Thesis

Development of Chatbot System by Using Decision Tree Algorithm for Medical Specialist

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The rapid advancement of technology has a big impact on how we live our daily lives. Artificial
Intelligence (AI), or more precisely, an AI-powered chatbot, is one of those technologies. This virtual
assistant has gained a lot of popularity recently, mostly because of noteworthy advancements in
artificial intelligence, machine learning, and other basic fields like neural networks and natural
language processing. These chatbots use interactive questions to efficiently converse with everyone.
Additionally, hospitals are starting to incorporate online components so that people can learn more
about the facility and some of the services it offers. The objective of this project is to use decision tree
algorithms to create an AI chatbot system for medical specialists. Based on the input of symptoms and
comorbidities, the system will be compared to another algorithm to evaluate which one performs
better. In this study, two machine learning algorithm models—the DT classifier and the RF classifier—
were constructed and trained. Each model's accuracy score is used to assess it. Based on the findings,
it is recommended to utilise the RF algorithm rather than the DT method for the Chatbot Dataset
because it has a higher accuracy score.

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Availability

Detail Information

Series Title

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Call Number

BI 24-006

Publisher

i3L, Jakarta : i3L, Jakarta., 2024

Collation

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Language

English

ISBN/ISSN

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Classification

NONE

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Artificial Intelligence
Machine learning
Chatbot
Decision Tree

Specific Detail Info

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Statement of Responsibility

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Other version/related

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