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Rudi Setiawan
Magister Ilmu Fisika,Universitas Diponegoro
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Journal : Indonesian Journal of Data and Science

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Rice Leaf Disease Classification with Machine Learning: An Approach Using Nu-SVM Setiawan, Rudi; Zein, Hamada; Azdy, Rezania Agramanist; Sulistyowati, Sulistyowati
Indonesian Journal of Data and Science Vol. 4 No. 3 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i3.114

Abstract

This study explores the application of machine learning for classifying rice leaf diseases, employing the Nu-Support Vector Machine (Nu-SVM) algorithm, analyzed through a 5-fold cross-validation approach. The research focuses on distinguishing between healthy leaves and those affected by BrownSpot and LeafBlast diseases. The dataset, comprising segmented rice leaf images processed using Sobel edge detection and Hu Moments feature extraction, is utilized to train and test the model. Results indicate a moderate level of accuracy (52.12% to 53.81%) across the cross-validation folds, with precision and recall metrics demonstrating variability and highlighting the challenges in precise disease classification. Despite this, the model maintains a consistent ability to identify true positives. The study contributes to the field of precision agriculture by showcasing the potential and limitations of using machine learning for plant disease diagnosis. It underscores the need for advanced image processing techniques and diverse feature extraction methods to enhance model performance. The findings are pivotal for developing more effective, automated diagnostic tools in agriculture, thereby aiding in better disease management and potentially improving crop yields. This research serves as a foundational step towards integrating machine learning in agricultural disease detection, emphasizing its importance in sustainable farming practices.
Classification of Rice Grain Varieties Using Ensemble Learning and Image Analysis Techniques Setiawan, Rudi; Hayatou Oumarou
Indonesian Journal of Data and Science Vol. 5 No. 1 (2024): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v5i1.129

