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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Global Medical and Health Communication SISFOTENIKA JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Media Keperawatan Indonesia JURNAL TEKNOLOGI INFORMASI Applied Technology and Computing Science Journal International Journal of Informatics and Computation Prosiding Seminar Nasional Multidisiplin Ilmu Respati Jurnal Teknik Informatika (JUTIF) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Prosiding Seminar Nasional Pengabdian Kepada Masyarakat International Journal of Informatics Engineering and Computing
Sri Hasta Mulyani
Universitas Respati Yogyakarta
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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GENERATIVE ADVERSARIAL NETWORKS FOR ANTERIOR CRUCIATE LIGAMENT INJURY DETECTION Mulyani, Sri Hasta; Diqi, Mohammad; Salsabil, Husna Arwa
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.1150

Abstract

This research explores the application of Generative Adversarial Networks (GANs) for detecting and classifying Anterior Cruciate Ligament (ACL) injuries using MRI images. The study utilized a dataset of 917 MRI images, each labeled as healthy, partially injured, or completely ruptured, to train the model. The performance of the GAN model was evaluated using a confusion matrix and a classification report, yielding an overall accuracy of 92%. The model demonstrated high proficiency in identifying healthy ACLs and partially injured ACLs but encountered some challenges in accurately identifying completely ruptured ACLs. Despite this, the results suggest that machine learning techniques, particularly GANs, have significant potential for enhancing the accuracy and efficiency of ACL injury detection. The ability of the model to distinguish between different degrees of injury could potentially aid in treatment planning. However, the study also underscores the need for further refinement of the model, particularly in improving its sensitivity in detecting severe ACL injuries. This research highlights the potential of machine learning in medical imaging and provides a solid foundation for future research in ACL injury detection and classification.
An Internet of Things-Based Temperature and Humidity Monitoring System for Palm Sugar Storage Warehouses Izzurohman, Moh.; Mulyani, Sri Hasta; Ordiyasa, I Wayan
International Journal of Informatics Engineering and Computing Vol. 2 No. 2 (2025): International Journal of Informatics Engineering and Computing [Preview]
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/c3d6kr84

Abstract

The integration of Internet of Things (IoT) technology in warehouse management offers real-time monitoring and control to improve efficiency and minimize risk. This study develops an IoT-based system for a sugar warehouse to monitor environmental parameters such as temperature and humidity. The system uses sensors (DHT22, ultrasonic, and light sensors) connected to a NodeMCU ESP8266, with real-time data sent to a web dashboard via the internet. The results indicate that the system can detect environmental changes and send alerts when thresholds are exceeded, ensuring sugar quality and reducing manual supervision.
Co-Authors Ariyanto Nugroho Catur Paryadi Fajar Y Zebua Giyawati Yulilania Okinarum Hamzah Hamzah Hamzah Husna Arwa Salsabil Izzurohman, Moh. Jerry Hardianto Maisarah Nurain Marselina Endah Hiswati Mohammad Diqi Okinarum, Giyawati Yulilania Ordiyasa, I Wayan Putra Wanda, Putra R.Nurhadi Wijaya Rizky Erwanto Rizky Erwanto Rodiyah Suwarto Trinidya, Fike Venny Vidayanti Vidayanti, Venny Wijaya, Nurhadi Wita Adelia