Fast and Accurate Indonesian QnA Chatbot Using Bag-of-Words and Deep-Learning For Car Repair Shop Customer Service
Abstract
Keywords
Full Text:
PDFReferences
A. C. Sari, N. Virnilia, J. T. Susanto, K. A. Phiedono, and T. K. Hartono, “Chatbot developments in the business world,” Adv. Sci. Technol. Eng. Syst. J., vol. 5, no. 6, pp. 627–635, 2020.
I. Rizomyliotis, M. N. Kastanakis, A. Giovanis, K. Konstantoulaki, and I. Kostopoulos, “‘How mAy I help you today?’ The use of AI chatbots in small family businesses and the moderating role of customer affective commitment,” J. Bus. Res., vol. 153, pp. 329–340, 2022.
G. Aalipour, P. Kumar, S. Aditham, T. Nguyen, and A. Sood, “Applications of sequence to sequence models for technical support automation,” in 2018 IEEE International Conference on Big Data (Big Data), 2018, pp. 4861–4869.
A. Nursetyo, E. R. Subhiyakto, and others, “Smart chatbot system for E-commerce assitance based on AIML,” in 2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2018, pp. 641–645.
S. A. Prasetya, A. Erwin, and M. Galinium, “Implementing
Indonesian language chatbot for ecommerce site using artificial intelligence markup language (AIML),” in Prosiding Seminar Nasional Pakar, 2018, pp. 313–322.
M. A. Hakim, S. Nurhayati, and K. Indonesia, “Development of Chatbot Application ‘Midwify ‘Based on Android As a Supporting Media To Learn Medical Science in Stikes Bhakti Kencana Bandung,” Komputika J. Sist. Komput., vol. 8, no. 1, 2019.
A. Prasetyo and H. A. Santoso, “Intents Categorization for Chatbot Development Using Recurrent Neural Network (RNN) Learning,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021, vol. 1, pp. 51–55.
C. O. Bilah, T. B. Adji, and N. A. Setiawan, “Intent Detection on Indonesian Text Using Convolutional Neural Network,” in 2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom), 2022, pp. 174–178.
S. P. Barus and E. Surijati, “Chatbot with Dialogflow for FAQ Services in Matana University Library,” Int. J. Informatics Comput., vol. 3, no. 2, pp. 62–70, 2022.
B. P. Wicaksono and A. Zahra, “Design of the use of chatbot as a virtual assistant in banking services in Indonesia,” IAES Int. J. Artif. Intell., vol. 11, no. 1, p. 23, 2022.
A. Elcholiqi and A. Musdholifah, “Chatbot in Bahasa Indonesia using NLP to provide banking information,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 14, no. 1, pp. 91–102, 2020.
D. Gunawan, F. P. Putri, and H. Meidia, “Bershca: bringing chatbot into hotel industry in Indonesia,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 18, no. 2, pp. 839–845, 2020.
F. P. Putri, H. Meidia, and D. Gunawan, “Designing intelligent personalized chatbot for hotel services,” in Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence, 2019, pp. 468–472.
F. Dwitama and A. Rusli, “User stories collection via interactive chatbot to support requirements gathering,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 18, no. 2, pp. 890–898, 2020.
V. A. H. Firdaus, P. Y. Saputra, and D. Suprianto, “Intelligence chatbot for Indonesian law on electronic information and transaction,” in IOP Conference Series: Materials Science and Engineering, 2020, vol. 830, no. 2, p. 22089.
K. T. Wirawan, I. M. Sukarsa, and I. P. A. Bayupati, “Balinese historian chatbot using full-text search and artificial intelligence markup language method,” Int. J. Intell. Syst. Appl., vol. 11, no. 8, p. 21, 2019.
I. W. Puspitasari, F. R. Rinawan, W. G. Purnama, H. Susiarno, and A. I. Susanti, “Development of a Chatbot for Pregnant Women on a Posyandu Application in Indonesia: From Qualitative Approach to Decision Tree Method,” in Informatics, 2022, vol. 9, no. 4, p. 88.
L. Hidayatin and F. Rahutomo, “Query expansion evaluation for chatbot application,” in 2018 International Conference on Applied Information Technology and Innovation (ICAITI), 2018, pp. 92–95.
Y. W. Chandra and S. Suyanto, “Indonesian chatbot of university admission using a question answering system based on sequence-to-sequence model,” Procedia Comput. Sci., vol. 157, pp. 367–374, 2019.
L. Manik et al., “Out-of-scope intent detection on a knowledge-based chatbot,” Int. J. Intell. Eng. Syst., vol. 14, no. 5, pp. 446–457, 2021.
L. Shang, Z. Lu, and H. Li, “Neural responding machine for short-text conversation,” arXiv Prepr. arXiv1503.02364, 2015.
C. Pricilla, D. P. Lestari, and D. Dharma, “Designing interaction for chatbot-based conversational commerce with user-centered design,” in 2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA), 2018, pp. 244–249.
Y. Windiatmoko, R. Rahmadi, and A. F. Hidayatullah, “Developing facebook chatbot based on deep learning using rasa framework for university enquiries,” in IOP conference series: materials science and engineering, 2021, vol. 1077, no. 1, p. 12060.
