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Hakikat Dan Prinsip Metode Pembelajaran Pendidikan Agama Islam Arlina Arlina; Jeni Anwar Rambe; Muhammad Zailani; Rani Wardani Hasibuan; Nadya salsabilah; Rizka Ardianti
Ta'rim: Jurnal Pendidikan dan Anak Usia Dini Vol. 4 No. 3 (2023): Agustus : Jurnal Pendidikan dan Anak Usia Dini
Publisher : Sekolah Tinggi Agama Islam Yayasan Pendidikan Ilmu Qur'an Baubau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59059/tarim.v4i3.166

Abstract

The method is very important in facilitating a job because the method is a systemic way of working to facilitate the implementation of an activity in order to achieve the specified goals. The Islamic Religion Learning Method itself certainly cannot be separated from the main objectives of religious education in Indonesia which are listed in article 39 paragraph 2 of Law no. 20 of 2003, "education is an effort to strengthen faith and devotion to God Almighty in accordance with the religion professed by the students concerned by taking into account the demands to respect other religions in the relationship of inter-religious harmony in society to realize national unity. This PAI learning methodology will be meaningless if it is not implemented in educational practice. The implementation of the PAI learning methodology in learning includes the selection of effective and efficient teaching methods. In the Qur'an there are many methods that can be applied to convey God's words to humans, such as the story method, discussion, question and answer (dialogue), parable method (metaphor), method of punishment and reward.
Performance Analysis of Convolutional Neural Networks and Naive Bayes Methods for Disease Classification in Tomato Plant Leaves Nadya Salsabilah; Irawati; Hayati, Lilis Nur
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