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All Journal Jurnal Simetris ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Martabe : Jurnal Pengabdian Kepada Masyarakat IJISTECH (International Journal Of Information System & Technology) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Minda Baharu Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informasi dan Teknologi Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Yumary: Jurnal Pengabdian kepada Masyarakat IJISTECH Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Quancom: Jurnal Quantum Komputer The Indonesian Journal of Computer Science
Caniago, Deosa Putra
Institut Teknolog Batam
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Journal : The Indonesian Journal of Computer Science

 1 
Implementation of Deep Learning Using YOLOv7 and Telegram Notifications for Preventing Illegal Fishing in the Waters of Batam Muhammad Abrar; Deosa Putra Caniago
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i5.3472

Abstract

Batam Island is one of Indonesia's outermost islands that directly borders neighboring countries. The implementation of YOLOv7 to detect ships in the waters of Batam is capable of identifying ship objects, with test results after 100 training epochs producing a precision value of 1.00 and a confidence value of 0.882, indicating a high level of confidence in the detection results of the YOLOv7 model. The F1 score of 0.99 at a confidence level of 0.729 shows that this model achieves a high level of accuracy in object detection. Based on the evaluation results using a confusion matrix, it indicates high accuracy for each class in the YOLOv7 model: Ferry 93%, Indonesian Fishing Boat 85%, Malaysian Fishing Boat 89%, Thai Fishing Boat 91%, Vietnamese Fishing Boat 82%, Speedboat 94%, and Tanker 83%. The testing results of the website application integrated with YOLOv7 and Telegram bot produce a website that can detect objects and send notifications, thus expected to prevent illegal fishing.
Sistem Monitoring Kecepatan Angin Dan Suhu Udara Berbasis Notifikasi Telegram Muhammad Abrar; Deosa Putra Caniago; Rifa’atul Mahmudah Burhan; Refli Noviardi
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4305

Abstract

The unpredictable weather in Batam City impacts the use of sea transportation, which is frequently used by residents for inter-island crossings. There is a need for a real-time monitoring system for wind speed and air temperature, along with notifications when wind speeds become potentially dangerous for sea transportation users. In this research, an Internet of Things (IoT)-based monitoring system for wind speed and air temperature was implemented using the Thingspeak platform for real-time monitoring. The test results demonstrated that the monitoring system could successfully store wind speed and air temperature data in the Thingspeak database. Additionally, Thingspeak was able to display graphs of wind speed and air temperature. The notification tests via Telegram showed that when the wind speed reached 1.5-2.9 m/s, an alert warning was sent, and when the wind speed exceeded 3 m/s, a danger warning was issued.
Sistem Pengawasan Berbasis IoT pada Robot Vision Untuk Peningkatan Keamanan Perimeter di Industri Batam Caniago, Deosa Putra; Muhammad Jufri; M Abrar Masril
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4476

Abstract

Batam City faces significant security challenges alongside rapid industrial growth, making the need for effective surveillance systems in industrial areas urgent. This research developed a surveillance robot utilizing Internet of Things and computer vision technologies to enhance perimeter security in industrial zones. The robot is equipped with Arduino as the controller, a Pixy2Cam camera for object detection, and a WiFi module for remote connectivity. Testing results indicate that the robot can detect individuals wearing safety gear in 0.2 seconds and achieves a detection success rate of 100% under ideal conditions. The developed controller application using MIT App Inventor also displays real-time images, allowing for rapid responses to potential threats. This research demonstrates that the developed surveillance robot effectively enhances monitoring in the Batam industrial area.
Transformasi Pertanian Dalam Ruangan: Hidroponik Cerdas Berbasis IoT : Indoor Farming Transformation: IoT-Based Smart Hydroponics Caniago, Deosa Putra; Masril, M Abrar
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i5.3408

Abstract

The growth of technology has had a significant impact on the agricultural sector, including the method of hydroponic cultivation. According to the Basic Health Research (Riskesdas) conducted by the Ministry of Health, 90% of the Indonesian population lacks sufficient vegetable consumption. The World Health Organization (WHO) recommends a daily vegetable intake of around 400 grams for adults, which can be fulfilled through indoor hydroponic gardens. However, hydroponic cultivation requires intensive monitoring and control, posing a challenge for busy urban communities. Therefore, one solution to address the challenges in hydroponic farming is leveraging Internet of Things (IoT) technology and utilizing Real-time Clock (RTC) to create a Smart Indoor Hydroponic Garden system that enables real-time control of water pH and room temperature using temperature sensors and water quality sensors. This system can be utilized by urban individuals who lack access to open land, allowing them to meet their daily vegetable needs directly from home.
Optimizing Hospitality Choices: A Forward Chaining and Certainty Factor-Based Expert System for Recommending 4-Star Hotels in Batam City Caniago, Deosa Putra; Simatupang, Devid Trinaldo; Kurnia, Okki; Septiana, Reski; Sekar, M. Y. Meinadia
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3658

Abstract

Tourism and travel is the largest industry in the world with hotels as a key factor in enjoying a holiday. As the cornerstone of tourism, the hotel industry continues to develop to meet increasingly high customer expectations. The application of high technology is the key to competition between hotels, with several hotels moving towards an innovative and efficient "smart hotel" concept. This research explores the hotel industry in Batam as a unique tourism destination and industrial center. The main focus includes analyzing the level of technology adoption in Batam hotels, identifying trends and factors driving the “smart hotel” concept, and developing expert system models to improve the tourist experience. By combining the two methods of Forward Chaining and Certainty Factors in an Expert System, it is hoped that the results of this research can provide important insights regarding the development of the hotel industry in Batam and the positive impact of technology in improving the quality of service to travelers.
Co-Authors Alhamidi, Alhamidi Andrian Syah Arvy Kurnia Ramadhan Aryo Pratama, Bimo Assaidatul Husna candra, joni eka Candra, Samuel Damanik, Evi Maryati Faizila, Reva Unieq Friadi, John Handayani, Vitri Aprilla Hanif Sumardi Harahap, Widiya Lestari Hendri Kremer Hernando, Luki Hilmy, Ananda Husna, Assaidatul Jabnabillah, Faradibah Jeremy Andika Kevin Antony Kremer, Hendri Kurnia, Okki M Abrar Masril M. Abrar Masril maranti Mardiansyah, Yopy Mardiansyah, Yopy Maria Yosefina Meinadia Sekar Kinanti Aswirawan Masril, M. Abrar Masril, Muhammad Abrar Mhd Adi Setiawan Aritonang Muhammad Abrar Muhammad Abrar Muhammad Abrar Masril Muhammad Abrar Masril Muhammad Adi Sukma Nalendra Muhammad Jufri Muhammad Jufri Muhammad Jufri munir, Zainul Munir Nabilah Nabilah Nadia Widari Nasution Nalendra, Muhammad Adi Sukma Noviardi, Refli Nurcholiq, Rini Nurul Ilmi Reant Egie Fahruddini Ria Sapitri Rifa’atul Mahmudah Burhan Rini Nurcholiq Sapitri, Ria Septiana, Reski Simatupang, Devid Trinaldo Sumijan Sunarsono, Hery Syah, Andrian Syamsiar, Syamsiar Widiya Lestari Harahap