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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF SCIENCE AND SOCIAL RESEARCH International Journal of Advances in Data and Information Systems INFOKUM Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Jurnal Minfo Polgan (JMP) Journal of Science Technology (JoSTec) Jurnal Pengabdian Masyarakat Nusantara Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Pengabdian kepada Masyarakat Jurnal Pustaka Dianmas Journal of Technology and Computer (JOTECHCOM) LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics JIPITI: Jurnal Pengabdian kepada Masyarakat International Journal of Applied Mathematics and Computing. International Journal of Educational Insights and Innovations (IJEDINS) Outline Journal of Community Development Komunitas: Hasil Kegiatan Pengabdian Masyarakat Indonesia
M. Rhifky Wayahdi
Universitas Battuta
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Veterinary Other

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Artificial Intelligence-Based Hydroponic Plant Disease Detection System (Lactuca sativa) Wayahdi, M. Rhifky; Ruziq, Fahmi; Nurhajijah, Nurhajijah
Journal of Technology and Computer Vol. 2 No. 4 (2025): November 2025 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Hydroponic cultivation of lettuce (Lactuca sativa) offers high water efficiency, yet productivity is frequently compromised by rapid disease spread and nutrient imbalances. Traditional manual monitoring is labor-intensive, time-consuming, and prone to subjective diagnostic errors, often leading to delayed interventions. This study aims to develop an automated, real-time disease detection system by integrating Deep Learning algorithms with an Internet of Things (IoT) architecture. The proposed method utilizes an optimized One-Stage Object Detector based on the YOLO framework, specifically designed for efficient deployment on edge computing devices. The model was trained and validated on a diverse dataset encompassing healthy plants, tip-burn, leaf spot, and nutrient deficiencies, employing rigorous data augmentation to ensure robustness against indoor lighting variability. Experimental results demonstrate that the system achieves a Mean Average Precision (mAP@0.5) of 94.8%, significantly outperforming conventional Support Vector Machine (SVM) approaches and standard detectors. The model maintains high detection accuracy even under complex background conditions. In conclusion, this research provides a viable, low-latency solution for precision agriculture, enabling growers to automate plant health monitoring and effectively minimize crop losses.
Real-Time Classification of Hydroponic Vegetable Types on Mobile Devices Using Lightweight Deep Learning Models Wayahdi, M. Rhifky; Ruziq, Fahmi; Nurhajijah, Nurhajijah
Journal of Technology and Computer Vol. 1 No. 4 (2024): November 2024 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Hydroponic cultivation requires precise monitoring to ensure crop quality and productivity, yet manual identification of vegetable varieties and their growth status remains labor-intensive and prone to error. This study aims to develop a real-time, mobile-based classification system for hydroponic vegetables using lightweight Deep Learning models optimized for edge computing. The proposed method evaluates two distinct architectures, MobileNetV3 and YOLO-Nano, trained via transfer learning on a dataset comprising major hydroponic crops such as Lettuce, Pak Choy, Mustard Greens, and Cherry Tomatoes. Experimental results demonstrate that while YOLO-Nano offers superior inference speed (~55 FPS), MobileNetV3 achieves a significantly higher classification accuracy of 96.4% while maintaining a real-time performance of ~35 FPS on standard mobile hardware. The study concludes that MobileNetV3 provides the optimal balance between accuracy and computational efficiency for handheld agricultural applications. This research contributes a scalable, low-cost solution for smart farming, enabling producers to perform rapid, on-site digital inventory and quality assessment without reliance on internet connectivity.
Computational Simulation and Algorithm Analysis for Solving Combinatorial Optimization Problems in Graph Theory and Discrete Mathematics Dwi Oktaviana; M. Rhifky Wayahdi; Syed Hassan Ali
International Journal of Applied Mathematics and Computing Vol. 1 No. 3 (2024): July : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i3.273

