Implementasi Chatbot Berbasis Aturan untuk Layanan Customer Service E-commerce pada Platform WhatsApp
Abstract
The high intensity of repetitive questions regarding product information, order status, and store policies in e-commerce businesses creates an additional workload for customer service and delays responses to customers. This research aims to implement a rule-based chatbot on the WhatsApp platform to automate customer service. The method used is the Waterfall software engineering model with stages of needs analysis, design, implementation, testing, and evaluation. The chatbot was implemented using Python integrated with WhatsApp Business API utilizing quick reply features. Functional testing results on 100 question samples show 87% accuracy. Usability testing using the System Usability Scale (SUS) on 30 users yielded a score of 78.5 (category "Good"). These results indicate that the proposed solution is effective in handling routine inquiries and can reduce customer service operational burden by 40% based on response time measurements. The main limitation lies in handling complex questions that require real-time data checking from external inventory systems.
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References
WhatsApp Business Platform Documentation, “WhatsApp Business,” 2022. Accessed: Sep. 27, 2025. [Online]. Available: https://business.whatsapp.com/blog/live-chat-customer-service-guide
D. S. Dewi, “Penerapan Algoritma Stemming Sastrawi Dan Cosine Similarity Pada Information Retrieval,” Repositori UIN Jakarta, 2022
S. Borsci and M. Schmettow, “Re-examining the chatBot Usability Scale (BUS-11) to assess user experience with customer relationship management chatbots,” Pers Ubiquitous Comput, vol. 28, no. 6, pp. 1033–1044, Dec. 2024, doi: 10.1007/s00779-024-01834-4.
G. Cameron et al., “Assessing the Usability of a Chatbot for Mental Health Care,” pp. 1–12, 2020, doi: 10.1007/978-3.
A. Kurniawan, A. Abdiansah, and A. S. Utami, “NL2SQL for Chatbot with Semantic Parsing Using Rule-Based Methods Chatbot Natural Language to Structured Query Language NL2SQL Rule Base,” Sriwijaya Journal of Informatic and Applications, vol. 5, no. 1, pp. 39–48, 2024, Accessed: Sep. 27, 2025. [Online]. Available: http://sjia.ejournal.unsri.ac.id
M. S. Ibrahim, J. A. Eleiwy, H. M. Muhi-Aldeen, Y. Al-Yasiri, and A. A. Nafea, “Human to Chatbot Text Classification Using Multi-Source AI Chatbots and Machine Learning Models,” Journal of Intelligent Systems and Internet of Things, vol. 16, no. 1, pp. 152–165, 2025, doi: 10.54216/JISIoT.160113.
J. Pardede and D. Darmawan, “Perbandingan Algoritma Stemming Porter, Sastrawi, Idris, Dan Arifin & Setiono Pada Dokumen Teks Bahasa Indonesia,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 12, no. 1, pp. 69–76, 2025, doi: 10.25126/jtiik.2025128860.
H. Bahak, F. Taheri, Z. Zojaji, and A. Kazemi, “Evaluating ChatGPT as a Question Answering System: A Comprehensive Analysis and Comparison with Existing Models,” Arxiv, Dec. 2023, Accessed: Sep. 27, 2025. [Online]. Available: http://arxiv.org/abs/2312.07592
K. H. TEO and M. J. AHMAD KHIRI, “FCSIT WhatsApp Chatbot,” Trends in Undergraduate Research, vol. 4, no. 1, pp. c41-51, Jun. 2021, doi: 10.33736/tur.2866.2021.
E. Nichifor, A. Trifan, and E. M. Nechifor, “Artificial Intelligence in Electronic Commerce: Basic Chatbots and the Consumer Journey,” Amfiteatru Economic, vol. 23, no. 56, pp. 87–101, 2021, doi: 10.24818/EA/2021/56/87.
K. T. Wirawan, I. M. Sukarsa, and I. P. A. Bayupati, “Balinese Historian Chatbot using Full-Text Search and Artificial Intelligence Markup Language Method,” International Journal of Intelligent Systems and Applications, vol. 11, no. 8, pp. 21–34, Aug. 2020, doi: 10.5815/ijisa.2019.08.03.
S. Gupta, R. Ranjan, S. Narayan Singh, and B. Sindri, “Comprehensive Framework for Evaluating Conversational AI Chatbots,” Arxiv, 2024. Accessed: Sep. 27, 2025. [Online]. Available: https://arxiv.org/pdf/2502.06105.pdf
I. Suasnawa, I. Wiratama, I. Sudiartha, I. Caturbawa, A. Sapteka, and I. Indrayana, “Chatbot-Based Student Information Service in Indonesian Language,” INSTICC, Dec. 2023, pp. 223–227. doi: 10.5220/0011753800003575.
D. Mustikasari, I. Widaningrum, R. Arifin, W. Henggal, and E. Putri, “Comparison of Effectiveness of Stemming Algorithms in Indonesian Documents,” Advances in Engineering Research, August, 2021, doi: 10.2991/aer.k.210810.025
S. K. Adabala, “The Evolution of Chatbots from Simple Scripts to AI-Powered Assistants,” Journal of Artificial Intelligence, Machine Learning and Data Science, vol. 3, no. 1, pp. 2224–2229, Jan. 2025, doi: 10.51219/jaimld/sai-krishna-adabala/487.
WhatsApp Business Platform Documentation, “A Comprehensive Guide On WhatsApp API For Customer Support,” 2020. Accessed: Sep. 27, 2025. [Online]. Available: https://www.gupshup.ai/resources/wp-content/uploads/2022/03/A_Comprehensive_Guide_On_WhatsApp_API_For_Customer_Support.pdf?x19052&utm_source=chatgpt.com
O. Singh, J. Anthal, D. Yadav, and K. Mourya, “Studying Rule-Based and Self-Learning Chatbots: A Comprehensive Literature Review,” International Journal of Scientific Research and Engineering Development, vol. 8, no. 1, pp. 1654–1657, 2025, Accessed: Sep. 27, 2025
X. Liang et al., “Chatbot-Delivered Stage of Change–Tailored Web-Based Intervention to Promote Physical Activity Among Inactive Community-Dwelling People Aged 65 years or More: Protocol for a Randomized Controlled Trial,” JMIR Res Protoc, vol. 14, pp. 1–14, 2025, doi: 10.2196/68796.
A. Hidayat, A. Nugroho, and S. Nurfaizin, “Usability Evaluation on Educational Chatbot Using the System Usability Scale (SUS),” in 2022 7th International Conference on Informatics and Computing, ICIC 2022, Institute of Electrical and Electronics Engineers Inc., 2022. doi: 10.1109/ICIC56845.2022.10006991.
E. Kusumaningtyas, E. Laurentino, and A. Barakbah, “Responsive Chatbot Using Named Entity Recognition and Cosine Similarity,” INSTICC, Dec. 2023, pp. 239–245. doi: 10.5220/0011756300003575.
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