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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Ilmiah Media Sisfo Indonesian Journal of Electrical Engineering and Computer Science Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi Jurnal Pengabdian Masyarakat Unama Prosiding Seminar Nasional Ilmu Teknik
WILLY RIYADI
Universitas Dinamika Bangsa, Jambi, Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering

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Perancangan Alat Deteksi Tingkat Kematangan Buah Mangga Indramayu Berdasarkan Kandungan Gas dan Pengolahan Citra Menggunakan YOLOv11 Adi Kusuma; Jasmir Jasmir; Willy Riyadi; Ahmad Ahmad
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.151

Abstract

Indramayu mango is a seasonal fruit that is highly favored due to its delicious taste and high nutritional content. However, high mango production is often not supported by adequate post-harvest facilities, particularly in terms of fruit ripeness classification. Currently, mango ripeness classification is still performed manually, which tends to be subjective and inconsistent. To address this issue, this study proposes a ripeness detection system for Indramayu mangoes by integrating the TGS2602 gas sensor and the YOLOv11 algorithm based on image processing. The TGS2602 sensor is used to detect ethylene gas emitted by ripe mangoes, while YOLOv11 is employed for visual image analysis of the fruit. This study aims to evaluate the system’s performance in classifying ripe and unripe mangoes, as well as analyze the integration between the gas sensor and the object detection model. The test results show that the TGS2602 sensor can detect increased ethylene gas concentration in ripe mangoes, while YOLOv11 demonstrates high accuracy in detecting mangoes based on visual images, with precision and recall close to 1.0. The system was also tested under various lighting conditions, including dark environments, and still performed well, although with a slight decrease in accuracy under low-light conditions.
Co-Authors Abdul Harris Abdul Harris Abidin, Dodo Zaenal Adi Kusuma Ahmad Ahmad Ali, Edi Amroni Amroni Arvita, Yulia Bustami, M. Irwan Desi Kisbianty, Desi Despita Meisak Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin, Fachruddin Ibnu Sani Wijaya ISW Ido Fitra Ramadhan Igra Soliqin Ika Riski Monika Irawan Irawan Irawan, Beni Jasmir Jasmir Jasmir Jasmir Jasmir Jasmir Jasmir, Jasmir Junaidi, Feri Khairuldi Kiki Fauzi Kurniabudi Kurniabudi, Kurniabudi Lies Aryani Lina Juriatun Nasirin M. Irwan Bustami Marrylinteri Istoningtyas Muhammat Andri Pareza Alam Jusia Pareza Alam Jusia, Pareza Alam Randa, Wahidul Riko Ardiyanto Rohaini, Eni Rohaini, Eni Selphia , Megah SIKA, XAVERIUS Sika, Xaverius Silvia Rianti Agustini Sutoyo, Mochammad Arief Hermawan Xaverius Sika Yessi Hartiwi YOSE, IMELDA Yovi Pratama Yulia Arvita Zulia, Restutik