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All Journal JISICOM (Journal of Information System, Infomatics and Computing) Building of Informatics, Technology and Science Publikasi Pengabdian Masyarakat Komputer dan Teknologi (PUNDIMASKOT) Sistem Komputer & Teknologi Intelegensi Artifisial (SIKOMTIA) Jurnal Pengabdian Masyarakat Singa Podium (JPMSIPO) Galaksi
Prambodo, Yoga Listi
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences

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Journal : Sistem Komputer

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Penerapan Metode Color Based Detection Menggunakan Platform ESP32-Cam Sebagai Alat Pendeteksi Ikan Betta Varian Albino Ardiansyah, Fahmi; Prambodo, Yoga Listi; Iswidodo, Iswidodo
Sistem Komputer dan Teknologi Intelegensi Artifisial (SIKOMTIA) Vol. 1 No. 3 (2023): December
Publisher : FIKOM Universitas Bung Karno

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59039/sikomtia.v1i3.17

Abstract

This research aims to overcome the problems that arise in identifying Betta fish variants, especially Albino variants, which are often difficult to distinguish by ordinary people due to difficulties in distinguishing visual differences. This problem encourages the need to develop a tool that is able to automatically distinguish Betta Albino fish variants. This research presents the concept of implementing the ESP32-Cam platform as a Betta Albino fish variant detection tool. The novelty of this research lies in the use of the ESP32-Cam platform which is an innovation as a detection tool. The urgency of this research lies in the need for a tool that can help ordinary people in identifying Betta Albino fish variants easily without requiring knowledge of Betta fish species. The method used in this research is colour-based detection using the eloquent surveillance library. The image capture process is done through an ESP32-Cam camera by utilising the concept of object detection and image processing. This research also involves the application of components such as TCS 3200, LM393, and LCD 1602 I2C to support the function of the detection tool. The results show that the Betta Albino fish variant object detection device is able to identify colour differences accurately. Through the ESP32-Cam platform, this tool successfully creates an automated solution that can distinguish Betta Albino fish variants well. In conclusion, this study confirms that the use of the ESP32-Cam platform in designing the Betta Albino fish variant detection tool can be practically applied. This tool has the potential to contribute in facilitating the accurate identification of Betta Albino fish variants to the general public.
Rancang Bangun Alat Pendeteksi Keaslian Batu Bacan Doko Berbasis Mikrokontroler ATMega2560 Alhamid, Umar Djafar; Prambodo, Yoga Listi; Asruddin, Asruddin
Sistem Komputer dan Teknologi Intelegensi Artifisial (SIKOMTIA) Vol. 1 No. 3 (2023): December
Publisher : FIKOM Universitas Bung Karno

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59039/sikomtia.v1i3.20

Abstract

This research designed and developed a tool to detect the authenticity of Bacan Doko. The development of this tool uses TCS3200 sensor components as a detection of color variations in stones, BH1750 sensors to measure light intensity, and LCD1602 to display information on stone detection results visually. This study aims to overcome the problem of identifying the authenticity of Bacan Doko stones which are often difficult to detect accurately by ordinary people who do not understand the world of gemology, which results in the existence of fake stones on the market. The presence of this tool provides innovation in the world of gemology by utilizing microcontroller and sensor technology to overcome the authentication problem of Bacan Doko stone accurately, and support the integrity of the gemstone market. The development of data processing algorithms is carried out to analyze and process information received from input values on sensors. The detection tool provides good results to recognize and distinguish genuine Bacan Doko stones based on the color characteristics of the sensor identification results TCS3200 taking into account the light intensity measured by the BH1750 sensor and information can be displayed clearly through the LCD screen. The development of this tool successfully proved its effectiveness in identifying the authenticity of Bacan Doko stone. This tool can be a reliable solution for traders and gemstone observers in ensuring the authenticity of Bacan Doko.
Co-Authors Alexius Ulan Bani Alhamid, Umar Djafar Ardiansyah, Fahmi Asruddin, Asruddin Azlan, Azlan Eka Handayani Fifto Nugroho Iswidodo, Iswidodo Kurnia, Mega Tri Lubis, Ahmad Faiz Nuaridito, Muhammad Fahri Pembuain, Fince Saputro, Joko Sharyanto, Sharyanto Wahidin , Ahmad Jurnaidi Wijaya, Dedi Sukma Yusar, Muhammad Rajib