Article Per Year (5 Year)
p-Index From 2021 - 2026
4.97
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Jurnal Buana Informatika JUITA : Jurnal Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Indonesian Journal of Information System J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Community Empowerment Journal of Applied Data Sciences Nakhoda: Jurnal Ilmu Pemerintahan Emerging Information Science and Technology Prosiding Seminar Nasional Program Pengabdian Masyarakat Scientific Journal of Informatics Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Cahya Damarjati
Universitas Muhammadiyah Yogyakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences

Published : 46 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 46 Documents
Search

 1   2   3   4   5 
Automatic Measurement Application of Heart Area from Chest X-Ray Images Using the U-Net Deep Learning Method Setianto, Andhika Putra; Damarjati, Cahya; Asroni, Asroni
Emerging Information Science and Technology Vol. 2 No. 1: May 2021
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v2i1.16864

Abstract

Heart health is a basic human right and a crucial component of global health justice. In an ever-more-advanced age, every task becomes simple due to science, technology, and information development. However, certain tasks are still performed manually. Therefore, innovation in computerized system design is required. The human heart area calculation was performed by combining image processing and deep learning techniques. Deep learning is a scientific subfield of machine learning, while image segmentation is a step in image processing. This study employed the U-Net segmentation method to identify different stages of heart area calculation. U-Net could conduct image segmentation with the small training dataset accurately. This study’s population consisted of 800 chest X-ray images obtained from the Kaggle website, with human hearts as the sample. The findings revealed that the training data with the U-Net architecture model acquired an accuracy of 09.98. However, the testing data accuracy was still determined manually. In this work, the U-Net model employed an input shape measuring 256x256, a kernel size of 3x3, and 50 epochs.
Classification of Student Understanding on Covid-19 Booster Vaccine Using Machine Learning Damarjati, Cahya; Riyadi, Slamet; Irawan, Ricki
Emerging Information Science and Technology Vol. 3 No. 2 (2022): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v3i2.18680

Abstract

The outbreak of COVID-19 has been declared a global pandemic by the World Health Organization (WHO). Developing a vaccine is one of the best ways to reduce the virus's impact. Nevertheless, the development of virus mutations produces new variants that diminish the efficacy of the previous vaccine. Booster doses of the Covid-19 vaccine is still a matter of debate among the public, particularly among students, as evidenced by the low rate of booster vaccinations in the community, which is a result of a lack of knowledge about booster vaccines. The purpose of this study is to assess the level of understanding among Universitas Muhammadiyah Yogyakarta (UMY) students regarding booster vaccinations, with the results subsequently serving as a factor or strategy for future government booster vaccination policy decisions. ANN and SVM algorithms could be used to predict the level of understanding of booster vaccinations among UMY students. However, the maximum level of precision in classifying the level of comprehension is not yet known. To determine which of the two methods, kernel and k-fold, provided the maximum level of accuracy, a comparative study was conducted between them. The research was conducted by disseminating questionnaires containing assessments of booster vaccinations to a total of 2095 respondents. Using randomized sampling type, this study yielded an accuracy of 88.45% for the ANN method and 89.93% for the SVM method in each scenario. In addition, the authors conduct feature efficiency, which aims to reduce the time and cost associated with data computation.
Laravel Framework-Based Information System of the Department of Information Technology of Universitas Muhammadiyah Yogyakarta Musyary, Musyary; Kurniati, Aprilia; Damarjati, Cahya
Emerging Information Science and Technology Vol. 4 No. 2 (2023): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v4i2.20736

Abstract

It is crucial to have a reliable and adequate information system to implement information technology. It explains why technology must continue advancing in this area, specifically regarding the Information Technology Department’s information management at Universitas Muhammadiyah Yogyakarta (UMY). Information has been disseminated through the WhatsApp and Telegram applications, leading to improper conveying of the made and supplied information due to excessive stacking. Hence, a web-based information system was developed in PHP with the help of the Laravel framework to overcome the issue. Moreover, a database was set up using MySQL to circumvent the issue. The newly constructed information system could enhance information management, leading to more accurate and efficient information generation for various uses.
Partial Adaptive Multi-Level Block Truncation Coding (Ambtc) Of Spinal X-Ray Image For Efficient Compression Damarjati, Cahya
Emerging Information Science and Technology Vol. 5 No. 1 (2024): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v5i1.22409

Abstract

This study aims to explore various adaptations of the AMBTC compression model applied to lumbar spine radiographic images, focusing on minimizing image size while preserving essential information. The approach involves adjusting several technical aspects of the AMBTC model, including the number of blocks, block size, and compression rate. The quality of the compressed images is assessed using image quality metrics such as PSNR (Peak Signal-to-Noise Ratio) and MSE (Mean Squared Error). The findings indicate that a modified AMBTC compression model can significantly enhance the quality of lumbar spine radiographic images, evidenced by increased PSNR values, while substantially reducing the file size without compromising crucial image details
Discrete Curvelet Transform Feature Extraction for Mangosteen Fruit Surface Damage Detection Utama, Nafi Ananda; Triyani, Wahyu Indah; Riyadi, Slamet; Damarjati, Cahya
Emerging Information Science and Technology Vol. 5 No. 1 (2024): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v5i1.22602