Abstract

This research explored the efficacy of machine learning techniques, specifically the Bagging meta-estimator, in the classification of rice grain images. Utilizing a dataset composed of 45,000 images of Arborio, Basmati, and Jasmine rice varieties, a 5-fold cross-validation was employed to evaluate the model's performance. The results were highly promising, with the model consistently achieving over 96% in accuracy, precision, recall, and F1-score across all folds, indicating its robustness and reliability. The study confirmed that ensemble learning techniques could significantly improve the classification accuracy over single classifier systems in agricultural applications. The findings offer a significant contribution to automated agricultural processes, suggesting that machine learning can greatly enhance the efficiency and precision of rice variety classification. These results pave the way for further research into the integration of such models into agricultural quality control and provide a foundation for the exploration of advanced image processing and deep learning techniques for improved performance. Future research directions include expanding the model to encompass a wider variety of crops and integrating additional data modalities to refine classification accuracy further. Practical applications should explore the incorporation of this technology into existing agricultural systems to maximize the benefits of automation in quality control.
Co-Authors Adi Pamungkas Agustiany, Fifin Arifiani Aisyah Rahmawati Alamri, Sazili Mustofa Amani, Risca Andreas N, R Djoko Anggraeni, Ellya ANGGRAENI, RENI Ani Haryani, Ani Annas Alkhowarizmi Aprianti, Penti Arif Setiawan , Andi Aris Wahyu Murdiyanto Aritonang, Sovian Aryani, Wiwik Dyah Asep Ahmad Sopandi Asnani Asnani Aulia Safitri, Aulia Azdy, Rezania Agramanist Azzahra, Haliza Bartolomeus Samho Bartoven Vivit Nurdin Beni, Muhammad Bernard Dehaan, Yeovan Naufal Capah, Agitha Casanova Chairunnisa, Devina Azzahra Chatarina Umbul Wahyuni Cristofer, Fernando Daulay, Okky Freeza Dede Hertina Dedet Erawati Denis Pramudia Putra Dermawijaya, Boyke Iskandarsyah Dewi Utami Dewi, Fitria Dewi, Manda Iska Eddy, Syaiful Elsa Efrina Elvi Yenie, Elvi Embunsari, Nur Enggar Alfianto Erdyvania Apritrycia Etty Puji Lestari Fahruzi, Akhmad Faisal, Amir Fatmawati, Fatmawati Fitria, Suci Gifari, Muhammad W. Grahita Kusumastuti, Grahita Hadia Sukma, Yoga Hakim Santoso, Abdul Hamada Zein Handayani, Kiki Yuli Hardi, Rahmat Sulhan Hari Agus Sujono Hartono, Ahmat Dwi Hayatou Oumarou Heri Sutanto Herninda, Amalia Revy Hong, Lim Zhen I Ketut Sutapa Ida Zahrina Imam, Asep Indiriani, Dini Irawan, Ghani Rafif Irwansyah, Defi Iskandar Mirza Istiqomah, Hilmi Aulia Jamaluddin, Bahman Janizal jannah, lailatul Jarwinda, Jarwinda Jayawarsa, A.A. Ketut Juhana, Riyadi Kadir Parewe, Andi Maulidinnawati Abdul Kamal, Ahmad Syazwan Ahmad Kholida, Putri Kisman, Zainul Komala, Yulia Laksono, Muharram Budi Latipah, Asslia Johar Madi, Madi Maharani, Nabilla Mahdi, Arisul Mansurudin, Mansurudin Margianto, Tofik Marlina Marlina Mashud, Mustain Mega Iswari Miati, Iis Muhammad Nur Ihsan, Muhammad Nur Muhartini Salim Muslimin, Ahmad Novi Mustagfirin Mustagfirin Nabila, Laila Nova Resfita Nugroho, Widianto Nuhan, Hudan Khalish Nur Aida Wassi`atu Sakdiah Nurhasan Nugroho Nurwijayanti Oscar Yasunari Pambudi, Wisnu Setyo Pingki Novita Berliana Pratama, Gerald Untirtha Prayuda, Peggy Ivana Priyanto, Rachmat Puji Astuti, Nur Rochmah Dyah Purwoko, Agus Putra, Fajri Profesio Putri Kholida Putri, Natasya Armelia Putri, Sherlyana Hardiyandeffi Raditia Fath Kharomatudzaky Rahmadi, Isnaini Rahmahtrisilvia Rahmahtrisilvia Rahman, Fikri Aulia Rahman, Rabiatul Adawiah Abdul Rahman, Titik Khawa Abdul Rahman, Yusuf A. Ramayanti, Rizka Renaldy, Rexsa Resfita, Nova Rio Febrianto Arifendi, Rio Febrianto Riyadl, Ahmad Ronny Durrotun Nasihien, Ronny Durrotun Rozak, Abd Rumondang, Rumondang Rupiarti, Riski Mini Saadah, Neng Siti Nur Sabar Sabar Sdarmin Sudarmin, Sdarmin Sekar Ambarsari Sujatmiko Putri Sepiah Dwi Cahyani Setiawan, Agung W. Setiawan, Cahya Heru Shamsuddin, Syamimi Siagian, Apriansyah Dharmawan Siburian, Marsudi siregar, umaiyu Siti Khumayah Sparingga, Daniel Sri Ernawati Sulistyowati Sulistyowati Sumarmi Supriyadi Supriyadi Supriyanto, Adolf Asih Susilo Susilo Sutikno Sutikno Syah, Yogi Darman Syahputra, Ahmad Reynaldi Syahrizal Nasution Syaripudin Syaripudin Thahyo Subroto, Thahyo Triharjanto, Robertus Heru Umar Al Faruq Wahyuningtyas, Amalia Wibowo, Nanang Roni Widodo Widodo, Panut Widodo, Teguh Heri Y. H. Yogaswara, Y. H. YOSAN, R BAGUS Yoseptry, Ricky Yulianti, Wayan Rifa Zaenal Arifin Zulmiyetri Zulmiyetri