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lilis nurhayati
Teknik Informatika, Fakultas Ilmu Komputer, Universitas Muslim Indonesia Makassar, Indonesia
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Performance Analysis of Convolutional Neural Networks and Naive Bayes Methods for Disease Classification in Tomato Plant Leaves Nadya Salsabilah; Irawati; Lilis Nur Hayati
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.255

Abstract

Tomatoes are one of the most widely cultivated and consumed crops, but they are highly susceptible to disease attacks. The main diseases that often attack tomato plants are early blight and late blight. This study compares two machine learning-based classification methods, namely Convolutional Neural Network (CNN) and Naïve Bayes, in detecting tomato leaf diseases. The dataset used consists of 1,255 images obtained from Kaggle, which have been processed and divided into three data ratio scenarios (70:30, 80:20, and 90:10) for training and testing. The results showed that CNN is superior to Naïve Bayes, with the highest accuracy reaching 83.01%, while Naïve Bayes only achieved 34%. With better stability and accuracy, CNN has the potential to help farmers detect diseases more quickly and increase agricultural productivity
Klasifikasi Penyakit Bawang Merah Menggunakan Naïve Bayes dan Convolutional Neural Network Dian; Purnawansyah; Darwis, Herdianti; Nurhayati, Lilis
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3265

Abstract

Bawang merah rentan terhadap serangan penyakit yang dapat mengganggu pertumbuhan dan mengakibatkan hasil panen yang tidak maksimal bahkan gagal panen, seperti bercak ungu dan moler. Penelitian ini bertujuan untuk mengklasifikasikan penyakit bawang merah dengan mengimplementasikan meetode naïve bayes (gaussian , bernoulli, dan multinomial) dan CNN pada citra bawang merah yang diekstraksi menggunakan fourier descriptor. Metode FD – CNN memperoleh tingkat accuracy 98% dalam mengklasifikasikan penyakut bawang merah, moler dan bercak ungu, sedangkan metode CNN tanpa menggunakan ekstraksi menghasilkan nilai accuracy sebesar 97%. Adapun pada metode naïve bayes, pengklasifikasian yang memiliki accuracy paling tinggi adalah metode gaussian naïve bayes sebesar 95% sedangkan yang paling rendah yaitu metode bernoulli naïve bayes dengan tingkat accuracy sebesar 42%. Dengan demikian, dapat disimpulkan bahwa CNN, FD-CNN, dan FD-GNB efektif untuk meningkatkan performa klasifikasi pada citra daun bawang merah.
Co-Authors A?ayunnisa, Nurul Abdi, Muhammad Alim Abdul Wahab Abdullah, Syahrul Mubarak Achmad Suyudi Amiruddin Agung, Riski Dewa Aji, Fery Setyo Akbar, Muhammand Ali Munawir Amelia, Ayu Amir, Nur Hikmah Amrin, Fery Andriawan Andi Rizaldi Pratama Andika Syaputra Andrian, David Anik Nur Handayani Ansari Ansari As'ad, Ihwana Asdar Djamereng Astuti, Wistiani Atmajaya, Dedy Ayu Aksari AZUZ, FAIDAH Bellanov, Agrienta Bora, Leni J Cahya Wulandari, Lusi Mei Damanhuri, Nor Salwa Damayanti, Florencia Agatha Daris, Mega Asfirawati Darwis, Herdianti Dewantoro, Albertus Daru Dewi Pancawati Novalita, Dewi Pancawati Dewi Widyawati Dian Dian Dimas, Ravael Djamereng, Asdar Dolly Indra Dwi Nur Halizah Elvira Siruna Fadly Achmad Faradibah, Amaliah Fattah, Farniwati Febriyanti, Rina Fery Andriawan Amrin Fery Setyo Aji Fikar, Sul Firmiaty, Sri Fitriyani Umar Halimahtul Wildan Haris, Najwan Firdaus Harjuna, Muhammad Harlinda Lahuddin Harun, Makmur Hatta, Andi Muhammad Iqra Rezky Hazjuang, Muhammad Fatwa Herdianti Darwis Herdianti Herdianti Herman Herman Herman Hermany, Nurul Inayah Huda, Besse Nurul Indra, doly Irawati - Irawati Irawati Irawati Irawati Irawati Irja, Mulianty Cipta Irwan Ardyansah Irwan Irwan Ismail, Wawan Iwanto, Agustinus jabir, sitti rahmah Jeremy, Jason Jihan Fatihah Ismiralda Karim Abdullah, Karim Kharawan, Athifah Arsa Kononis, Elisabet Priska Arkadewi Kristiani, Poppy Marselina Lasman Parulian Purba Lokapitasari Belluano, Poetri Lestari Lukman Syafie Magfirah, Magfirah Manga, Abdul Rachman Massa, Paschal Nicollas Dominggo Mude, Muh. Aliyazid Muh Alim Abdi Muhammad Agus Muljanto Muhammad Alim Abdi Muhammad Alwi Muhammad Arif Muhammad Bayu Rahmat Muhammad Dzuljalali Wal Ikram Muhammad Fadhli Ardhi Indrani Muhammad Firdaus Banjar Muhammad Ikhsan Muhammad Ikhsan Supriyadi Muhammad Nazar Alfath Muhammad Rezki Mukarramah, Rifqatul Munawir Munawir Munawir Nasir Hamzah Munawir, Ali Nadya Salsabilah Naqiyah, Ainun Nasir, Haidawati Nathanael, Randy Abednego Nia Kurniati Novianti, Nabila Nugroho, Afifah Khairunnisa Nurfadillah Said Nurlinda Nurlinda Nurul Kholifah Yulinda Nurul Rismayanti Purba, Lasman Parulian Purnawansyah Purnawansyah Purnawansyah R, M Yusuf Rafael, Ivan Rahbiah, Sitti Ramadhan, Wahyu Hidayat Ramdan Satra Ratnawaty, Latifah Resky Anugrah Rezky Anugrah Rezky Anugrah Ridho Anugrah Albanjari Rini Andari, Rini Risti Amelia Rosa Andrie Asmara Sahelangi, Milly Maria Salim, Yulita Salmat, Surya Mudti Saripah Fitriani Satma, Satma Setia Budi, Muh Arif Siswahyudianto Situju, Nurwaini Sri Hartini Sugiarti Sugiarti Sugiarti Sugiarti, Sugiarti Sul Fikar Sulfikar Sulfikar Surachmad, Winarto Surya Mudti Salmat Syafie, Lukman Syahrul Bone Syam, Muhammad Farhan Tenripada, A Ulfah Ulhaq, Muhammad Dhiya Umar Mansyur Umniah Umniah Valentino, Teofilus Veithzal Rivai Zainal Wa Ode Tanti Wahyu Sakti Gunawan Irianto Wahyudi, Yasyfa Xena Arleyda Wal Ikram, Muhammad Dzuljalali Wibowo, Nanang Roni Widari, Nyoman Sri Widyawati, Dewi Winarto Surachmad Wisti Astuti Wulan Purnama Sari Yulita Salim Yundari, Yundari