Hadi, Ahmad (2024) Pengenalan Hewan Berdasarkan Teknologi Reproduksi Hewan Menggunakan Augmented Reality. Other thesis, Universitas Islam Riau.
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Abstract
The introduction of animal breeding technology at school is carried out using the presentation method of group activities and exercises on the material provided, causing students to feel that they do not understand and are lazy in learning. There is a need for different alternatives to help students understand the concept of introducing animal breeding technology, so that it can increase students' interest in understanding the learning concept. There is an application that is able to describe certain simulations, namely Augmented Reality (AR). AR is used as an interactive medium in the learning process, it is hoped that it can increase students' interest in learning. This application creates 3D objects using Blender, the user interface uses Unity, the augmented reality library uses ARCore SDK, and 3D object tracking uses markerless techniques. AR technology can combine virtual objects into a threedimensional real environment. In displaying 3D objects, the application can be used optimally in tracking object areas with a minimum distance of 5 cm, as well as tracking object areas that have texture or color, and have a light intensity of at least 16 lux. After user testing of the application, a score of 92.86% was obtained that the animal recognition application based on animal reproduction technology using augmented reality could be implemented well. By creating this application, students' interest in learning in the subchapter of animal reproductive technology can increase.
Item Type: | Thesis (Other) |
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Contributors: | Contribution Contributors NIDN/NIDK Sponsor Yulianti, Ana 1024077901 |
Uncontrolled Keywords: | ARCore SDK, Augmented Reality, Animal, Markerless, Animal Reproduction Technology |
Subjects: | Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
Divisions: | > Teknik Informatika |
Depositing User: | Uthi kurnia S.IP |
Date Deposited: | 13 Sep 2025 08:11 |
Last Modified: | 13 Sep 2025 08:11 |
URI: | https://repository.uir.ac.id/id/eprint/28503 |
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