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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat Pascal: Journal of Computer Science and Informatics
Sony Bahagia Sinaga
STMIK Mulia Darma
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Pemasangan Dan Pemeliharaan Jaringan Komputer Pada Sekolah Menengah Kejuruan Parulian 1 Medan Sony Bahagia Sinaga; Berto Nadeak
Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat Vol. 1 No. 02 (2024): Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat
Publisher : CV. Devi Tara Innovations

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Abstract

The development of computer technology is increasing rapidly, this can be seen in the era of the 80s computer networks are still a puzzle that academics want to answer, and in 1988 computer networks began to be used in universities, companies, now entering this millennium era, especially the world wide internet has become the daily reality of millions of people on this earth. In addition, network hardware and software have completely changed, at the beginning of its development almost all networks were built from coaxial cables, now many of them have been built from fiber optics or wireless communication. Computer network technology is already used in various fields including education. Some schools have computers to speed up the work process, and some even use computer network technology to support the learning process. Currently, many schools have computer networks that integrate local networks into intranet and internet networks. Given the need for computer-based education delivery, computer networks in schools are very helpful in the teaching and learning process and make it easier for students and teachers to access information through the internet. In this training, participants will be taught and accompanied to learn to install computer networks. The purpose of this activity is to provide basic computer network training to students, starting from the introduction of computer networks, the practice of making network cables to the configuration of LAN computer networks. The results obtained in general students quickly mastered the material in the installation of computer networks, this is shown by the results of the pre-test. The importance of the results of this service is used to find out how much ability to absorb/capture the material provided by the instructor.
Development and Performance Evaluation of an IoT-Based Smart Irrigation System for Real-Time Soil Moisture Monitoring and Automatic Irrigation Siti Rubiah; Tasya Halizha Lubis; Haryoko Ichsan Prabowo; Dina Lorensa Sinaga; Sony Bahagia Sinaga
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 02 (2026): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Manual irrigation management often results in watering practices that do not reflect actual soil moisture conditions, leading to inefficient water use and reduced crop productivity. This study aims to design and implement an Internet of Things (IoT)-based Smart Irrigation System capable of monitoring soil moisture in real time while automatically controlling the irrigation process. The research employed a Research and Development (R&D) method using a prototyping approach, including requirement identification, system design, hardware and software implementation, system integration, and performance testing. The proposed system was developed using an ESP32 microcontroller, a capacitive soil moisture sensor, a relay module, a water pump, and an internet-based monitoring dashboard. System performance was evaluated through sensor readings, real-time data monitoring, automatic pump control, response time measurement, and operational stability testing. The results demonstrate that the proposed system successfully monitors soil moisture, transmits data to the dashboard in real time, and automatically controls the irrigation pump based on predefined soil moisture thresholds. The implementation of a threshold with hysteresis mechanism improves pump stability by reducing frequent switching caused by sensor fluctuations. Furthermore, the system exhibits a relatively fast response time and stable operation throughout the testing period. These findings indicate that IoT technology provides an effective solution for developing efficient, practical, and scalable smart irrigation systems suitable for small- and medium-scale agricultural applications.
Jaringan CNN 3D Berorientasi Konteks Untuk Mengenali Aksi Dengan Memanfaatkan Segmentasi Semantik (CARS) Kevin H Hutahaean; Sony Bahagia Sinaga; Chandra Frenki Sianturi
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol. 9 No. 1 (2025): AI dan Teknologi Cerdas: Pilar Ekosistem Digital Berkelanjutan dalam Meningkatk
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v9i1.9567

Abstract

Pengenalan aksi manusia menjadi topik penting dalam bidang visi komputer karena beragam aplikasinya, seperti pengawasan, interaksi manusia–komputer, dan sistem otonom. Walaupun metode CNN 3D terbaru mampu menangkap informasi spasial dan temporal dengan hasil yang cukup baik, pendekatan ini masih menghadapi kendala dalam memanfaatkan konteks lingkungan tempat aksi berlangsung. Keterbatasan tersebut mengurangi kemampuannya dalam membedakan aksi yang mirip serta mengidentifikasi skenario rumit secara lebih akurat. Untuk mengatasi permasalahan tersebut, penelitian ini mengusulkan pendekatan baru yang disebut Context-aware 3D CNN for Action Recognition based on Semantic Segmentation (CARS). Metode CARS mencakup modul pengenal adegan intermediari yang memanfaatkan model segmentasi semantik guna mengekstraksi petunjuk kontekstual dari rangkaian video. Informasi kontekstual tersebut kemudian direpresentasikan dan digabungkan dengan fitur yang dipelajari oleh model 3D CNN, sehingga terbentuk peta fitur global yang lebih kaya. Selain itu, CARS memasukkan Convolutional Block Attention Module (CBAM), yang menerapkan mekanisme atensi kanal dan spasial untuk menyoroti bagian paling penting dari peta fitur 3D CNN. Peneliti juga mengganti fungsi kerugian entropi silang konvensional dengan focal loss, yang lebih efektif dalam menangani kelas tindakan manusia yang jarang muncul dan sulit dibedakan. Serangkaian eksperimen pada berbagai dataset benchmark terkenal, seperti HMD51 dan UCF101, menunjukkan bahwa metode CARS yang diusulkan mampu melampaui kinerja pendekatan mutakhir berbasis 3D CNN. Selain itu, modul ekstraksi konteks dalam CARS bersifat generik dan plug-and-play, sehingga dapat meningkatkan akurasi klasifikasi pada berbagai arsitektur 3D CNN.
Optimization of Indoor Navigation Using the A Algorithm and Adaptive Grid (Gridadapte) for Efficient Pathfinding Asia Leny Ritonga; Ega Fransiska; Hafidz Afdillah; Johan Alfredo Nainggolan; Rahmad Imam Sobari; Sony Bahagia Sinaga
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 01 (2025): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Optimal path navigation in indoor environments is a crucial problem in the development of robotic systems and location-based services due to complex spatial structures, the presence of obstacles, and limited available pathways. The A* algorithm, as a heuristic-based pathfinding method, is widely used; however, its performance degrades on high-resolution grid maps because of the increasing number of nodes that must be explored. This study proposes the integration of the A* algorithm with an adaptive grid simplification method (Gridadapte) to improve pathfinding efficiency without sacrificing route quality. The research methodology includes grid-based indoor map modeling, the application of Gridadapte to reduce cell density in low-obstacle areas, and the implementation of the A* heuristic function for optimal path search. Performance evaluation is conducted through simulations on several indoor map scenarios by comparing conventional A* and Gridadapte-based A* in terms of the number of explored nodes, path length, and computation time. Simulation results show that the proposed approach significantly reduces the number of search nodes by 30–45% and accelerates computation time by 25–40% compared to A* on regular grids, while the resulting path length remains optimal and does not experience a significant increase. These findings indicate that Gridadapte is effective in reducing the A* search space while preserving the topological structure of the environment. Therefore, the combination of A* and Gridadapte is proven to enhance both the efficiency and accuracy of pathfinding in complex indoor environments. This approach has strong potential for application in autonomous robotic systems, smart building guidance systems, and location-based Internet of Things (IoT) applications in indoor settings such as hospitals, campuses, and shopping malls.
Co-Authors Asia Leny Ritonga Berto Nadeak Chandra Frenki Sianturi Dina Lorensa Sinaga Ega Fransiska Hafidz Afdillah Haryoko Ichsan Prabowo Johan Alfredo Nainggolan Kevin H Hutahaean Rahmad Imam Sobari Siti Rubiah Tasya Halizha Lubis