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Among many pathfinding algorithms, A* search algorithm is an algorithm that most commonly used in grid-based pathfinding. This is due to implementation of A* search which proven to be able to generate the optimal path in a relatively short time by combining two characteristics of Djikstra's and best-first search algorithm. In the implementation of A* search, the selection of heuristic function and data structure can affect the performance of the algorithm. The purpose of this research is to find the best heuristic function and data structure with regards of the performance in A* search implementation as a pathfinding algorithm in a 3D platform. In the experiment, some known heuristic functions and data structures will be tested on the various 3D platform with a different size and obstacle percentage. Based on experiment that have been done, euclidean squared distance is best heuristic function for 3D pathfinding problem, with regards of the implementation performance. In addition, we also found that binary heap is the best data structure to be implemented for 3D pathfinding problem, with regards of implementation performance.

Augmented Reality is a technology that can project objects from the virtual world to the real world. Augmented Reality continues to be developed so it can be easy to implement into various devices. However, the device must have a camera, VGA card, and the ability to process data that is high enough to be able to process and projecting graphical data that captured by the camera and displayed to the screen. Marker-based Augmented Reality is still better than Markerless Augmented Reality due to several issues such as disturbances in the geomagnetic sensor that is used to map the Y axis and Z device that belongs to the user.

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The problem of Indonesian language errors among students is of particular observation. This problem becomes an important concern for students majoring in journalism because one day the graduates will become journalists. A language error filtering application has been developed that can be used quickly and accurately in journalists’ work. This application, which involves statistical analysis, computational language, and artificial intelligence, is named U-Tapis. This study was aimed at finding out the feasibility and effectiveness measures of the U-Tapis model by focusing on the language of students’ journalistic works such as opinions, news items, and news articles. The study involved 30 students majoring in Journalism, a private university in Jakarta, Indonesia. It was found that the students’ error rate decreased after the use of the model. It can be concluded that, in addition to eligibility which reaches 92.31%, the U-Tapis application can help effectively increase students’ proficiency in the use of the Indonesian language.