Published: 2021-12-30
Algoritma Artificial Neural Network pada Text-based Chatbot Frequently Asked Question (FAQ) Web Kuliah Universitas Nasional
DOI: 10.35870/jtik.v5i4.261
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Abstract
The technology development increase the number of automation system in indudustry. One of them is Chatbot application in education industry. This automation technology is able to lessen university's service in order to facilitate the students' need of information whenever and wherever they are. Lack of student literacy regarding the functions and use of the web in conducting online lectures causes the same number of questions repeatedly to the university, which are actually frequently asked questions that have been written in a list of frequently asked questions (Faq), such as: assignment submission, forget passwords, lectures online, video conference lectures and lecture web applications on android. Chatbot will automatically answer students' question in university web page by providing information and suggesting a proper answer suit to the question. This research will develop Chatbot type based on text by applying Artificial Neural Network (ANN) algorithm . The applied data set while conducting the Chatbot coaching is the questions data which frequently being asked (FAQ) in the study web, 25 questions with its answer which is divided into 16 labels or classes. The testing is conducted by using 110 different conversations from the dataset but have the same intention. From those 110 conversation, the Chatbot succed in answering 107 questions precisely and made 3 wrong conversation. The testing result shows a good result by having 97,27% accuracy and 2,72% error.
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Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 4 (2021)
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Section: Computer & Communication Science
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Published: %750 %e, %2021
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License: CC BY 4.0
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Copyright: © 2021 Authors
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DOI: 10.35870/jtik.v5i4.261
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