Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JUITA : Jurnal Informatika
Riza Arifudin
Informatics Engineering, Faculty of Mathematics and Natural Sciences, Semarang State University.
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Enhancing Durrotalk Chatbot Accuracy Utilizing a Hybrid Model Based on Recurrent Neural Network (RNN) Algorithm and Decision Tree Dede Rizki Darmawan; Riza Arifudin
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.20868

Abstract

DurroTalk, a chatbot for new student admissions at Pondok Pesantren Durrotu Ahlissunnah Waljamaah, Semarang, integrates a hybrid model with Recurrent Neural Network (RNN) and Decision Tree. RNN, the base model, employs Natural Language Processing (NLP) to understand sentence structure and context, overcoming vanishing gradient through LSTM layers. The Decision Tree normalizes words, addressing slang and synonyms. The hybrid model boosts chatbot accuracy by 9%, reaching 77% from the initial 68%. This research signifies progress in integrating artificial intelligence into traditional education, showcasing a chatbot adept at handling non-standard language. Decision Tree integration enhances overall performance, making the chatbot proficient in understanding user inputs and generating contextually relevant responses. This study exemplifies the potential of AI, particularly chatbot technology, in modernizing educational processes at traditional institutions.
Co-Authors Dede Rizki Darmawan