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All Journal Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains IT JOURNAL RESEARCH AND DEVELOPMENT INOVTEK Polbeng - Seri Informatika Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Teknologi Informatika dan Komputer Jurnal Computer Science and Information Technology (CoSciTech) Jurnal PkM (Pengabdian kepada Masyarakat) Indonesian Journal of Informatic Research and Software Engineering Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi BATOBO: Jurnal Pengabdian Kepada Masyarakat CSRID
Hadiwandra, T Yudi
Universitas Riau
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 Other

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Journal : jurnal computer science and information technology coscitech

 1 
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

Abstract

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

Abstract

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

Abstract

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.
Implementasi Deep Learning Untuk Klasifikasi Penyakit Pada Daun Kelapa Sawit Menggunakan Arsitektur MobileNetV2 Arianda, Habil Putra; Hadiwandra, T. Yudi
Computer Science and Information Technology Vol 6 No 3 (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.v6i3.10306

Abstract

Accurate and efficient identification of diseases in oil palm leaves is a crucial challenge in maintaining plantation productivity and preventing significant crop losses. Limited access to experts and slow detection in the field are often obstacles. This study aims to develop a palm oil leaf disease classification model using a deep learning approach based on Convolutional Neural Network (CNN) with MobileNetV2 architecture. This model utilizes a transfer learning strategy from pre-trained ImageNet weights and is optimized through a two-phase training strategy on a dataset consisting of 1200 augmented oil palm leaf images, covering four classes, namely Healthy Sample, Fusarium Wilt, Parlatoria Blanchardi, and Rachis Blight. Model testing results show an accuracy of 85% on separate test data. The MobileNetV2 architecture was chosen for its lightweight characteristics, making this model efficient and highly suitable for implementation on mobile devices to assist in rapid disease identification in the field and support decision-making by farmers.
Rancang Bangun Aplikasi Point Of Sales Berbasis Web Dengan Arsitektur MVC Menggunakan Framework Laravel Di PT Palokoto Agro Industri As'ari, Azi; Hadiwandra, T. Yudi
Computer Science and Information Technology Vol 6 No 3 (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.v6i3.10308

Abstract

PT Palokoto Agro Industri still relies on Microsoft Excel for warehouse record-keeping, which is ineffective for managing large-scale data, prone to errors, and lacks security. The manual stock update process increases workload and reduces data accuracy. Furthermore, the absence of real-time access limits managers in monitoring warehouse activities and making timely decisions. To address these issues, this study developed a web-based Point Of Sales (POS) application. The application was built using the Model-View-Controller (MVC) architecture and the Laravel framework, equipped with features that align with warehouse recording standards, such as managerial access, automatic calculation of incoming and outgoing goods, and fast report generation. This research applied the Research and Development (R&D) method with a prototyping approach. The application was evaluated using the ISO/IEC 25010 standard, and the results showed that it fulfilled all aspects of software quality, including functional suitability, reliability, usability, performance efficiency, maintainability, portability, compatibility, and security. Therefore, the developed application meets the required quality criteria and can serve as a structured solution for warehouse record-keeping at PT Palokoto Agro Industri.
Co-Authors Adila, Mutiara Dafa Agus Syuhada Alfarisy, Salman Andhi, Rahmat Rizal Arianda, Habil Putra As'Ari, Azi dwi saputra Feri Candra Fiantino, Dzaky Mahendri, Diffa Rahmanda Putra Mhd. Ripaldi Mutiara Dafa Adila Noveri Lysbetti M Oktory, Hafidh Dwika Pratama, Munawwar Anugrah Rahman, Salsabilah Aulia Rahyul Amri Rayhan Al Farassy Salhazan Nasution Salman Alfarisy Sasongko, Hariyo Shinta Fesri Wandira Wandira, Shinta Fesri Wasilah Wasilah