KLASIFIKASI INTENT MENGGUNAKAN SOFTMAX DAN KLASIFIKASI ENTITAS MENGGUNAKAN CONDITIONAL RANDOM FIELD PADA FRAMEWORK RASA

FIRDAUS, RONI STARKO and Abdiansah, Abdiansah and Utami, Alvi Syahrini (2023) KLASIFIKASI INTENT MENGGUNAKAN SOFTMAX DAN KLASIFIKASI ENTITAS MENGGUNAKAN CONDITIONAL RANDOM FIELD PADA FRAMEWORK RASA. Undergraduate thesis, Sriwijaya University.

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Abstract

This research aims to develop a Chatbot Intent Classification and Entity Classification on the RASA Framework using the Softmax and Conditional Random Field methods. In the process of creating a chatbot, there are several problems that often arise, one of which is the low accuracy of entity classification and intent classification, which causes the chatbot to not perform as expected. These problems will be addressed using a machine learning approach with the Softmax and Conditional Random Field methods, which have been proven efficient for classifying intent and entities based on user input sentences in the chatbot. The research results show that intent classification using softmax achieved an average accuracy of 0.86, precision of 0.93, recall of 0.92, and F1-score of 0.92. Entity classification using Conditional Random Field achieved an average accuracy of 0.89, precision of 0.92, recall of 0.95, and F1-score of 0.93, using 132 test data consisting of questions or commands related to the Academic Information System of the Department of Informatics Engineering, Sriwijaya University, in the Indonesian language.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Chatbot, klasifikasi intent, klasifikasi entitas, softmax, Conditional Random Field
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Roni Starko Firdaus
Date Deposited:	28 Jul 2023 01:19
Last Modified:	28 Jul 2023 01:19
URI:	http://repository.unsri.ac.id/id/eprint/122596

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