Implementasi Deep Feed-Forward Neural Network pada Perancangan Chatbot Berbasis Web di UPPIK RSUD M. YUNUS
DOI:
https://doi.org/10.34010/komputika.v12i2.8914Abstract
ABSTRACT – The UPPIK (Customer Information and Counseling Complaint Unit) at the M. Yunus Hospital has an important role in serving visitors who come to the hospital. However, visitors often complain about the UPPIK service due to limited working hours, so there is not always staff available to provide the information needed by visitors. In addition, the ongoing Covid-19 pandemic requires people to maintain distance and reduce interaction with others. To solve this problem, an automatic chatbot has been developed to provide service as if the visitor is speaking directly to the staff without any time constraints. This research uses a Deep Feed-Forward Neural Network algorithm. The dataset used is a collection of question-answer data collected through direct observation at the UPPIK, consisting of 1464 pairs of data. The best accuracy was obtained by spliting the dataset into 80% training data (1,185 data), 10% testing data (147 data), and 10% validation data (132 data) with 300 epochs, which resulted in an accuracy of 91.98%. Evaluation of these results showed a precision value of 0.99, a recall value of 0.98, and an f1-score of 0.99.
Keywords - UPPIK RSUD M. Yunus Bengkulu; Artificial Intelligence; Chatbot; Deep Feed-Forward Neural Network; Deep Learning
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