Maze Runner game is a game that requires pathfinding algorithm to get to the destination with the shortest path. This algorithm is used in an NPC that will move from start node to destination node. However, the use of incorrect algorithms can affect the length of the computing process to find the shortest path. The longer the computing process, the longer the players have to wait. This study compared pathfinding algorithms A *, Dijkstra, and Breadth First Search (BFS) in the Maze Runner game. Comparison process of these algorithms was conducted by replacing the algorithm in the game by measuring the process time, the length of the path, and the numbers of block played in the existing computing process. The results of this study recommend which algorithm is suitable to be applied in Maze Runner Game.

This paper presents a tool wear monitoring methodology on the abrasive belt grinding process using vibration and force signatures on a convolutional neural network (CNN). A belt tool typically has a random orientation of abrasive grains and grit size variation for coarse or fine material removal. Degradation of the belt condition is a critical phenomenon that affects the workpiece quality during grinding. This work focuses on the identifation and the study of force and vibrational signals taken from sensors along an axis or combination of axes that carry important information of the contact conditions, i.e., belt wear. Three axes of the two sensors are aligned and labelled as X-axis (parallel to the direction of the tool during the abrasive process), Y-axis (perpendicular to the direction of the tool during the abrasive process) and Z-axis (parallel to the direction of the tool during the retract movement). The grinding process was performed using a customized abrasive belt grinder attached to a multi-axis robot on a mild-steel workpiece. The vibration and force signals along three axes (X, Y and Z) were acquired for four discrete sequential belt wear conditions: brand-new, 5-min cycle time, 15-min cycle time, and worn-out. The raw signals that correspond to the sensor measurement along the different axes were used to supervisedly train a 10-Layer CNN architecture to distinguish the belt wear states. Different possible combinations within the three axes of the sensors (X, Y, Z, XY, XZ, YZ and XYZ) were fed as inputs to the CNN model to sort the axis (or combination of axes) in the order of distinct representation of the belt wear state. The CNN classification results revealed that the combination of the XZ-axes and YZ-axes of the accelerometer sensor provides more accurate predictions than other combinations, indicating that the information from the Z-axis of the accelerometer is significant compared to the other two axes. In addition, the CNN accuracy of the XY-axes combination of dynamometer outperformed that of other combinations.

The purpose of this research is to visualize furniture objects from a catalogue using a markerless augmented reality tracking. Augmented reality is applied to help customers to envision an augmented object for learning the product knowledge of the furniture chosen. The markerless tracking method used in this research is a Simultaneous Localization and Mapping (SLAM), where a targeted surface of the floor for an augmented object can be determined in certain areas in the real world without using a marker. Testing was performed with parameters such as with a minimum of lighting intensity from without lighting, low lighting and bright lighting, a minimum of distance from 50 cm, 100 cm, and 150 cm, a minimum of height from 60 cm,120 cm,160 cm, and a minimum of angle from 30,50 and 70 degree of detection from the surface of the floor. The result of this research is the Simultaneous Localization and Mapping method is confirmed to be adequate for visualizing the 3D furniture model on targeted the surface of the floor without markers.

Information technology brings transformation from the physical world into the digital world. This transformation developed in various fields, especially games. In the past, games that are involving physical objects such as chess, cards, dominoes, and mahjong are popular for the publics. Card battle game is a game that pits strength between 2 cards. The game must have 2 players who will compete. However, if a player wants to practice before the match or wants to play alone, he needs Non Player Character (NPC). The NPC will be the opponent in card battle games. In order for NPCs to be able to fight players, a special algorithm is needed to make the NPCs compete with players. The algorithm that can be implemented into the NPC is the Min Max Algorithm. This algorithm is a responsive algorithm which can count every step of the player. The results of this study are expected to provide suitable opponents for players who want to practice or compete in Card Battle Game on their own.

Perancangan sistem merupakan strategi untuk memecahkan masalah dan mengembangkan solusi terbaik bagi suatu permasalahan tersebut. Tujuan dari penelitian ini adalah untuk merancang sebuah aplikasi dekstop yang dapat memberikan kemudahan bagi pengelola dalam mendapatkan informasi mengenai bonus dan layanan pada Steam Mobil dan Motor. Aplikasi ini dibangun menggunakan program NetBeans IDE 8.2 dan dibantu perangkat lunak Ms. Access 2016 sebagai pengolah database. Berdasarkan penelitian yang dilakukan dapat disimpulkan bahwa masih banyak Steam Mobil dan Motor yang belum memanfaatkan teknologi informasi yang berbasis jaringan dalam mengelola data dan informasi perusahaan. Selain itu belum ada peningkatan pengetahuan komputer pada setiap bagian sehingga pegawai lebih memilih menggunakan cara manual dalam melayani pengunjung dan anggota. Kata Kunci: sistem, database, steam