I.J. Intelligent Systems and Applications, 2019, 8, 21-34 Published Online August 2019 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijisa.2019.08.03 Balinese Historian Chatbot using Full-Text Search and Artificial Intelligence Markup Language Method

Kadek Teguh Wirawan Student, Departement of Information Technology, , , E-mail: [email protected]

I Made Sukarsa Lecturer, Departement of Information Technology, Udayana University, Bali, Indonesia E-mail: [email protected]

I Putu Agung Bayupati Lecturer, Departement of Information Technology, Udayana University, Bali, Indonesia E-mail: [email protected]

Received: 26 February 2019; Accepted: 19 March 2019; Published: 08 August 2019

Abstract—In the era of technology, various information expected to be obtained faster [1]. Various types of could be obtained quickly and easily. The information could be obtained relatively quick and easy is one of the information that could be obtained. Balinese today; one of them is information about the history of have known their history through Babad and stories Bali. Balinese had known their traditional history (Babad) which are told through generations. Babad is traditional- which generally talks about certain clan (Soroh) and is historical writing which tells important event that has decorated with mystical things. happened. As technology evolves, Balinese‘s interest in Babad is traditional-historical writing that tells studying their own history has been decreased. It is important event that has happened. In addition of Babad, caused by people interest in studying history books and the existence of history books of Bali could help to chronicles tend to decrease over time. Therefore, an increase knowledge into history that has ever existed in innovation of technology, which able to convert historical Bali; but in this modern era, Balinese‘s understanding of data from printed media to digital media, is needed. The its history is still lacking. technology that could be used is Chatbot technology; a The decreased understanding is caused by the lack of computer program that could carry out conversations. interest in learning about Balinese from Babad and other Chatbot technology is used to make people learning Bali historical-related books. Lontar expert and founder history easily by using Instant Messenger LINE as a of the Hanacaraka Society, Sugi Lanus, stated that most platform to communicate. This Chatbot uses two methods, Balinese had knowledge derived from Ancient Indian, but namely the Artificial Intelligence Markup Language many of them could not read lontar and do not method and the Full-Text Search method. The Artificial understand the meaning of Sanskrit. Lontar is traditional Intelligence Markup Language method is used as the writing with palm leaves as a medium containing mantra, process of making characteristic of questions and answers. tradition, or summary of important events. He also added The Full-Text Search method is the process of matching that the lontar in Bali that now still existed was not fully answers based on user input. This chatbot only uses explained because there were missing pages or the Indonesian to communicate. The results of this study are transfer of knowledge was inadequate and the language a Chatbot that could be accessed by using Instant itself is an obstacle. Asep Kembali, history and culture Messenger LINE and could communicate like historian observant, explained awareness level of Indonesian to expert. know and love their own history and culture have faded. There are many factors in society that caused this, such as Index Terms—Balinese History, Chatbot, Full-Text the attitude of individuals in knowing history and culture, Search, Artificial Intelligence Markup Language, Instant how to behave and how to respect and act on history itself. Messenger LINE. Based on these problems, an innovation that is able to convert historical data from printed media into digital media, that could be accessed anytime and anywhere, is I. INTRODUCTION needed. One new innovation to get information is Chatbot Information is an important part of life, which is technology. Chatbot technology is a form of Natural

Copyright © 2019 MECS I.J. Intelligent Systems and Applications, 2019, 8, 21-34 22 Balinese Historian Chatbot using Full-Text Search and Artificial Intelligence Markup Language Method

