Application of Natural Language Processing Using Cosine-Similarity Algorithm in Making Chatbot Information on the New Capital City of the Republic of Indonesia

H. T. Y. Achsan, D. Kurniawan, Diki Gita Purnama, Quintin Kurnia Dikara Barcah, Yuri Yusyana Astoria
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Abstract

The new capital city (IKN) of the Republic of Indonesia has been ratified and inaugurated by President Joko Widodo since January 2022. Unfortunately, there are still many Indonesian citizens who do not understand all the information regarding the determination of the new capital city. Even though the Indonesian Government has created an official website regarding the new capital city (www.ikn.go.id) the information is still not optimal because web page visitors are still unable to interact actively with the required information. Therefore, the development of the Chatting Robot (Chatbot) application is deemed necessary to become an interactive component in obtaining information needed by users related to new capital city. In this study, a chatbot application was developed by applying Natural Language Processing (NLP) using the Term Frequency-Inverse Document Frequency (TF-IDF) method for term weighting and the Cosine-Similarity algorithm to calculate the similarity of the questions asked by the user. The research successfully designed and developed a chatbot application using the Cosine-Similarity algorithm. The testing phase of the chatbot model uses several scenarios related to the points of NLP implementation. The test results show that all scenarios of questions asked can be responded well by the chatbot.
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余弦相似度算法自然语言处理在印尼共和国新首都聊天机器人信息制作中的应用
印度尼西亚共和国的新首都(IKN)已于2022年1月由总统佐科·维多多(Joko Widodo)批准并揭幕。不幸的是,仍有许多印尼公民不了解有关确定新首都的所有信息。尽管印尼政府已经建立了一个关于新首都的官方网站(www.ikn.go.id),但信息仍然不是最理想的,因为网页访问者仍然无法积极地与所需的信息互动。因此,开发聊天机器人(Chatbot)应用程序是必要的,它可以成为用户获取新首都相关信息的交互组件。在本研究中,应用自然语言处理(NLP)开发了一个聊天机器人应用程序,使用术语频率-逆文档频率(TF-IDF)方法进行术语加权,并使用余弦相似度算法计算用户提出的问题的相似度。本研究成功地设计并开发了一个基于余弦相似度算法的聊天机器人应用。聊天机器人模型的测试阶段使用了与NLP实现点相关的几个场景。测试结果表明,该聊天机器人可以很好地响应所有场景的提问。
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