Abstract

Combinatorial optimization is a fundamental area in operations research and computer science, focusing on identifying optimal solutions from a finite set of possibilities. This study explores the integration of branch and bound methods with heuristic algorithms to address optimization problems in graph theory and discrete mathematics. Python was employed for algorithm implementation due to its flexibility and comprehensive computational libraries, enabling efficient data analysis and visualization. Several benchmark problems were examined, including the Traveling Salesman Problem (TSP), Minimum Spanning Tree (MST), and Graph Coloring. Simulations were conducted using datasets of varying sizes (small, medium, and large) to evaluate performance across different scales. The results demonstrate that the hybrid approach achieves a balance between solution quality and computational efficiency, outperforming brute-force methods in terms of speed while maintaining near-optimal accuracy. Tabulated results and graphical comparisons highlight the reduction in computation time and improved scalability of the proposed method. The findings suggest that combining systematic search strategies with heuristics offers a practical and effective framework for solving complex combinatorial optimization problems. Recommendations for future research include testing scalability with larger datasets, incorporating advanced metaheuristics, and applying the approach to real-world domains such as logistics and network design.
Penguatan Kompetensi Transformasi Digital Mahasiswa Universitas Battuta melalui Workshop Pemanfaatan Teknologi Cloud Computing Ginting, Subhan Hafiz Nanda; Wahyuni, Dewi; Sridewi, Nurmala; Wayahdi, M. Rhifky; Darma, Surya
Jurnal Pustaka Dianmas Vol 5, No 2 (2025)
Publisher : Universitas Prof. Dr. Moestopo (Beragama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32509/dianmas.v5i2.6764

Abstract

Digital transformation is a strategic necessity in facing the dynamics of the world of work and developments in the information technology industry. Students, as future professionals, are required to have relevant digital competencies, particularly in the use of cloud computing technology, which is increasingly being used in data management, application development, and network-based collaboration. This community service activity aims to strengthen the digital transformation competencies of Battuta University students through the implementation of structured and applicable cloud computing technology utilization workshops. The methods used in this activity include participant needs analysis, material preparation, interactive workshop implementation, practical guidance, and activity outcome evaluation. The workshop material covered an introduction to the basic concepts of cloud computing, an understanding of key cloud services, and practical use of cloud platforms for data storage, access management, and implementation of simple services. Evaluation was conducted through pre-tests, post-tests, and observation of participant engagement during the activity. The results of the activity showed an increase in students' conceptual understanding and technical abilities in utilizing cloud technology. This activity contributed positively to improving students' readiness to meet competency demands in the digital era and strengthening their technological literacy and adaptation.
IMPLEMENTATION OF THE INTERNET OF THINGS IN CREATING SMART CLASSROOMS Ginting, Subhan Hafiz Nanda; Wahyuni, Dewi; Sridewi, Nurmala; Wayahdi, M. Rhifky; Darma, Surya
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5806