M. T. Anwar, “Automatic Complaints Categorization Using Random Forest and Gradient Boosting,” Adv. Sustain. Sci. Eng. Technol., vol. 3, no. 1, p. 210106, 2021.
E. Zuliarso, M. T. Anwar, K. Hadiono, and I. Chasanah, “Detecting Hoaxes in Indonesian News Using TF/TDM and K Nearest Neighbor,” in IOP Conference Series: Materials Science and Engineering, 2020, vol. 835, no. 1, p. 12036.
Y. HaCohen-Kerner, D. Miller, and Y. Yigal, “The influence of preprocessing on text classification using a bag-of-words representation,” PLoS One, vol. 15, no. 5, p. e0232525, 2020.
P. L. Rodriguez and A. Spirling, “Word embeddings: What works, what doesn’t, and how to tell the difference for applied research,” J. Polit., vol. 84, no. 1, pp. 101–115, 2022.
M. T. Anwar, L. Ambarwati, D. Agustin, and others, “Analyzing Public Opinion Based on Emotion Labeling Using Transformers,” in 2021 2nd International Conference on Innovative and Creative Information Technology (ICITech), 2021, pp. 74–78.
M. Ridha and K. Haura Maharani, “Implementation of Artificial Intelligence Chatbot in Optimizing Customer Service in Financial Technology Company PT. FinAccel Finance Indonesia,” Multidiscip. Digit. Publ. Inst. Proc., vol. 83, no. 1, p. 21, 2022.
X. Wang, X. Lin, and B. Shao, “How does artificial intelligence create business agility? Evidence from chatbots,” Int. J. Inf. Manage., vol. 66, p. 102535, 2022.
M. Chung, E. Ko, H. Joung, and S. J. Kim, “Chatbot e-service and customer satisfaction regarding luxury brands,” J. Bus. Res., vol. 117, pp. 587–595, 2020.
Y. Ruan and J. Mezei, “When do AI chatbots lead to higher customer satisfaction than human frontline employees in online shopping assistance? Considering product attribute type,” J. Retail. Consum. Serv., vol. 68, p. 103059, 2022.
A. Wiliam, S. Sasmoko, H. Prabowo, and others, “Analysis of e-service chatbot and satisfaction of banking customers in Indonesia,” Asia Proc. Soc. Sci., vol. 4, no. 3, pp. 72–75, 2019.
S. Bird, E. Klein, and E. Loper, Natural language processing with Python: analyzing text with the natural language toolkit. “ O’Reilly Media, Inc.,” 2009.
Martín~Abadi et al., “{TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems.” 2015. [Online]. Available: https://www.tensorflow.org/
F. Chollet and others, “Keras.” 2015.
M. Grinberg, Flask web development: developing web applications with python. “ O’Reilly Media, Inc.,” 2018.
R. Richad, V. Vivensius, S. Sfenrianto, and E. R. Kaburuan, “Analysis of factors influencing millennial’s technology acceptance of chatbot in the banking industry in Indonesia,” Int. J. Civ. Eng. Technol., vol. 10, no. 4, pp. 1270–1281, 2019.
L. Sanny, A. Susastra, C. Roberts, and R. Yusramdaleni, “The analysis of customer satisfaction factors which influence chatbot acceptance in Indonesia,” Manag. Sci. Lett., vol. 10, no. 6, pp. 1225–1232, 2020.
J. A. Mulyono and S. Sfenrianto, “Evaluation of customer satisfaction on Indonesian banking chatbot services during the COVID-19 pandemic,” CommIT (Communication Inf. Technol. J., vol. 16, no. 1, pp. 69–85, 2022.
M. T. Anwar, M. P. Utami, L. Ambarwati, and A. W. Arohman, “Identifying Social Media Conversation Topics Regarding Electric Vehicles in Indonesia Using Latent Dirichlet Allocation,” in 2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom), 2022, pp. 102–106.
J. Jedrzejowicz and M. Zakrzewska, “Text classification using LDA-W2V hybrid algorithm,” in Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent
Decision Technologies (KES-IDT 2019), Volume 1, 2020, pp. 227–237.
M. Xian-yan, C. Rong-yi, Z. Ya-hui, and Z. Zhenguo, “Multilingual short text classification based on LDA and BiLSTM-CNN neural network,” in Web Information Systems and Applications: 16th International Conference, WISA 2019, Qingdao, China, September 20-22, 2019, Proceedings 16, 2019, pp. 319–323.
M. L. Tedjopranoto, A. Wijaya, L. H. Santoso, and D. Suhartono, “Correcting typographical error and understanding user intention in Chatbot by combining N-gram and machine learning using schema matching technique,” Int. J. Mach. Learn. Comput., vol. 9, no. 4, pp. 471–476, 2019.
DOI: https://doi.org/10.26877/asset.v5i2.14891
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Advance Sustainable Science, Engineering and Technology (ASSET)
E-ISSN: 2715-4211
Published by Science and Technology Research Centre
Universitas PGRI Semarang, Indonesia
Website: http://journal.upgris.ac.id/index.php/asset/index
Email: asset@upgris.ac.id