Resmana Lim
Petra Christian University

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Journal : Perfecting a Video Game with Game Metrics

Indoor positioning system using BLE beacon to improve knowledge about museum visitors Andreas Handojo; Tanti Octavia; Resmana Lim; Jonathan Kurnia Anggita
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14886


Generally, a museum has many locations and artifacts collection that display for visitors. Museum manager often have difficulty in obtaining information on visitors behavior such as, is there are particular locations/artifacts in the museum that are frequently/rarely visit by museum visitors, how long visitors spend their time in particular locations/artifacts, etc. The purpose of this study is try to build a suitable system in order to improve knowledge about the behavior of museum visitors by identifying the position of visitors in the museum. This study uses Bluetooth Low Energy (BLE) Beacon that place around the museum. The visitor mobile phone will detect BLE beacon signal, then the mobile phone application will calculated the visitor’s mobile phone position using the signal strength from the BLE beacons that are detected. The application then sends it to the computer server to display it in as museum visitor heat map. From this information, the museum manager could find out the visitors behavior movement and know which areas/artifacts that frequently/rarely visit by museum visitors. According to distance error testing which compare real location and position of the calculation, it is show that the average of distance error is around 140 cm. So, it can be concluded that the information obtained is sufficient enough to represent the position of museum visitors.
Adaptive Background Extraction for Video Based Traffic Counter Application Using Gaussian Mixture Models Algorithm Raymond Sutjiadi; Endang Setyati; Resmana Lim
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 3: September 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i3.1772


The big cities in the world always face the traffic jam. This problem is caused by the increasing number of vehicle from time to time and the increase of vehicle is not anticipated with the development of new road section that is adequate. One important aspect in the traffic management concept is the need of traffic density data of every road section. Therefore, the purpose of this paper is to analyze the possibility of optimization on the use of video file recorded from CCTV camera for the visual observation and the tool for counting traffic density. The used method in this paper is adaptive background extraction with Gaussian Mixture Models algorithm. It is expected to be the alternative solution to get the data of traffic density with a quite adequate accuracy as one of aspects for decision making process in the traffic engineering