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Template Matching Algorithm Implementation For Introduction To Indonesian Traditional House Agus Sujarwadi; Joseph Carlo K; Iwan Hartadi TU; Erik Iman HU; Suhirman; A.Djoko Budiyanto; Suyoto; Natan Derek
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 4 No 2 (2022): International Journal of Engineering, Technology and Natural Sciences
Publisher : University of Technology Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (496.472 KB) | DOI: 10.46923/ijets.v4i2.182

Abstract

Digital image processing is an important way in computer vision to determine the shape of digital image objects. Many image processing applications have been produced, one of which is pattern recognition. Pattern recognition can be interpreted as the process of classifying a number of objects into several categories based on similarities and similarities in characteristics. In this study, the pattern recognition of traditional houses in Indonesia will be carried out. In the pattern recognition process, several stages of image processing (image pre-processing) are needed which aims to make the pattern obtained can be recognized accurately. For the introduction of this traditional house, several stages will be carried out before it can finally be recognized by the system. First, the image will be converted into a gray image, after the gray image is obtained, it will be converted into a binary image using thresholding and then followed by normalizing the image size (resize). After that, the resized image will be recognized using the Template Matching method. The results of this study, using 20 examples of traditional house patterns categorized into 10 types of traditional houses in Indonesia, the system can recognize 16 traditional house patterns correctly with an accuracy percentage of 80%. But this system also still has imperfections. Imperfections occur due to several factors such as taking the angle of the object in the test image that does not match the angle of the object in the target image, and also the presence of additional objects that cover the shape of the traditional house that will be recognized; such as: trees, cars, etc., as well as poor test image conditions.
Decentralized Finance (DeFi), Strengths Become Weaknesses: a Literature Survey Aziz Perdana; Erik Iman HU; Rianto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4806

Abstract

The use of blockchain technology in Decentralized Finance (DeFi) has gained popularity, with 23 public companies and one country holding bitcoin. DeFi aims to create an open and decentralized financial ecosystem that is accessible to everyone, eliminates intermediaries like financial institutions, and is verifiable, immutable, globally accepted, fast, low-cost, anonymous, and non-custodial. Despite its benefits, the rapid growth of DeFi has led to increased security risks. This study assesses the validity of DeFi's superiority claims in light of security incidents and events in 2022 and Twitter trends. This study used a Systematic Literature Review from various research articles and news from 2022. This research found that DeFi's superiority claims seem to be inconsistent with what is being advertised. It also found that if DeFi is not properly prepared and audited, its strength (Anonymous, open-source, decentralized, non-custodial, eliminates third parties and regulation) may become its weakness. Despite this, users still exhibit high levels of trust and optimism, as seen in the most popular terms shared by user tweets during significant losses, with 301,654 unique tweets between April 30 and May 31, 2022 and 344,519 unique tweets between October 3 and December 3, 2022, that are crypto, nft, and blockchain.