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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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Optimasi Manajemen Transaksi Barang Menggunakan Sistem Point Of Sales (POS) di PT Palokoto Agro Industri Hadiwandra, T Yudi; Amri, Rahyul; Nasution, Salhazan; As'Ari, Azi
BATOBO: Jurnal Pengabdian Kepada Masyarakat Vol 3 No 2: BATOBO: Desember 2025
Publisher : Jurusan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/batobo.3.2.41-54

Abstract

PT. Palokoto Agro Industri masih menghadapi permasalahan dalam sistem pencatatan gudang dimana masih mengandalkan microsoft excel dalam pencatatan gudang yang tidak efektif untuk data besar, rawan kesalahan, dan kurang aman. Proses pembaruan stok manual menambah beban kerja serta menurunkan akurasi data. Ketiadaan akses real-time juga membatasi pimpinan dalam memantau keadaan gudang dan mengambil keputusan tepat waktu. Untuk mengatas permasalah tersebut, diusulkan pengembangan sistem Point of Sales berbasis web yang memungkinkan sistem pencatatan gudang yang lebih efektif dan efisien. Sistem ini dibangun dengan pendekatan prototype dengan arsitektur Model-View-Controller (MVC) menggunakan framework Laravel dengan fitur sesuai dengan standar pencatatan gudang, rekapitulasi transaksi  barang masuk dan keluar secara otomatis, memberikan akses yang luas bagi pimpinan untuk memantau keadaan gudang dan pembuatan laporan yang cepat dan kekinian. Berdasarkan hasil pengujian menggunakan standar ISO/IEC 25010, sistem Point of Sales ini telah memenuhi semua aspek kualitas perangkat lunak, seperti functional suitability (100%), reliability (rating A), usability (89,5%), maintainability (rating A), performance efficiency (100%), portability (100%), compatibility (100%), dan security (rating A). Oleh karena itu, aplikasi yang dibuat telah memenuhi kriteria kualitas yang diperlukan serta dapat digunakan sebagai solusi dalam penanganan pencatatan gudang di PT Palokoto Agro industri.
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.
IMPLEMENTASI DEEP REINFORCEMENT LEARNING UNTUK PENGEMBANGAN AGEN GAME DODGEBALL MENGGUNAKAN UNITY ML-AGENTS Fiantino, Dzaky; Hadiwandra, T. Yudi
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 04 (2025): Volume 10 No. 04 Desember 2025 Press
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i04.36072

Abstract

The gaming industry has grown rapidly, and one of the key elements in a game is the non-playable character (NPC). Easily predictable NPC behavior often reduces player engagement and satisfaction. Static or unresponsive NPCs tend to create monotonous and less challenging gameplay experiences, ultimately lowering game quality and player interest. This study applies Deep Reinforcement Learning (DRL) using Unity ML-Agents to train agents in a Dodgeball game, enabling them to make adaptive decisions through self-play. A reward system was designed to provide positive feedback for strategic actions, such as picking up and throwing the ball, and penalties for mistakes, such as hitting walls or being hit by the ball. The training results showed a gradual improvement in agent performance, reflected in the increasing and stable cumulative rewards and ELO scores at the end of training. In performance testing, the DRL agent achieved a 66% win rate against the rule-based agent over 50 matches. A user preference test also revealed that 80% of players preferred competing against the DRL agent, with 60% of them considering it more challenging than the rule-based one. These results demonstrate that the DRL agent not only outperforms the rule-based agent but also provides a more dynamic and realistic gameplay experience.
Co-Authors Adila, Mutiara Dafa 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 Salhazan Nasution Salman Alfarisy Sasongko, Hariyo Shinta Fesri Wandira Wandira, Shinta Fesri Wasilah Wasilah