Abstract

Abstract: The development of digital technology has driven the transformation of educational services through the implementation of data-based learning systems and smart devices. One of the emerging approaches is the use of the Internet of Things (IoT) in building smart classrooms, which are classrooms capable of integrating physical devices, sensors, and information systems to improve learning efficiency and learning environment management. This study aims to analyze the implementation of IoT in the formation of smart classrooms, covering aspects of system design, device integration, and evaluation of its effectiveness in supporting the teaching and learning process. The research method used is a quantitative and experimental approach, by designing an IoT-based smart classroom prototype that integrates temperature, humidity, light intensity, and presence detection sensors, as well as device control such as lights, air conditioning, and projectors through an automatic system and remote control. Data was collected through device performance measurements, network stability tests, and questionnaires distributed to users (teachers and students) to assess the system's ease of use and usefulness. The results showed that the implementation of IoT in classrooms can improve the efficiency of facility management through device automation, facilitate real-time monitoring of classroom conditions, and provide a more comfortable and responsive learning environment. In addition, the developed system demonstrated stable data communication performance with low latency within acceptable operational limits. These findings indicate that the application of IoT in smart classrooms has the potential to contribute significantly to improving the quality of learning and classroom management, particularly in supporting a technology-based education ecosystem. This study recommends further development in the areas of data security, device interoperability, and integration with Learning Management Systems (LMS) to strengthen the sustainable implementation of smart classrooms. Keywords: Internet of Things, Smart Classroom, Classroom Automation, Sensors, Technology Based Education. Abstrak: Perkembangan teknologi digital mendorong transformasi layanan pendidikan melalui penerapan sistem pembelajaran berbasis data dan perangkat cerdas. Salah satu pendekatan yang berkembang adalah pemanfaatan Internet of Things (IoT) dalam membangun smart classroom, yaitu ruang kelas yang mampu mengintegrasikan perangkat fisik, sensor, serta sistem informasi untuk meningkatkan efisiensi pembelajaran dan pengelolaan lingkungan belajar. Penelitian ini bertujuan untuk menganalisis implementasi IoT dalam pembentukan smart classroom, mencakup aspek desain sistem, integrasi perangkat, serta evaluasi efektivitasnya dalam mendukung proses belajar mengajar. Metode penelitian yang digunakan adalah pendekatan kuantitatif dan eksperimental, dengan merancang prototipe smart classroom berbasis IoT yang mengintegrasikan sensor suhu, kelembapan, intensitas cahaya, deteksi kehadiran, serta pengendalian perangkat seperti lampu, pendingin ruangan, dan proyektor melalui sistem otomatis maupun kendali jarak jauh. Data dikumpulkan melalui pengukuran kinerja perangkat, uji stabilitas jaringan, serta penyebaran kuesioner kepada pengguna (guru dan siswa) untuk menilai tingkat kemudahan penggunaan dan kebermanfaatan sistem. Hasil penelitian menunjukkan bahwa implementasi IoT pada ruang kelas mampu meningkatkan efisiensi pengelolaan fasilitas melalui otomasi perangkat, mempermudah monitoring kondisi kelas secara real-time, serta memberikan dukungan lingkungan belajar yang lebih nyaman dan responsif. Selain itu, sistem yang dikembangkan menunjukkan performa komunikasi data yang stabil dengan tingkat keterlambatan (latency) yang rendah dalam batas operasional yang dapat diterima. Temuan ini mengindikasikan bahwa penerapan IoT dalam smart classroom berpotensi memberikan kontribusi signifikan terhadap peningkatan kualitas pembelajaran dan manajemen kelas, khususnya dalam mendukung ekosistem pendidikan berbasis teknologi. Penelitian ini merekomendasikan pengembangan lanjutan pada aspek keamanan data, interoperabilitas perangkat, serta integrasi dengan Learning Management System (LMS) untuk memperkuat implementasi smart classroom secara berkelanjutan. Kata Kunci: Internet Of Things, Smart Classroom, Otomasi Ruang Kelas, Sensor, Pendidikan Berbasis Teknologi.
Produksi Video Company Profil Fakultas Teknologi Universitas Battuta Medan dengan Adobe Premier CC 2019 Surya Darma; John John; M. Rhifky Wayahdi; Ihsan Primas Danu
Komunitas: Hasil Kegiatan Pengabdian Masyarakat Indonesia Vol. 3 No. 2 (2025): Mei : Komunitas: Hasil Kegiatan Pengabdian Masyarakat Indonesia
Publisher : Asosiasi Riset Ilmu Tanaman Dan Hewani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/komunitas.v3i1.126

Abstract

This study aims to produce a company profile video for the Faculty of Technology, Battuta University, Medan using Adobe Premiere CC 2019 software. This company profile video is designed to provide a clear picture of the vision, mission, organizational structure, facilities, and superior programs at the Faculty of Technology, Battuta University, Medan. The production process of this video goes through several stages, namely planning, shooting, processing visual materials, and editing to produce a video that is in accordance with the communication objectives to be conveyed. Adobe Premiere CC 2019 was chosen as the main tool in video editing because of the ability of this software to provide various professional editing features, such as transition settings, visual effects, color adjustments, and audio processing that supports the quality of the final video results. The results of this study are in the form of a company profile video that can be used as a promotional media, which is expected to improve the image and attractiveness of the Faculty of Technology, Battuta University, Medan in the eyes of prospective students and the general public. With this video, it is hoped that information about the faculty can be conveyed more effectively and attractively.
Co-Authors Anzani, Nurul Baginda Harahap Davita, Davita Dewi Wahyuni Dewi Wahyuni Dinur Syahputra Dinur Syahputra Dinur Syahputra Ellanda Purwawijaya Ginting, Subhan Hafiz Nanda Guntur, Surya Hasibuan, Eka Hayana Hutasoit, Rutmian Mariama Ihsan Primas Danu John John Manza, Yuke Mughnyanti, Mayang Nanda Ginting, Subhan Hafiz Nur Alisya, Siti Nurhajijah, Nurhajijah Ramadhan, Wisnu Ramadhani, Syafitri Rutmian Mariama Rutmian Mariama Hutasoit ruziq, fahmi Sheila Try Thania Sridewi, Nurmala Subhan Hafiz Nanda Ginting Subhan Hafiz Nanda Ginting Subhan Hafiz Nanda Ginting Surya Darma Surya Darma Surya Guntur Syed Hassan Ali Thania, Sheila Try Zaki, Mohammed