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All Journal Mechatronics, Electrical Power, and Vehicular Technology Journal of Educational Chemistry (JEC)
Sakti, Rizky Hamdani
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Chemistry Education Electrical & Electronics Engineering

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KIMI.AR Application for Easier and Interactive Chemistry Learning Irawan, Elysa Nensy; Salman, Fauzie; Putri, Aisyah Aira; Sakti, Rizky Hamdani; Mulya, Tri Seda; Venica, Liptia
Journal of Educational Chemistry (JEC) Vol 5, No 2 (2023)
Publisher : Chemistry Education Department

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jec.2023.5.2.16077

Abstract

Chemistry is a crucial subject since it covers the structure and makeup of the world around us. However, chemistry is frequently cited as a subject that students dislike. Most secondary school pupils believe that chemistry is difficult, uninteresting, and unimportant. Therefore, an improvement in learning technic is needed. An application called KIMI.AR was created in this research. KIMI.AR is a learning media in the form of a mobile-based augmented reality application regarding elements and the formation of chemical reactions that are expected to solve high school students' problems in the chemistry learning process. What makes the KIMI.AR application better than other chemistry learning applications is the focus on the displayed material according to the user's level and displaying descriptions in addition to 3D visualization that students can access through their respective Android devices. So, through the KIMI.AR application, learning chemistry becomes easier and more interesting.
KIMI.AR Application for Easier and Interactive Chemistry Learning Irawan, Elysa Nensy; Salman, Fauzie; Putri, Aisyah Aira; Sakti, Rizky Hamdani; Mulya, Tri Seda; Venica, Liptia
Journal of Educational Chemistry (JEC) Vol. 5 No. 2 (2023)
Publisher : Department of Chemistry Education, Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jec.2023.5.2.16077

Abstract

Chemistry is a crucial subject since it covers the structure and makeup of the world around us. However, chemistry is frequently cited as a subject that students dislike. Most secondary school pupils believe that chemistry is difficult, uninteresting, and unimportant. Therefore, an improvement in learning technic is needed. An application called KIMI.AR was created in this research. KIMI.AR is a learning media in the form of a mobile-based augmented reality application regarding elements and the formation of chemical reactions that are expected to solve high school students' problems in the chemistry learning process. What makes the KIMI.AR application better than other chemistry learning applications is the focus on the displayed material according to the user's level and displaying descriptions in addition to 3D visualization that students can access through their respective Android devices. So, through the KIMI.AR application, learning chemistry becomes easier and more interesting.
An evaluation of stereo vision for distance estimation using the SGBM algorithm in the CARLA simulator Sakti, Rizky Hamdani; Venica, Liptia; Putri, Dewi Indriati Hadi; Kosmaga, Shinta Rohmatika; Rijanto, Estiko
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1284

Abstract

This paper presents an evaluation of stereo vision based on the semi-global block matching (SGBM) algorithm for distance estimation in an autonomous parking scenario using the CARLA simulator. Distance-disparity regression functions are explored to enhance distance estimation accuracy. The proposed distance estimation model was evaluated using the design science research methodology (DSRM) framework, with experimental validation conducted in CARLA’s promenade environment. The evaluation employed root mean square error (RMSE) and relative error metrics to assess performance. Experiments were performed within a range of 40-350 cm, which is relevant for autonomous parking applications. The experimental results show that the algorithm achieves an overall RMSE of 1.69 cm and an average relative error of 1.1 %. The findings contribute to the advancement of perception systems for autonomous vehicles, particularly in challenging environments.
Co-Authors Elysa Nensy Irawan Estiko Rijanto Hadi Putri, Dewi Indriati Kosmaga, Shinta Rohmatika Liptia Venica Mulya, Tri Seda Putri, Aisyah Aira Salman, Fauzie