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All Journal CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications Engineering, Mathematics and Computer Science Journal (EMACS) International Journal of Computer Science and Humanitarian AI
Alexander Agung Santoso Gunawan
Bina Nusantara University
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

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Journal : Engineering, Mathematics and Computer Science Journal (EMACS)

 1 
Semantic Segmentation for Aerial Images: A Literature Review Yongki Christian Sanjaya; Alexander Agung Santoso Gunawan; Edy Irwansyah
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 2 No. 3 (2020): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v2i3.6737

Abstract

Semantic image segmentation is one of the fundamental applications of computer vision which can also be called pixel-level classification. Semantic image segmentation is the process of understanding the role of each pixel in an image. Over time, the model for completing Semantic Image Segmentation has developed very rapidly. Due to this rapid growth, many models related to Semantic Image Segmentation have been produced and have also been used or applied in many domains such as medical areas and intelligent transportation. Therefore, our motivation in making this paper is to contribute to the world of research by conducting a review of Semantic Image Segmentation which aims to provide a big picture related to the latest developments related to Semantic Image Segmentation. In addition, we also provide the results of performance measurements on each of the Semantic Image Segmentation methods that we discussed using the Intersectionover-Union (IoU) method. After that, we provide a comparison for each semantic image segmentation model that we discuss using the results of the IoU and then provide conclusions related to a model that has good performance. We hope this review paper can facilitate researchers in understanding the development of Semantic Image Segmentation in a shorter time, simplify understanding of the latest advancements in Semantic Image Segmentation, and can also be used as a reference for developing new Semantic Image Segmentation models in the future
Damage Classification on Bridges using Backpropagation Neural Network Victoria Ivy Tansil; Novita Hanafiah; Alexander Agung Santoso Gunawan; Dewi Suryani
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 3 No. 2 (2021): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v3i2.7406

Abstract

Bridge structures can be damaged due to various factors such as pressure, vibration, temperature, etc. This study aims to detect damaged on bridges early so that accidents that can occur due to the damaged-on bridge can be avoided. The research method is divided into designing a model, building the model, and evaluating the model. The result of this research is a program that can classify healthy or damaged bridges using vibration data of tested points on bridges.
User Experience Analysis of Duolingo Using User Experience Questionnaire Anderies Anderies; Cindy Agustina; Tania Lipiena; Ayunda Raaziqi; Alexander Agung Santoso Gunawan
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 5 No. 3 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i3.9227

Abstract

The internet is one of the vital means for everyone to get various information easily and exact like they’re looking for. The use of internet-based learning that is applied in modern times is very influential in the field of education compared to the past, because it can develop language skills in a country, besides that increasingly sophisticated technology can help students learn in a structured manner. One of the impacts we can see or feel is on the learning process. With the internet, it is so much easier either for the students or the teachers. One of the well-known applications in the world is Duolingo. Duolingo is one of many applications that give so much influence to language learning applications. More than 300 million people already use Duolingo for their learning. The purpose of this experiment is to analyze the User Experience of the Duolingo application. The experimental method was applied using surveys distributed via social media. There are 103 Duolingo users who were willing to take the surveys and answer all of the questions given. The result of the survey showed Novelty’s scale has the lowest mean, and Perspicuity’s scale has the highest. That means some of Duolingo’s users found that the application is less interesting. Hence, that could affect the effectiveness of the application.
Co-Authors Achmad Reyfanza Anderies Anderies Andrea Sutanto Arie Qur’ania Ayunda Raaziqi Cindy Agustina Cindy Natasya Dewi Suryani Edy Irwansyah Irvin Irvin Lili Ayu Wulandhari M. Aqila Budyputra Muhammad Edo Syahputra Novita Hanafiah Noviyanti T. M. Sagala Prihastuti Harsani Raditya Tamam Reza A Prasetyo Tania Lipiena Triastinurmiatiningsih, Triastinurmiatiningsih Victoria Ivy Tansil Yongki Christian Sanjaya