Chatbot for Signaling Quranic Verses Science Using Support Vector Machine Algorithm

U. Syaripudin, D. Suparman, Y. A. Gerhana, A. Rahayu, Mimin Mintarsih, Rizka Alawiyah
{"title":"Chatbot for Signaling Quranic Verses Science Using Support Vector Machine Algorithm","authors":"U. Syaripudin, D. Suparman, Y. A. Gerhana, A. Rahayu, Mimin Mintarsih, Rizka Alawiyah","doi":"10.15575/join.v6i2.827","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOIN Jurnal Online Informatika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15575/join.v6i2.827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

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.
基于支持向量机算法的古兰经科学聊天机器人信令
古兰经中的许多经文鼓励找到正确的方式来理解它的主题。该研究的目的是开发一种聊天机器人应用程序,可以用来探索和阐述古兰经中暗示科学的经文的内容。支持向量机(SVM)算法在聊天机器人应用中对问题和答案数据集进行分类。使用的数据集数量为76,测试数据高达10%。测试结果表明,SVM算法具有较好的分类效果,准确率达到87.5%。而用户测试结果获得的平均MOS为8.4,这意味着开发的聊天机器人应用程序在理解蕴含科学的古兰经方面非常有效。本研究旨在对古兰经关于科学技术的解释提供一个概览。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
2
审稿时长
12 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信