Language Processing application that studies provide relevant results. The MySQL database supports communication between human and computer through Full-Text Searching by using two functions, namely natural language. Chatbot will provide information about MATCH and AGAINST. Balinese history from ancient Bali to the time of Dutch Research conducted by Shah, Lahoti, and Lavanya [5] colonialism using LINE's instant messaging service. This built a Chatbot application by modeling the bot-making Chatbot uses two methods, namely the Artificial process in several stages. The first stage is creating a Intelligence Markup Language method and the Full-Text database of all knowledge about general education. The Search method. The Artificial Intelligence Markup second is making the same word cluster and frequently- Language method is used as the process of making used groups of words. The third is the use of Natural characteristic of questions and answers. The Full-Text Language Processing (NLP) to interpret inputs and Search method is the process of matching answers based respond to questions given. Inputs are processed with on user input. The results of this study are a Chatbot that simple steps such as dividing and sorting words and could be accessed by using Instant Messenger LINE and counting the number of searches for each word. The could communicate like historian expert. answer that is appropriate for the user is obtained by The paper is organized as follows. In section 2, related ranking and looking for the similarity of the score work is described. Section 3 describes the research between the word and dataset in the database with N- method by applying the system development life cycle Gram. After the answer is found, it will be given to the method. The SDLC method that is applied is the waterfall user. If the answer is less-expected than what the user model that starts from the study of literature, system wants, the bot could learn from the answers that have design, system implementation, trials, discussions and been modified by the user. This study concludes that the improvements. Section 4 describes the method use of NLP and self-learning techniques could be good implementation in detail and also analyzes how the additional features to make Chatbot technology more chatbot works from incoming messages to the answer human-like and also tend to provide promising results. search process. The analysis is done in 3 different Khanna [6] revealed that Artificial Intelligence (AI) scenarios with different messages that produce different could create machines that could simulate human answers. Finally, in section 5, the conclusions are drawn. intelligence. This study shows how the current approach to AI; one typical example of an AI system is Chatbot. Chatbot has a separate section that is in charge of II. RELATED WORKS managing the transfer and understanding of messages between users (humans) and the AI system, there are also Previous research related to the use of Chatbot as a parts that hold keys/points during discussions, and there communication medium and the use of the Full Text are parts in charge of handling errors. This research Search method and Artificial Intelligence Markup concludes that artificial intelligence could solve some of Language including Sam Goundar [2] revealed that the the main problems for humanity and artificial intelligence use of cellphones for accessing information would be will be integrated with everyday human life. more efficient and preferred for students, because Research conducted by Mhatre [7] applies web-based students would prefer accessing information from home Chatbots as personal assistants from users who could or place which they consider comfortable and do not need manage user meetings with their clients via email. This to go around only to find the desired information. This research makes a program that is able to extract incoming study concluded that the use of cell phones in the learning e-mails in the user's account automatically by matching process may provide convenience for students and giving several keywords from the e-mail content and subject. benefits to the school. Furthermore, the e-mail is read with the help of an Haller and Rebedea [3] built a Chatbot application algorithm such as pattern matching. The program will using a chat script. Chatscript uses rules or arrangement check it's user's schedule on a specific date and time from that contain labels, patterns, and outputs. The pattern is a Google Calendar. Pattern matching is done with the O- condition that is used to filter input or question given Program which is part of Artificial Intelligence Machine according to the template in the database and if the Learning (AIML) which could be used in the Hypertext question has been found then the next answer or output Preprocessor (PHP) programming language and uses the will be given in accordance with the knowledge that has MySQL database to store Chatbot information, including been implanted. The results achieved in this journal, the AIML files used to store responses from Chatbots. This chat script method used could work well by utilizing study concludes that by using the pattern matching patterns and knowledge from Wikipedia and DBpedia . algorithm, a system could act as a virtual personal Naem, Khalid and Hassan [4] revealed that Full-Text assistant who could plan user work and schedule Search has several functions, namely Natural Language meetings. Full Text Search, Boolean Full-Text Search, Full-Text Abushawar and Atwell [8] revealed that the pattern Search with Query Expansions, and others. The FTS matching process uses the Artificial Intelligence Markup algorithm consists of several steps, namely database Language method done by matching words per word to initialization, connecting databases that include get the most suitable pattern. This process is described in connecting strings with tables in the database, indexing the Graphmaster rule which consists of several categories FTS in tables and specifying indexes for FTS, and the and patterns. This research builds a Java-based latter matching text with the FTS index table so as to

Copyright © 2019 MECS I.J. Intelligent Systems and Applications, 2019, 8, 21-34 Balinese Historian Chatbot using Full-Text Search and Artificial Intelligence Markup Language Method 23

application that is able to form the AIML knowledge base making of Chatbot applications for media on academic automatically and is divided into 2 program versions. The information, staffing, student affairs and facilities at the first version is feature matching based on user input. This Faculty of Mathematics and Natural Sciences, Unlam process begins with reading the text from the corpus and Banjarbaru using the Artificial Intelligence Markup inserting it into a vector, then the pre-processing process Language (AIML) method. The purpose of this study is which consists of the tokenization process (word solving), to make it easier for users to find academic, staffing, the stopword or filtering process (eliminating words that student information and facilities available at the Faculty have no meaning) and stemming process (changing into of Mathematics and Natural Sciences, Lambung word form basic), then specify the word into the pattern Mangkurat University, Banjarbaru. The AIML method and template, and the last process is to save the pattern uses the template matching process, the process of and template results into the AIML file. The second determining answers based on certain characteristics that version is by making a more approach to the input from have been designed in the database. The design of the the user to get the most suitable answer. Modeling is template begins with determining the information needed, prepared to map all traits that have the same response into then formed into a question that is adjusted to the shape one form and transfer all repetition of features with of the pattern. different templates into one form with a list of different Suryani and Amalia [12] built an East Java tourist responses. attraction information Chatbot application using a Research conducted by Dole [9] implemented a web- website-based Artificial Intelligence Markup Language based Chatbot application that was used as an (AIML) method. This application aims to allow tourists information service for customer banks. The application to find out information about a tourist attraction in the uses the speech recognition method to convert voice input East Java area by asking questions and answers to the into a text form and the Artificial Intelligence Markup system. The application consists of two interfaces, the Language (AIML) method to determine the appropriate admin interface which is used by administrators to add answer. The process starts when the customer finishes and process AIML data, while the user interface is used giving questions through the microphone. The program by users to communicate with the system. Determining carries out the speech recognition process in accordance the answer is done by matching the input from the user with the input from the customer and turns it into text with the pattern in the database. form. The process is continued with feature matching Paliwahet [13] says that matching the Full-Text Search based on the stored on AIML. The program Boolean Mode is different from ordinary matching. gives an output in the form of