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Journal : Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control

Development of Android-Based Software to Support The Selection of University Majors that Fits with Student Personality Type Fridayanti, Fridayanti; Uriawan, Wisnu; Atmadja, Aldy Rialdy
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 3, August 2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.81 KB) | DOI: 10.22219/kinetik.v3i3.628

Abstract

Selecting study program is important things that must decide for high school student in Indonesia. However, students often have difficulties to explore the field of study which match with him. Technology can be used as a tool for making a decision, for example by using android application. Android platform has advantages because it is easy to accessible and familiar in teenagers in Indonesia. In this research, an application was developed by Rational Unified Process methodology. The selection of study program is done with knowing personality type. There are 6 criteria in defining personality type with RIASEC method: Realistic, Investigative, Artistic, Social, Enterprising, Conventional. Personality type can be known after user filled the questionnaire in an application. Next, an application can display study program that matches the type of user personality. From evaluation and analysis, the result showed that application is easy to use. It is expected that this application can be a simulated application which provides information and solutions in advance to selecting study program in universities.
Development of Android-Based Software to Support The Selection of University Majors that Fits with Student Personality Type Fridayanti Fridayanti; Wisnu Uriawan; Aldy Rialdy Atmadja
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 3, August 2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v3i3.628

Abstract

Selecting study program is important things that must decide for high school student in Indonesia. However, students often have difficulties to explore the field of study which match with him. Technology can be used as a tool for making a decision, for example by using android application. Android platform has advantages because it is easy to accessible and familiar in teenagers in Indonesia. In this research, an application was developed by Rational Unified Process methodology. The selection of study program is done with knowing personality type. There are 6 criteria in defining personality type with RIASEC method: Realistic, Investigative, Artistic, Social, Enterprising, Conventional. Personality type can be known after user filled the questionnaire in an application. Next, an application can display study program that matches the type of user personality. From evaluation and analysis, the result showed that application is easy to use. It is expected that this application can be a simulated application which provides information and solutions in advance to selecting study program in universities.
Intelligent Traffic Management System Using Mask Regions-Convolutional Neural Network Pasha, Muhammad Kemal; Atmadja, Aldy Rialdy; Firdaus, Muhammad Deden
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2233

Abstract

Urban centers worldwide continue to face challenges in traffic management due to outdated traffic signal infrastructure. This study aims to develop an intelligent traffic management system by implementing the Mask Regions-Convolutional Neural Network (MR-CNN) algorithm for real-time vehicle detection and traffic flow optimization. Utilizing the CRISP-DM framework, this research processes CCTV footage from the Pasteur-Pasopati intersection in Bandung to identify and quantify vehicles dynamically. The proposed system leverages an enhanced Mask R-CNN model with a ResNet-50 FPN backbone to improve detection accuracy. Experimental results demonstrate an 80% vehicle detection accuracy, with a macro-average precision of 0.89, recall of 0.83, and an F1-score of 0.82. These findings highlight the system’s capability to replace conventional fixed-time traffic signals with a more adaptive approach, adjusting green light durations based on real-time traffic density. The proposed solution has significant practical implications for reducing congestion and improving traffic flow efficiency in urban environments.