Web-Based Chatbot Development and User Satisfaction Analysis Using the Naive Bayes Method Through Online Questionnaires

Nurholis; Willy Prihartono; Fathurrohman

doi:10.59934/jaiea.v4i2.823

Authors

Nurholis STMIK IKMI Cirebon
Willy Prihartono STMIK IKMI Cirebon
Fathurrohman STMIK IKMI Cirebon

DOI:

https://doi.org/10.59934/jaiea.v4i2.823

Keywords:

Web-Based Chatbot, Natural Language Processing, Naive Bayes, User Satisfaction, Sentiment Analysis, TF-IDF

Abstract

This study aims to develop a web-based chatbot using Natural Language Processing (NLP) technology and the Naive Bayes algorithm to enhance digital interaction quality. User satisfaction was evaluated through an online survey involving 202 university students, focusing on ease of use, response speed, and relevance. The research followed the CRISP-DM framework, including data preprocessing (case folding, tokenization, stopword removal, and stemming), text transformation using the TF-IDF method, and implementation of a Naive Bayes classification model. an F1-score of 84%. Sentiment analysis revealed predominantly positive feedback, reflecting user satisfaction with the chatbot’s ease of use and response accuracy. However, some limitations, such as insufficient contextual understanding, were identified. These findings provide valuable insights into NLP-based chatbot development to support effective digital interactions. The proposed chatbot demonstrates potential applications in customer service, education, and e-commerce, with future improvements suggested to enhance contextual comprehension and scalability.

Downloads

Download data is not yet available.

References

R. Nur Aziza et al., “Pembangunan Aplikasi dan Klasifikasi Pertanyaan Chatbot Informasi Akademik Menggunakan Metode Cosine Similarity dan Naïve Bayes,” vol. 12, no. 2, pp. 169–179, 2024, [Online]. Available: https://doi.org/10.33322/kilat.v12i2.1921

R. A. Sekarwati, A. Sururi, R. Rakhmat, M. Arifin, and A. Wibowo, “Survei Metode Pengujian Chatbot pada Media Sosial untuk Mengukur Tingkat Akurasi,” Sisfotenika, vol. 11, no. 2, p. 172, 2021.

M. Muliyono and S. Sumijan, “Identifikasi Chatbot dalam Meningkatkan Pelayanan Online Menggunakan Metode Natural Language Processing,” Jurnal Informatika Ekonomi Bisnis, vol. 3, pp. 142–147, 2021, doi: 10.37034/infeb.v3i4.102.

Y. Christian and M. Erline, “Web-Based Chatbot With Natural Language Processing and Knuth-Morris-Pratt (Case Study: Universitas Internasional Batam),” JST (Jurnal Sains dan Teknologi), vol. 11, no. 1, pp. 132–141, 2022, doi: 10.23887/jstundiksha.v11i1.43258.

A. L. Maitri and J. Sutopo, “Rancangan Bangun Chatbot Sebagai Pusat Informasi Lembaga Kursus Dan Pelatihan Menggunakan Pendekatan Natural Language Processing,” Eprints.Uty.Ac.Id, pp. 1–9, 2019, [Online]. Available: http://eprints.uty.ac.id/

D. Apriliani, S. F. Handayani, and I. T. Saputra, “Implementasi Natural Language Processing (NLP) Dalam Pengembangan Aplikasi Chatbot Pada SMK YPE Nusantara Slawi,” Techno.Com, vol. 22, no. 4, pp. 1037–1047, 2023, doi: 10.33633/tc.v22i4.9155.

Y. Yunefri, Y. E. Fadrial, and S. Sutejo, “Chatbot Pada Smart Cooperative Oriented Problem Menggunakan Natural Language Processing dan Naive Bayes Classifier,” INTECOMS: Journal of Information Technology and Computer Science, vol. 4, no. 2, pp. 131–140, 2021, doi: 10.31539/intecoms.v4i2.2704.

C. Diantoni, R. Mufidah, and H. Triana, “Membangun Chatbot Untuk Informasi Magang Dan Studi Independen Kampus Merdeka Dengan Algoritma Naive Bayes,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 8, no. 2, pp. 1389–1397, 2024, doi: 10.36040/jati.v8i2.8962.

Pardede, A. M. H. (2018). Perancangan Sistem Pakar Diagnosa Penyakit Tanaman Kelapa Sawit Dengan Metode Bayes Study Kasus PT. Ukindo Blankahan Estate.

Abdullah, D., Zarlis, M., Pardede, A. M. H., Anum, A., Suryani, R., Parwito, ... & Setiyadi, D. (2019, November). Expert System Diagnosing Disease of Honey Guava Using Bayes Method. In Journal of Physics: Conference Series (Vol. 1361, No. 1, p. 012054). IOP Publishing.

Sawitri, S., Simanjuntak, M., & Pardede, A. M. H. (2024). APPLICATION OF NAIVE BAYES METHOD TO DIAGNOSE FMD DISEASE IN GOATS. Journal of Mathematics and Technology (MATECH), 3(2), 103-111.

Lestari, S. A. M., Pardede, A. M., & Simanjuntak, M. (2024). Prediksi Disleksia pada Anak menggunakan Metode Naive Bayes. Jurnal Kajian dan Penelitian Umum, 2(5), 37-51.