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All Journal Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Aiti: Jurnal Teknologi Informasi Infotek : Jurnal Informatika dan Teknologi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Bulletin of Computer Science Research Journal of Information Technology (JIfoTech) Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science SmartComp SAINTEK Infact: Jurnal Sains dan Komputer Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) UPGRADE: Jurnal Pendidikan Teknologi Informasi
Agustinus Rudatyo Himamunanto
Universitas Kristen Immanuel
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Other

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Journal : Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)

 1 
Analisis Performa Raytracing dan MCMC Pada Realisme Visualisasi Obyek 3D Dengan Terintegrasi MIPMapping Budet, Vincensa Woytimena; Himamunanto, Agustinus Rudatyo; Budiati, Haeni
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.436

Abstract

The development of computer graphics has resulted in an increasingly realistic and immersive digital world, especially in the field of 3D object representation. One of the techniques for image presentation is ray tracing, however, regular ray tracing requires long computation time. To achieve high realism in 3D objects, complex computational operations and the use of appropriate algorithms are required. In this research, Markov chain Monte carlo (MCMC) algorithm has the potential to achieve realism on a 3D object. This research analyzes the performance comparison between ordinary ray tracing and MCMC algorithm in achieving realism on 3D objects and integrating Mipmapping technology to improve the visual quality of 3D objects. The results are measured by calculating the PSNR value on the rendered object and comparing the noise level of a 3D object rendered with ordinary ray tracing, and ray tracing using the Monte carlo algorithm. The number of samples used were 50 samples of 3D objects tested with Monte Carlo and obtained a result of 94%, and with ordinary ray tracing of 6% which is indicated by the level of distortion or error that occurs in the processed object. This shows that by rendering using the MCMC algorithm the image quality of the rendered object is better than rendering using ordinary ray tracing
Implementasi dan Analisis Performa Pembelajaran Pengenalan Hewan Pada Anak-Anak Usia 5 Tahun Berbasis Augmented Reality Chrisdyanto, Daniel Nourman; Himamunanto, Agustinus Rudatyo; Sumihar, Yo’el Pieter
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.424

Abstract

Introducing animals to early childhood is a crucial aspect of their initial educational development. At the age of 5, children are in a significant phase of developing language, observational skills, and conceptual understanding. In the context of learning, Augmented Reality (AR) can provide a more interactive and immersive learning experience compared to traditional methods. This application was created using Vuforia and Unity Engine, with the C# programming language. The application can display 3D animal objects, play animal sounds, and provide information about the animals in Indonesian. The animals featured in this application are the Brazilian turtle and the dog. Based on the data, images included in the Vuforia database showed a detection success rate of 7 out of 9 images for the Brazilian turtle. Meanwhile, for the dog, 10 out of 12 images included in the Vuforia database were successfully detected. These figures are reflected by the number of stars in the Vuforia database.
Peningkatan Resolusi Citra dengan Menggunakan Metode GAN untuk Aplikasi Peningkatan Gambar Ama, Marniati Triningsi Tamo; Himamunanto, Agustinus Rudatyo; Setyawan, Gogor Christmass
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.447

Abstract

This research proposes the use of a Generative Adversarial Network (GAN), a deep learning approach consisting of two neural networks: a generator that generates high-resolution images from low-resolution images, and a discriminator that distinguishes between original high-resolution images. and the image the generator produces. Through joint training, the generator learns to produce increasingly realistic and detailed images. This research uses training data of 400 image data, 100 images consisting of training data and test data. The GAN model trial showed a success rate of 80% training data, 20% test data. This process continued through repeated testing and 10,000 epoch training periods using Pytorch to train the GAN, with sharper and more detailed results than conventional methods. The application of GANs in various applications such as medical image processing, video restoration, and security surveillance shows great potential in improving image quality. Challenges such as training stability and computational time are overcome through more efficient regularization and optimization techniques, so that GANs prove to be a powerful tool for image resolution enhancement with a significant contribution to the development of more advanced image processing technologies.
Co-Authors Ama, Marniati Triningsi Tamo Bolo, Naomi Tena Budet, Vincensa Woytimena Budiati, Heni Chrisdyanto, Daniel Nourman Dangga, Nofrilia Debora, Agnes Monica Deona Carol Gerjana Rijke Saijuna Desri A.F. Waruwu Erwin Oktaf Kurniawan Waruwu Febe Maedjaja Gea, Juli Hartati Gogor Christmass Setyawan Gulo, Bintang Karmila Haeni Budiati Haeny Budiati Jatmika Kristian Juri Damai Lase Listra Frigia Missianes Horhoruw Magdalena, Mensiana Nelvina Adonia Niasiska, Niasiska Nurcahyo, Azriel Christian Olam, Enos Nikodemus Samuel Tora Setyawan, Gogor Setyawan, Gogor C. Setyawan, Gogor Chrismass Sumihar, Yo’el Pieter Supriadi, Joseph Susilo, Zefanya Damar Aristo Swasono, Henoch Yanuar Ari Swasono, Natan Enggal Tasane, Elshaddai L Wanda, Melifan Zalukhu, Jean Pinter Son Zalukhu, Talenta Teholi