SIBI in Indonesian known as standard of Indonesian sign language. To help deaf people Myo Armband becomes an immersive technology for communication each other. The problem on Myo sensor is unstable clock rate. It causes different length data for the same period even on the same gesture. This paper proposes Moment Invariant Method to extract the feature of sensor data from Myo. This method reduces the amount of data as the result is same length of data. The implementation of this method is the user-dependent feature according to the characteristics of Myo Armband. We tested for gesture of alphabet A to Z based on SIBI (Indonesian Sign Language) with static and dynamic movements. There are 26 classes of alphabet and 10 variants. We use min-max normalization for guarantying the range of data and K-Nearest Neighbor method to classify dataset. Performance analysis with leave-one-out-validation method produced an accuracy of 82.31%.
The quick response (QR) code provides a fast, easy, convenient, accurate and automatic method of transporting data. By freeing applications and popularizing wireless communications and cellular technology, two-dimensional barcode technology has been used for production, logistics, and sales. To order the benefits of technology to the service sector, for this study, we used various QR code applications in the food or beverage menu service management system in restaurants / cafes. The specific purpose is to allow restaurant waiters to quickly and appropriately provide service to restaurant / cafe customers. Experimental results show that the method developed in this study can significantly improve the service menu, prepare waiters and chefs to provide the right service, shorten the time for ordering the menu, and facilitate the resolution of the problem. Research in actual circumstances will be a full support tool for restaurant / cafe menu services. The results of the test prove agreeing from the point of view of efficiency and cost savings, the new system is fast and efficient, improving very competitive with the release of an improved management system.
The rejection on ratification of the revision of Indonesian Code Law or known as RKUHP and Corruption Law raises several opinions from various perspectives in social media. Twitter as one of many platforms affected, has more than 19.5 million users in Indonesia. Twitter is one of many social media in Indonesia where people can share their views, arguments, information, and opinions from all points of view. Since Twitter has a great diversity of users, it needs a system which is designed to determine the opinion tendency towards the problems or objects. The purpose of this study is to analyze the sentiment of Twitter users' tweets to reject the revision of the Law whether they have positive or negative sentiments using the Agglomerative Hierarchical Clustering method. The data that being used in this study were obtained from the results of crawling tweets based on hashtag (#) (#ReformasiDikorupsi). The next stage is pre-processing which consists of case folding, tokenizing, cleansing, sanitizing, and stemming. The extraction features Opinion words and Term Frequency (TF) which performs the process automatically. In the clustering stage, two clusters use three approaches; single linkage, complete linkage and average linkage. In the accuracy calculation phase, the writer uses the error ratio, confusion matrix, and silhouette coefficient. Therefore, the results are quite good. From 2408 tweets, the highest accuracy results are 61.6%.
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