Mi-Botway: a Deep Learning-based Intelligent University Enquiries Chatbot

Yurio Windiatmoko(1*), Ahmad Fathan Hidayatullah(2), Dhomas Hatta Fudholi(3), Ridho Rahmadi(4),

(1) Master Program in Informatics, Department of Informatics, Universitas Islam Indonesia.
(2) Department of Informatics, Universitas Islam Indonesia
(3) Department of Informatics, Universitas Islam Indonesia
(4) Department of Informatics, Universitas Islam Indonesia
(*) Corresponding Author


Intelligent systems for universities that are powered by artificial intelligence have been developed on a large scale to help people with various tasks. The chatbot concept is nothing new in today's society, which is developing with the latest technology. Students or prospective students often need actual information, such as asking customer service about the university, especially during the current pandemic, when it is difficult to hold a personal meeting in person. Chatbots utilized functionally as lecture schedule information, student grades information, also with some additional features for Muslim prayer schedules and weather forecast information. This conversation bot was developed with a deep learning model adopted by an artificial intelligence model that replicates human intelligence with a specific training scheme. The deep learning implemented is based on RNN which has a special memory storage scheme for deep learning models, in particular in this conversation bot using GRU which is integrated into RASA chatbot framework. GRU is also known as Gated Recurrent Unit, which effectively stores a portion of the memory that is needed, but removes the part that is not necessary. This chatbot is represented by a web application platform created by React JavaScript, and has 0.99 Average Precision Score.


AI Chatbot University

Article Metrics

Abstract view : 148 times


S. Y. Yoo and O. R. Jeong, “Auto-growing knowledge graph-based intelligent chatbot using BERT,”

ICIC Express Lett., vol. 14, no. 1, pp. 67–73, 2020, doi: 10.24507/icicel.14.01.67.

S. Al-fakhri et al., “Aplikasi Chatbot Informasi Kampus Polban Menggunakan Aplikasi LINE

Messenger,” no. November, pp. 302–313, 2019.

W. Dadang, “Deep Learning (Pembelajaran Dalam),” 06 februari 2018, 2018.

https://warstek.com/2018/02/06/deepmachinelearning/ (accessed Jun. 06, 2020).

A. Santoso and G. Ariyanto, “Implementasi Deep Learning Berbasis Keras Untuk Pengenalan

Wajah,” Emit. J. Tek. Elektro, vol. 18, no. 01, pp. 15–21, 2018, doi: 10.23917/emitor.v18i01.6235.

T. Bocklisch, J. Faulkner, N. Pawlowski, and A. Nichol, “Rasa: Open Source Language

Understanding and Dialogue Management,” pp. 1–9, 2017, [Online]. Available:


Y. Windiatmoko, R. Rahmadi, and A. F. Hidayatullah, “Developing Facebook Chatbot Based on

Deep Learning Using RASA Framework for University Enquiries,” IOP Conf. Ser. Mater. Sci. Eng.,

vol. 1077, no. 1, p. 012060, 2021, doi: 10.1088/1757-899x/1077/1/012060.

R. K. Csaky, “Deep Learning Based Chatbot Models,” 2019, [Online]. Available:


B. P. Prashant, M. S. Anil, and K. M. Dilip, “Online Chatting System for College Enquiry using


OF ENGINEERING ( Computer Shri Chhatrapati Shivajiraje College of.”

J. Thakkar, P. Raut, Y. Doshi, and K. Parekh, “Erasmus AI Chatbot,” Int. J. Comput. Sci. Eng., vol.

, no. 10, pp. 498–502, 2018, doi: 10.26438/ijcse/v6i10.498502.

M. Rana, “Digital Commons @ Georgia Southern EagleBot : A Chatbot Based Multi-Tier Question

Answering System for Retrieving Answers From Heterogeneous Sources Using BERT,” pp. 1–54,

, [Online]. Available: https://digitalcommons.georgiasouthern.edu/etd.

A. Jiao, “An Intelligent Chatbot System Based on Entity Extraction Using RASA NLU and Neural

Network,” J. Phys. Conf. Ser., vol. 1487, no. 1, 2020, doi: 10.1088/1742-6596/1487/1/012014.

L. Wu, A. Fisch, S. Chopra, K. Adams, A. Bordes, and J. Weston, “StarSpace: Embed all the

things!,” 32nd AAAI Conf. Artif. Intell. AAAI 2018, pp. 5569–5577, 2018.

J. Lafferty and A. Mccallum, “Conditional Random Fields Probabilistic Models,” vol. 2001, no.

June, pp. 282–289, 2001.

S. Hochreiter and J. Schmidhuber, “Long Short-Term Memory,” Neural Comput., vol. 9, no. 8, pp.

–1780, 1997, doi: 10.1162/neco.1997.9.8.1735.

C. Goutte and E. Gaussier, “Ch10_Witnesses[8463].Pdf,” no. April, 2005, doi: 10.1007/978-3-540-


DOI: https://doi.org/10.29099/ijair.v6i1.247

Copyright (c) 2021 International Journal of Artificial Intelligence Research


International Journal Of Artificial Intelligence Research

Organized by: Departemen Teknik Informatika STMIK Dharma Wacana
Published by: STMIK Dharma Wacana
Jl. Kenanga No.03 Mulyojati 16C Metro Barat Kota Metro Lampung
phone. +62725-7850671
Fax. +62725-7850671
Email: jurnal.ijair@gmail.com | herinurdiyanto@ieee.org 

View IJAIR Statcounter

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.