as 100 student data. Data attributes include environmental features, social features, and related school features to group student data for learning data processing. From the classification results using the PSO method, the silhouette value is 0.97140754, very close. These results indicate that the PSO method can improve the K-Means clustering method's performance in the classification process of student learning interest.Â