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Journal : Bulletin of Electrical Engineering and Informatics

Classification of good and damaged rice using convolutional neural network Dolly Indra; Hadyan Mardhi Fadlillah; Kasman Kasman; Lutfi Budi Ilmawan; Harlinda Lahuddin
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3385

Abstract

Rice production is massive in Indonesia, therefore maintaining the quality of the product is necessary. Detection and classification of objects have become a very important part in image processing. We performed object detection namely rice. After the object is found, it can be classified into two categories, namely good and damaged rice. We conducted a new study on rice which was carried out per group not per grain to obtain or classify good and damaged rice where we had carried out several steps, namely segmentation process using HSV (hue, saturation, value) color space. HSV is used because of its excellence in representing brightness of the image. We considered evaluating brightness because the tendency of damaged rice is darker or paler compared to good rice. To accomodate environment lighting ambiguity we perform the image acquisition in a controlled environment, so that all the images have the same light intensity. Here we use only channel V of HSV to be used in feature extraction using the gray-level co-occurrence matrix (GLCM) and finally convolutional neural network (CNN) is used for classification. From the test experiments that we have done, we have produced 83% prediction accuracy. Considering how similar the good rice is to the spoiled rice, the results are quite impressive.
Co-Authors Abdul Rauf Tuasikal Agung, Riski Dewa Ahmad Toni, Ahmad Aldri Frinaldi Amir, Nur Hikmah Anik Nur Handayani Arfan Zainuddin As'ad, Ihwana Astuti, Wistiani Damanhuri, Nor Salwa Daris, Mega Asfirawati Djamereng, Asdar Erick Irawadi Alwi Erick Irawadi Alwi Erick Irawadi Alwi, Erick Irawadi Erick, Erick Irawadi Alwi Fadly Achmad Farniwati Fattah Fery Setyo Aji Firman Shantya Budi, Firman Shantya Hadyan Mardhi Fadlillah Haerdiansyah Syahnur, Muhammad Harlinda Lahuddin Hayudin Hasnanda Maila Herman Herman Hi. Talib, Juraiz Hidayat, Muh Wahyu Huzain Azis Ihwana As’ad Irawati Irawati Irja, Mulianty Cipta Jafar, Putri Jufriadif Na`am, Jufriadif Julius Santony Kadri Rahmat Suat, Wahyu Kasman Kasman Lilis Nur Hayati lilis nurhayati Lukman Syafie Lutfi Budi Ilmawan Lutfi Budi Ilmawan, Lutfi Budi Manga, Abdul Rachman Mansyur, St. Hajrah Mardiyyah Hasnawi Muh. Ridwan Rahim Muhammad Al Mubarak Muhammad Arfah Asis Muhammad Farhan Hermansyah Mukarramah, Rifqatul Mustika, Mustika Octavia Novanto, Achmad Nur Hayati, Lilis Nurhalima Nurhalima Ode, Nada Kayatri Purnawansyah Purnawansyah Rahma, Dewi Ernita Rahmat Suat, Wahyu Kadri Rahmayani, Nurul Ramadan, Syahril Ramdan Satra Ramdaniah Ramdaniah Rezky Anugrah Rifky Saputra Scania, Muhammad Rosa Andrie Asmara Salsa, Salsabila Aurelia Saputra Scania, Muhammad Rifky Satma, Satma St. Hajrah Mansyur Subhan Ardhiman Sugiarti, Sugiarti Sukur, Widianti Syahnur, Muh. Haerdiansyah Syahrul Mubarak Abdullah Tasmil Tasmil Tasrif Hasanuddin Taufik, Muhammad Asrai Umar Mansyur Umar, Fitriyani Veithzal Rivai Zainal Wahyu Sakti Gunawan Irianto Yuhandri Yuhandri, Yuhandri Yundari, Yundari Zahra, Andi Fathimatuz Zahra