Jurnal
Chatbot Designing Information Service for New Student Registration Based on AIML and Machine Learning
XMLOne of the efforts made by universities to serve prospective
students is by providing consulting services and information that is
usually carried out directly at the booth provided, through phone
service or live chat support available on the college website.
Increased visitors will result in waiting times due to limited
availability of officers, which results in decreased satisfaction of
prospective new students, moreover this service is only available
during campus operating hours. One alternative solution to
overcome this problem is to use Chatbot, able to answer questions
raised by prospective new students which can be categorized as
Frequently Asked Questions abbreviated as FAQ. Chatbot
technology can be developed with a variety of AI (Artificial
Intelligence) techniques. One of them is the AIML (Artificial
Intelligence Markup Language) technique. One of the main
drawbacks of AIML is that there is no reasoning ability so a
learning system that is focused on supervised learning is needed. In
the chatbot that will be built the learning process uses a selective
neural conversational model or commonly called the Deep
Semantic Similarity Model (DSSM) developed by Microsoft.
Meanwhile, the measurement of chatbot performance will be done
using Confusion Matrix which is a method of evaluating the
performance of the algorithm from Machine Learning (ML). The
results of the study stated that the chatbot system that was built was
able to answer questions posed by prospective students properly
and correctly while the questions were available in the chatbot
knowledge base.
Detail Information
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Jurnal
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Bahasa |
English
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Penerbit | JAIA – Journal Of Artificial Intelligence And Applications : Pekanbaru., 2020 |
Edisi |
Published
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Copyright |
STMIK Amik Riau
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