Garuda - Garba Rujukan Digital

Hadiwandra, T Yudi

Universitas Riau

Author-ID : 2644132

Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences

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Rancang Bangun Aplikasi Android Pengenalan Pembelahan Sel Menggunakan Teknologi Augmented Reality Markerless Fatma Dwi Anisa; T. Yudi Hadiwandra
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7922

Biology learning at SMA N 2 Pangkalan Kuras often requires practical sessions for several learning topics. However, the lack of a dedicated laboratory room and practical tools has led to the discontinuation of practical lessons. One of the topics that requires high visualization is cell division. This research aims to design and develop an Android application based on Augmented Reality (AR) using a markerless method as a practical medium for introducing the process of cell division. The markerless method is used so that the application can be used anywhere and anytime without relying on physical markers. This research utilizes the R&D method, and the application development follows the Multimedia Development Life Cycle (MDLC) method. The markerless AR-based cell division Android application system uses C# programming language and applies the Simultaneous Localization and Mapping (SLAM) algorithm. The application testing follows the ISO 25010 standard, consisting of functional suitability aspects, which achieved a result of 100%. The compatibility test also received a score of 100% for each smartphone that installed, ran, and uninstalled the application. The performance efficiency test shows that the camera system is capable of detecting flat surfaces such as tables, walls, and floors, while the average response time test revealed that the highest response speed was achieved on the latest Android types with larger RAM. The user experience received an "excellent" rating.

Rancang Bangun Aplikasi Android Pengenalan Pembelahan Sel Menggunakan Teknologi Augmented Reality Markerless Fatma Dwi Anisa; T. Yudi Hadiwandra
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7922

Biology learning at SMA N 2 Pangkalan Kuras often requires practical sessions for several learning topics. However, the lack of a dedicated laboratory room and practical tools has led to the discontinuation of practical lessons. One of the topics that requires high visualization is cell division. This research aims to design and develop an Android application based on Augmented Reality (AR) using a markerless method as a practical medium for introducing the process of cell division. The markerless method is used so that the application can be used anywhere and anytime without relying on physical markers. This research utilizes the R&D method, and the application development follows the Multimedia Development Life Cycle (MDLC) method. The markerless AR-based cell division Android application system uses C# programming language and applies the Simultaneous Localization and Mapping (SLAM) algorithm. The application testing follows the ISO 25010 standard, consisting of functional suitability aspects, which achieved a result of 100%. The compatibility test also received a score of 100% for each smartphone that installed, ran, and uninstalled the application. The performance efficiency test shows that the camera system is capable of detecting flat surfaces such as tables, walls, and floors, while the average response time test revealed that the highest response speed was achieved on the latest Android types with larger RAM. The user experience received an "excellent" rating.

Implementasi Deep Learning Untuk Identifikasi Tanaman Rimpang Menggunakan Metode Convolutional Neural Network Mahendri, Diffa Rahmanda Putra; T. Yudi Hadiwandra
Computer Science and Information Technology Vol 6 No 1 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i1.8943

Rhizome plants are spices widely used by Indonesian people as cooking ingredients or traditional medicine. These plants havesimilar appearances, making them difficult to distinguish for some people. Errors in identifying rhizome plants can lead topoisoning, allergies, or unwanted side effects. To simplify identifying these plants, a system is needed to detect and differentiatetypes of rhizome plants, which can be achieved using Convolutional Neural Networks (CNN) with the YOLO algorithm. CNN isa Machine Learning technique capable of identifying objects based on their visual features, enabling efficient differentiation ofrhizome plants. The image dataset used is divided into six classes, with a total of 700 images. Model testing produced resultswith a precision of 98%, recall of 99%, and mAP50-95 of 96%. Future research is expected to increase dataset variety to avoidoverfitting.

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Journal : Jurnal Computer Science and Information Technology (CoSciTech)