Chatbot untuk Website Utama UK Petra dengan Hidden Markov Model dan k-Nearest Neighbor untuk Generate Jawaban - Kevin Koesoemo; Alexander Setiawan; Indar Sugiarto (Jurnal Infra, 2021)
Petra Christian University has various services for general information about university majors and student admissions, such as social media and WhatsApp. However, these services still limited by number and working time of operators as human. Therefore, with this chatbot, information about PCU can be found anytime. Chatbot Study by S. C. P & Afrianto needs method to match chatbot question with the dataset. This thesis uses two methods, namely kNN (k-Nearest Neighbor) and HMM (Hidden Markov Model) to solve these problem. In this chatbot, it will try to combine and compare these two methods, and see if it can produces answers that can be understood and in accordance with various difficulty questions given. The kNN is used as a classification for questions given to chatbot which approximately match with questions on the chatbot’s knowledge base. HMM is used to assemble answer words from the selected knowledge base. Chatbot’s answers will be tested in terms of validity of the answers by two respondents (Public Relation and Admission staff) also the length of time it takes to produce answers. The results of the chatbot with kNN has an accuracy of 64.44% (45 questions), with average system runtime of 0.08 seconds. While the results of chatbot with kNN-HMM produces random and irregular answers, with average system runtime of 0.12 seconds, cause by HMM which is a probability based method.