Balinese script writing, as one of Balinese cultural richness, is going to extinct because of its decreasing use. This research is a way to preserve it through collaboration between Computer Science and Language discipline, that focused on accuracy comparison of Latin-to-Balinese script transliteration method on mobile application as a ubiquitous learning media. From few research in this area, there are only two existing methods to be compared, i.e. each on Android mobile application that were called Belajar Aksara Bali (BAB), and Transliterasi Aksara Bali (TAB). The comparison was based on The Balinese Alphabet writing rules and examples document by Sudewa. Through the experiment, TAB has outperformed BAB since TAB has passed over 68% (103 of 151) cases, while BAB has passed over only 39% (59 of 151) cases. This research contributes on a comprehensive accuracy comparison analysis of Latin-to-Balinese script transliteration method, specifically on mobile application, since there is no such study. This research also contributes on those methods improvement possibility. In the future, this research can be used as a reference for improvement of any Latin-to-Balinese script transliteration method by taking care on thirteen kind of special words that were found during this comparison study.

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Balinese script writing, as one of Balinese cultural richness, is going to extinct because of its decreasing use. This research is one of the ways to preserve Balinese script writing using technological approach. Through collaboration between Computer Science and Balinese Language discipline, this research focused on the development of a Latin-to-Balinese script transliteration robotic system that was called LBtrans-Bot. LBtrans-Bot can be used as a learning system to give the transliteration knowledge as one aspect of Balinese script writing. In this research area, LBtrans-Bot was known as the first system that utilize Noto Sans Balinese font and was developed based on the identified seventeen kinds of special word. LBtrans-Bot consists of the transliterator web application, the transceiver console application, and the robotic arm with its GUI controller application. The transliterator used the Model-View-Controller architectural pattern, where each of them was implemented by using MySQL database (as the repository for the words belong to the seventeen kinds of special word), HTML, PHP, CSS, and Bootstrap (mostly for the User Interface responsive design), and JavaScript (mostly for the transliteration algorithm and as the controller between the Model and the View). <em>Dictionary</em> data structure was used in the transliterator memory as a place to hold data (words) from the Model. The transceiver used batch script and AutoIt script to receive and trasmit data from the transliterator to the GUI controller, which control the Balinese script writing of the robotic arm. The robotic arm with its GUI controller used open-source mDrawBot Arduino Robot Building platform. Through the experiment, LBtrans-Bot has been able to write the 34-pixel font size of the Noto Sans Balinese font from HTML 5 canvas that has been setup with additional 10-pixel length of the width and the height of the Balinese script writing area. Its transliterator gave the accuracy result up to 91% (138 of 151) testing cases of The Balinese Alphabet writing rules and examples document by Sudewa. This transliterator result outperformed the best result of the known existing transliterator based on Bali Simbar font, i.e. Transliterasi Aksara Bali, that only has accuracy up to 68% (103 of 151) cases of the same testing document. In the future work, LBtrans-Bot could be improved by: 1) Accommodating more complex Balinese script with trade off to the limited writing area of robotic system; 2) Enhancing its transliterator to accommodating the rules and/or examples from the testing document that recently cannot be handled or gave incorrect transliteration result; enriching the database consists of words belong to the seventeen kinds of special word; and implementing semantic relation transliteration.

As part of the Balinese culture in Indonesia, the Balinese script has rarely been used today. Its Balinese-to-Latin script transliteration knowledge is also affected by that condition and has caused concern over the threat of extinction. This study is aimed to preserve that knowledge through a technological approach by collaboration between Information Technology and Balinese Language discipline. This research analyzed the ubiquitous learning aspect of Balinese-to-Latin script transliteration as part of Balinese Language education, which is a mandatory local subject from basic to high school in Bali Province. This analysis was conducted on the Balinese Glyph Recognition (BalineseGR) web application that was developed as a technology product of Universitas Pendidikan Ganesha (Undiksha), Indonesia. Balinese is a sort of Optical Character Recognition (OCR) web application that receives a Balinese script image and outputs Latin text. It was considered as the first Balinese-to-Latin script transliteration web application using JavaScript for the algorithm. Recently, its initial development has covered transliteration knowledge of eighteen Balinese script's basic syllables (Akśara Wreşāstra) only. Since ubiquitous learning is supported by mobile computer through a wireless network, and it is aimed to provide learners with content and interaction anytime and anywhere, BalineseGR web application has several aspects to concern about (1) its counterpart mobile application development where image input not only from a file but also more useful directly from a camera, and (2) richer knowledge content, including a transliteration of the vowels (Akśara Suara), additional basic syllables (Akśara Şwalalita), sound killers (Pangangge Tengenan), numerals, punctuations, ligatures, and miscellaneous glyph.

Balinese script is a part of Balinese culture which is feared to be extinct due to the decrease in its use. This research is one of the efforts to preserve Balinese Script using technology, which focuses on the error analysis of Latin-to-Balinese script transliteration method based on Noto Sans Balinese font. This analysis can be used as a reference for the future improvement to make this method more robust. This research used accuracy testing method to test compatibility result of transliteration produced by the application with 27,506 words contained in the Balinese Language Dictionary. This experiment result shows the accuracy of the application is 54.5%. After the addition of special word and correction on the application algorithm, the result changed to 94%. There is still 6% of other incorrect transliteration because of the various case, related to a word has several different meanings (so different Balinese scripts), and related to the affixed word. In the future work, these 6% incorrect transliteration need to be accommodated to make the recent method more robust.

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This study aims to describe (1) type of numbers in old Balinese, and (2) type of numbers in new Balinese. The subject of this study is the ancient Balinese inscription while the object is the numbers. The documentation method is used in order to collect the data. Then, the data analysis uses several techniques such as, data identification, data reduction, data classification, and data summarization. The result of this study was found that (1) type of the numbers in the old Balinese such as distributive numbers, collective numbers, indefinite distributive numbers, klitik numbers, measurement numbers, and fractional numbers, and (2) type of numbers in New Balinese which based on the same meanings, such as the equivalent forms, the similar forms, and the different forms.

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