Chatbot for Signaling Quranic Verses Science Using Support Vector Machine Algorithm - Undang Syaripudin; Deden Suparman; Yana Aditia Gerhana; Ayu Puji Rahayu; Mimin Mintarsih; Rizka Alawiyah (JOIN (Jurnal Online Informatika), 2021)
The many verses in the Qur'an encourage finding the right way how to understand it thematically. The purpose of the research is to develop a chatbot application that can be used to explore and elaborate the content of verses in the Qur’an that hint at science. The support vector machine (SVM) algorithm classifies question and answers datasets in chatbot applications. The number of data sets used is 76, with test data as much as 10%. The test results show that the SVM algorithm is quite good in classifying, with an accuracy value of 87.5%. While the user test results obtained an average MOS of 8.4, which means the chatbot application developed is very effective in understanding the Qur'an, which implies science. This research is expected to provide an overview of the explanation of the Qur'an about science and technology.