Sistem Tanya Jawab Konsultasi Shalat Berbasis RASA Natural Language Understanding (NLU)

Muhammad Rizqi Sholahuddin, Firas Atqiya


A chatbot is an intelligent system that provides users with direct interaction with machines via written media. This paper describes how to use chatbots to ask questions about prayer procedures. A Muslim sometimes has questions about the procedure for praying when he finds a difference between the procedures performed by other Muslims. In this case, the use of chatbots is to provide an explanation. This chatbot was developed using a deep learning model, especially LSTM, that was integrated with the RASA framework. LSTM (Long Short Term Memory) can efficiently save some of the needed memory while also removing some of the unnecessary memory. The Telegram platform was chosen for the chatbot's implementation. The results showed that the chatbot telegram prayer consultation with DIET Classifier and RASA was able to recognize questions and provide answers in the form of text and images, with 96 percent accuracy.


S. Yoo and O. Jeong, “Auto-Growing Knowledge Graph-Based Intelligent Chatbot Using BERT.” ICIC International 学会, 2020. Accessed: Sep. 07, 2021. [Online]. Available:

F. H. Firmansyah, I. P. Sari, and M. Musyarofah, “Pengembangan Media Pembelajaran Interaktif Berbasis Android Untuk Pembelajaran Terbuka dan Jarak Jauh di Universitas Pendidikan Indonesia,” Edsence J. Pendidik. Multimed., vol. 1, no. 2, pp. 99–108, Dec. 2019, doi: 10.17509/edsence.v1i2.21667.

A. G. I. Hutabarat and A. C. Padmasari, “Rancang Bangun Game Tradisional ‘Tambah Satu’ berbasis Platform Android,” Edsence J. Pendidik. Multimed., vol. 2, no. 1, pp. 29–44, Jun. 2020, doi: 10.17509/edsence.v2i1.25028.

P. R. Shalih and I. Irfansyah, “Perancangan Game Berbasis Multimedia Development Life Cycle (MDLC) Tentang Tokoh Pahlawan Indonesia Masa Kini untuk Generasi Z,” Edsence J. Pendidik. Multimed., vol. 2, no. 2, pp. 83–92, Dec. 2020, doi: 10.17509/edsence.v2i2.26690.

H. Toba and B. Wijaya, “Implementasi Sistem Tanya Jawab Berbasis Skenario untuk Mendukung Proses Akademik dengan IBM Watson Assistant,” J. Edukasi Dan Penelit. Inform. JEPIN, vol. 6, no. 2, p. 154, Aug. 2020, doi: 10.26418/jp.v6i2.40715.

E. N. S. C. P and I. Afrianto, “Rancang Bangun Aplikasi Chatbot Informasi Objek Wisata Kota Bandung dengan Pendekatan Natural Language Processing,” Komputa J. Ilm. Komput. Dan Inform., vol. 4, no. 1, pp. 49–54, Mar. 2015, doi: 10.34010/komputa.v4i1.2410.

S. Triputra and F. Atqiya, “Implementation of Natural Language Processing in Seller-bot for SMEs,” J. Phys. Conf. Ser., vol. 1764, no. 1, p. 012069, Feb. 2021, doi: 10.1088/1742-6596/1764/1/012069.

W. Suwarningsih, “Sistem Tanya Jawab Medis Berbasis Case Base Reasoning Menggunakan Semantic Role Labelling,” Disertasi Program Doktor, Institut Teknologi Bandung, 2017.

J. L. Kolodner, “An introduction to case-based reasoning,” vol. 6, pp. 3–34, 1992, doi:

G. G. Chowdhury, “Natural language processing,” Ann Rev Info Sci Tech, vol. 37, pp. 51–89, Jan. 2005, doi:

J. Pustejovsky and A. Stubbs, Natural Language Annotation for Machine Learning, 3rd ed. O’Reilly Media, 2013.

B. R. Ranoliya, N. Raghuwanshi, and S. Singh, “Chatbot for university related FAQs,” 2017, pp. 1525–1530. doi: 10.1109/ICACCI.2017.8126057.

E. Ovchinnikova, Integration of World Knowledge for Natural Language Understanding. Atlantis Press, 2012. [Online]. Available:

C. Olah, “Understanding LSTM Networks,” Aug. 27, 2015.

N. K. Manaswi, “RNN and LSTM,” in Deep Learning with Applications Using Python, Berkeley, CA: Apress, 2018, pp. 115–126. doi: 10.1007/978-1-4842-3516-4_9.

M. Saini, “Using the DIET classifier for intent classification in dialogue,”, Jul. 29, 2020. (accessed Sep. 28, 2021).

T. Bunk, D. Varshneya, V. Vlasov, and A. Nichol, “DIET: Lightweight Language Understanding for Dialogue Systems,” ArXiv200409936 Cs, May 2020, Accessed: Dec. 19, 2021. [Online]. Available:



  • There are currently no refbacks.

Copyright (c) 2021 Edsence: Jurnal Pendidikan Multimedia

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

Jurnal Pendidikan Multimedia (Edsence) ( p-ISSN:2685-2489 | e-ISSN:2685-2535) published by Universitas Pendidikan Indonesia (UPI)

Indexed by:



p-ISSN:2685-2489 | e-ISSN:2685-2535


Visitor Number :

View My Stats