Implementation of Chatbot for Merdeka Belajar Kampus Merdeka Program using Long Short-Term Memory

Muhammad Rahaji Jhaerol; Sudianto Sudianto

doi:10.23887/janapati.v12i2.58794

Authors

Muhammad Rahaji Jhaerol Institut Teknologi Telkom Purwokerto
Sudianto Sudianto Institut Teknologi Telkom Purwokerto

DOI:

https://doi.org/10.23887/janapati.v12i2.58794

Keywords:

academic services, ai-chatbot, Deep Learning, LSTM, MBKM

Abstract

Good service can help the organization improve efficiency and effectiveness in operations. Optimal service can also improve the customer experience and provide added value to an organization that provides services. One of the services that can be optimized is the Merdeka Belajar Kampus Merdeka (MBKM) program which is a learning program organized by the Ministry of Education, Culture, Research, and Technology (Kemendikbudristek), especially MBKM services at the Institut Teknologi Telkom Purwokerto (ITTP). The problem is that the MBKM service at ITTP is not optimal due to inaccessibility to anyone and so many programs available. Thus, resulting in not optimal services provided. Therefore, this study aims to implement a Chatbot service in the MBKM program at ITTP. The method used in building a Chatbot service is the Deep Learning Long Short-Term Memory (LSTM) algorithm. LSTM is a type of artificial neural network architecture that matches text data. The results show an accuracy score of 100% and a loss of 0.121%. Meanwhile, the results of the further evaluation are in the form of average weights consisting of precision, recall, and F1-score, respectively of 100%, 100%, and 100%.

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