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Implementation of Marker Image Based Tracking Dental Care and Tooth Type "GG-Q" Based on Augmented Reality Markarius Paso; Reza Andrea; Suswanto Suswanto
TEPIAN Vol 1 No 4 (2020): December 2020
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v1i4.221

Abstract

Augmented Reality (AR) is a technology that allows people to visualize the virtual world as part of the real world. In simple terms AR can be defined as a real environment that is added with virtual objects, this is made possible through certain input devices. Learning media is a tool used in supporting the implementation of the teaching and learning process. In this process, it can be carried out using books or media electronics. One of them is using electronic media in the form of smart phones. In implementing it is applied to the treatment and type of teeth. The types of teeth used are incisors, canines, molars and molars . There are also cavities, tooth structure and dental care . The method used in this research is Marker based tracking. Marker based tracking is a type of Augmented Reality that recognizes a marker and identifies it to add a virtual object to the real environment.
Android-Based Geographic Information System Tourism of Samarinda City Aca Al Ahwa; Suswanto Suswanto; F. V. Astrolabe Sian Prasetya
Journal of Geomatics Engineering, Technology, and Sciences Vol. 1 No. 1 (2022): September 2022
Publisher : P3KM Politani Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/gets.v1i1.11

Abstract

This research is motivated by the tourism potential of Samarinda which is actually very good, but this potential has not been fully utilized by the city government and the private sector. So that people are less interested in traveling in Samarinda. Therefore, the purpose of this research is to build an android-based regional tourism information system for Samarinda City as a source of information to find out what tourist objects are owned by Samarinda City. This study uses spatial data in the form of location coordinates, addresses and non-spatial data as well as supporting information in the form of tourist names, categories, types of tours, addresses. Making this Android-Based Samarinda City Tourism Geographic Information System using Google Maps as a base map. The results of this study are to simplify data management for the general public, the test results of 60% of respondents answered agree, 34% of people answered strongly agree, 4% of people answered less agree, 2% of people answered disagree, 0% of people answered strongly disagree, and the results of the validation test using Pearson's product moment correlation model using SPSS with the number of rcount>rtable all valid data.
Android-Based Geographic Information System Tourism of Samarinda City Aca Al Ahwa; Suswanto Suswanto; F. V. Astrolabe Sian Prasetya
Journal of Geomatics Engineering, Technology, and Science Vol. 1 No. 1 (2022): September 2022
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/gets.v1i1.11

Abstract

This research is motivated by the tourism potential of Samarinda which is actually very good, but this potential has not been fully utilized by the city government and the private sector. So that people are less interested in traveling in Samarinda. Therefore, the purpose of this research is to build an android-based regional tourism information system for Samarinda City as a source of information to find out what tourist objects are owned by Samarinda City. This study uses spatial data in the form of location coordinates, addresses and non-spatial data as well as supporting information in the form of tourist names, categories, types of tours, addresses. Making this Android-Based Samarinda City Tourism Geographic Information System using Google Maps as a base map. The results of this study are to simplify data management for the general public, the test results of 60% of respondents answered agree, 34% of people answered strongly agree, 4% of people answered less agree, 2% of people answered disagree, 0% of people answered strongly disagree, and the results of the validation test using Pearson's product moment correlation model using SPSS with the number of rcount>rtable all valid data.