Abstract

Mangosteen (Garcinia mangostana L) is one of the commodities of Indonesian fruit and is used as an export primadona that became the basis of Indonesia to increase the currency of the country. The quality of the fruit can be seen from the surface, whether there is damage or not. The sorting that the farmers have been doing all this time is still using the conventional way, that is, with the sense of sight. This conventional method seems to be less effective because it takes a lot of energy, takes a long time, and there are different perceptions between farmers. To solve this problem, a method of surface quality extraction of mango fruit will be developed based on image processing. The initial stage of image processing is with the image size equation then the image is converted to grayscale mode, then a discrete curvelet transformation is performed. The next stage is the extraction of mean, energy, entropy, standard deviation, variance, sum, correlation, contrast, and homogeneity. The result of the subsequent feature extraction is used to enter a value at the classification stage. From some of these extractions it will be known which extraction has the highest accuracy value. The method of classification used is Linear Discriminant Analysis (LDA) with the method of K-Fold Cross Validation which in this study is divided into 4-fold cross validation. After testing on 120 images, the highest value of accuracy is with extraction of standard characteristics deviation of 91.7% and variance of 88.4%.
Pengembangan Aplikasi Perawatan Sepatu Berbasis Website Asroni Asroni; Dede Chandra; Cahya Damarjati
Proceeding of Informatics Collaborations and Dessimenation Meeting Vol. 1 No. 1 (2025)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Vist Clean adalah layanan perawatan sepatu yang bertujuan untuk membersihkan, merawat, dan memperbaiki sepatu pelanggan dengan teknik khusus. Namun, minimnya digitalisasi menyebabkan efisiensi operasional rendah dan banyak kesalahan, seperti pencatatan transaksi manual yang menyulitkan rekap data. Selain itu, pelanggan harus mengecek status pengerjaan secara manual karena durasi perawatan bergantung pada antrean dan kondisi sepatu.Untuk mengatasi hal ini, dikembangkan sistem informasi berbasis online yang memungkinkan pemesanan layanan, pencatatan transaksi digital, dan pemantauan status pengerjaan. Dengan sistem ini, transaksi tercatat otomatis, dan pelanggan dapat memeriksa status laundry sepatu secara mandiri.Pengembangan sistem menggunakan metode Waterfall SDLC, sementara analisis dan perancangan dilakukan dengan UML. Sistem ini dikembangkan menggunakan PHP (Laravel), Bootstrap, dan MySQL. Fitur utama mencakup pemesanan layanan dengan laporan yang dapat diunduh serta pelacakan status pengerjaan sepatu.
Co-Authors Abdul Eriawan Nahar Abdurrahim, Minhajuddin K. Abyiyansyah Meidy Laksono Adhianty Nurjanah Amelia Mutiara Ayu Ratiwi Andhika Putra Setianto Aprilia Kurnianti Aprilia Kurniati, Aprilia Arifia Kasastra R ARIS NUGROHO Asnor Juraiza Ishak Asri Tri Wulandari Asroni Asroni Asroni Asroni Asroni Asroni Asroni, Asroni Ayu Ratiwi, Amelia Mutiara Azizah, Laila Marifatul Bahrurozi, Sofran Chen, Hsing-Chung Dede Chandra Dimas Bagas Ajipratama Edifianto, Gilang Hendra Dita Eko Fajar Cahyadi Eko Prasetyo Fadhan Anwarodin Fauri Hakim Gilang Hendra Dita Edifianto Heri Wijayanto Indira Prabasari Indira Prabasari, Indira Irawan, Ricki Ishak, Asnor Juraiza Kamarul Hawari Ghazali Karim, Rohana Abdul Karisma Trinanda Putra, Karisma Trinanda Kasastra R, Arifia Laila Ma’rifatul Azizah Lukito Edi Nugroho Mahardika, Naufal Gita Mahmudi, Muhammad Nazih Masyhur, Ahmad Musthafa Maududi Nur Imani Tarigan Minhajuddin K. Abdurrahim Muhammad Alfadha Termahadi Muhammad Dzaki Mubarok Mukhtar Hanafi Musyary, Musyary Nafi Ananda Utama Nano Prawoto Nasrul Saefullah Nisrina Akbar Rizky Putri Prasetyo, Satria Prayitno Prayitno Ramli, Suzaimah Ricki Irawan Ridho Al-Hamdi Rochmah, Faizatur Salsabila, Lathifah Khansa Sartika Puspita Setianto, Andhika Putra Sifa Dinia Silvester Tena Siti Khotimah Slamet Handoko Slamet Riyadi Slamet Riyadi Slamet Riyadi Sofiani, Erma Sofran Bahrurozi Sri Suning Kusumawardani Sunardi Sunardi Suparman Suradi, Muhamad Arief Previasakti Suwadi Suwadi Titis Wisnu Wijaya Titis Toha Ardi Nugraha Tony K Hariadi Trinanda Putra, Karisma Triyani, Wahyu Indah Utama, Nafi Ananda Yunita Lestari