Article Per Year (5 Year)
p-Index From 2021 - 2026
2.096
P-Index
This Author published in this journals
All Journal snimed Jurnal Simantec JURNAL PENDIDIKAN TAMBUSAI INTEK: Informatika dan Teknologi Informasi Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi International Journal of Engineering, Technology and Natural Sciences (IJETS) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Scientific Research, Education, and Technology Mekongga: Jurnal Pengabdian Masyarakat
Astrianty, Ledy Elsera
Universitas Teknologi Yogyakarta
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Development of Mobile Augmented Reality-Based Boarding House Search Application Pamungkas, Awanda Bintang; Astrianty, Ledy Elsera
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 3 No. 4 (2024): Vol. 3 No. 4 2024
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v3i4.592

Abstract

This research focuses on developing a mobile application for boarding house search utilizing Augmented Reality (AR) technology. The application integrates AR features to provide an interactive and immersive experience, enabling users to visualize boarding houses in 3D and explore detailed information in real time. The ADDIE model was adopted as the development framework, encompassing Analysis, Design, Development, Implementation, and Evaluation phases. The application features include a 360-degree view, GPS navigation, real-time updates, and an intuitive user interface to enhance the boarding house search process. Black box testing results indicate that the system performs efficiently across key functionalities such as registration, login, navigation, and booking. The findings demonstrate the potential of AR technology to address challenges in property search, offering innovative solutions for both users and property owners. This study contributes to the advancement of AR-based applications in the housing sector, emphasizing their role in improving user satisfaction and decision-making.
Empowering Digital Parenting through Web-Based Admission System and Technology Literacy Training for Families in Early Childhood Education Kalifia, Anna Dina; Astrianty, Ledy Elsera; Sanjaya, Fadil Indra; Pramudwiatmoko, Arif
MEKONGGA: Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2025): April 2025
Publisher : Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mekongga.v2i1.218

Abstract

This community service program was conducted to address two main problems identified at TK Pamardisiswi Muja Muju, Yogyakarta: the limited digital literacy among parents in guiding their children’s use of technology, and the absence of an accessible web-based student registration system. The program was implemented through an educational and technological approach, including observation, interviews, system development, training, and evaluation. The developed information system simplified the administrative process and expanded access to educational information. The training provided not only improved participants’ technical skills in operating the system but also enhanced their understanding of digital parenting. Evaluation results indicated a significant increase in participants’ abilities: login (35% to 92%), online form completion (28% to 89%), document upload (25% to 86%), understanding of digital content risks (19% to 81%), and awareness of parental roles in guiding children in the digital environment (30% to 90%). This program contributed to strengthening family digital literacy and advancing educational digitalization in early childhood settings.
Sistem Prediksi Kualitas Udara Menggunakan Algoritma Long Short-Term Memory (LSTM) Wicaksono, Muhammad Zaki; Astrianty, Ledy Elsera
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8619

Abstract

Conventional and static air quality monitoring in Yogyakarta City which only presents historical (past) data reports hinders proactive mitigation efforts against air pollution. This research aims to develop an air quality prediction system using the Long Short-Term Memory (LSTM) algorithm, a deep learning method superior for time-series data analysis. The system utilizes historical data from the Yogyakarta City Environmental Agency (DLH) from 2022 to 2024, covering pollutant parameters such as PM10, PM2.5, SO₂, CO, O₃, and NO₂. The primary prediction focus is the AQI (Air Quality Index) value, calculated based on the concentration of these pollutant parameters. The research method includes data preprocessing, such as handling missing data with interpolation, designing a two-layer LSTM model architecture, model training, and performance evaluation using Mean Absolute Error (MAE) and Mean Absolute Deviation (MAD) metrics. The results show that the developed LSTM model successfully provides predictions with good performance, where the combined average MAE value (4.85) is significantly lower than the average MAD of the actual data (10.19), indicating that the model's prediction error is smaller than the natural variability of the data. The output of this research is a prototype application with a graphical user interface (GUI) capable of displaying air quality predictions for the next day, identifying critical pollutant components, and presenting air quality condition classifications informatively.
Applying Convolutional Neural Networks for Real-Time Recognition of Indonesian Traditional Foods Adiyasa, Ananta Rizqi; Astrianty, Ledy Elsera
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 4 No. 4 (2025): Vol. 4 No. 4 2025
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v4i4.976

Abstract

This study aims to develop an image-based recognition system for Indonesian traditional foods to support the preservation of Nusantara culinary heritage in the digital era using the Convolutional Neural Network (CNN) method. This research was conducted due to the very limited number of studies specifically focused on classifying Indonesian regional traditional foods. Using a transfer learning approach, the pre-trained ResNet50 model was employed as the main architecture, with fine-tuning applied to the final layers to adapt the classification to 13 categories of Indonesian traditional foods. The dataset consisted of 1,300 images that underwent preprocessing and data augmentation to enhance the model’s generalization performance. Evaluation results show that the model achieved an accuracy of 81%, with precision, recall, and F1-score values indicating strong classification performance across most classes. The model was integrated into a user interface system to support real-time image prediction. System testing demonstrated fast response capabilities and high prediction confidence. Overall, this study confirms that CNNs with transfer learning can serve as an effective solution for recognizing Indonesian traditional foods and hold potential for further development as an educational medium and a tool for promoting local culinary culture.
Co-Authors Adiyasa, Ananta Rizqi Ardias, Asril Lintang Bagus Lindu Pamungkas Christian Wibowo Trinugroho Fadhlika Rahma Taru Dinata Fadil Indra Sanjaya Fajardika Dwi Yulianto Fajriyah, Rohmanul Galang Aidil Akbar Izzati Muhimmah Kalifia, Anna Dina Ma’mur Pebrianto Mohamad Krisna Maulana Nanda Prasetya Pamungkas, Awanda Bintang Pramudwiatmoko, Arif Saputri, Bella Dian Silvia Rosita SITORUS, TOBA AMIRUDDIN Wahyu Dwi Susanti Wan Rivaldo Wicaksono, Muhammad Zaki Yasmini Fitriyati, Yasmini