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All Journal JAIS (Journal of Applied Intelligent System) Jurnal Kesehatan Vokasional Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) JOINT (Journal of Information Technology Jurnal Teknik Informatika (JUTIF) Jurnal Kesehatan Tambusai Jurnal Puan Indonesia Tedc Journal of Economics, Accounting, Tax and Management Journal of Innovative and Creativity Journal of New Trends in Sciences JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Journal of Applied Information Technology and Innovation
Ayu Hendrati Rahayu
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Journal : jais journal of applied intelligent system

 1 
Classification of X-Ray Images of Normal, Pneumonia, and Covid-19 Lungs Using the Fuzzy C-Means (FCM) Algorithm Dini Rohmayani; Ayu Hendrati Rahayu
Journal of Applied Intelligent System Vol 7, No 1 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i1.5512

Abstract

Lung disease has a very serious impact on the respiratory system and can be dangerous if not treated immediately. At this time, lung diseases that are often encountered by the public include pneumonia and 2019 coronavirus. Many people mistake the disorder that occurs to him because the symptoms of Covid-19 and pneumonia are very similar. Thus, it is very important to know the difference between the two diseases so that early treatment can be carried out. Based on the problems that have been described, the author will propose a study entitled "Classification of X-ray Images of Normal Lungs, Pneumonia, and Covid-19 Using the Fuzzy C-Means (FCM) Algorithm". The aim of this study is to assist in classifying normal, pneumonia, and Covid-19 lungs. The reason for choosing this algorithm is that this algorithm has advantages in grouping cluster centers which are more optimal than other methods.
Naive Bayes Performance in Analysis of Public Opinion Sentiment Against COVID-19 Ayu Hendrati Rahayu; Ari Sudrajat
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.7134

Abstract

The huge impact caused by the COVID-19 pandemic has made many people express their opinions on Twitter social media. There are various responses given by the community that are negative and positive. The dataset comes from kaggle with more than 750 tweets of data. Classification designed by the Naive Bayes method. Implementation through preprocessing, case folding, tokenizing, stopword removal, TF-IDF, and cross validation has been able to produce quite high accuracy. After classification, validation will be carried out with Cross Fold Validation. The best value is on cv5 where accuracy = 0.847, precision = 0.855, recall = 0.83, and f1 score = 0.842.
Watermarking using DCT and DWT on Pneumonia images Sudrajat, Ari; Rahayu, Ayu Hendrati
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.8914

Abstract

Watermarking is a branch of the data hiding technique. Watermarking is a technique used to insert a copyright label on an image, so that the copyright of the image can be protected. Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are techniques that can be used to watermark. In this study, the Discrete Cosine Transform and Discrete Wavelet Transform methods will be used to watermark images to 5 different host images. In the tests carried out, watermarking techniques will be compared using DCT, DWT, DCT-DWT combination and DWT-DCT combination. The results obtained in this study were the highest PSNR value obtained at 41.931, the highest SSIM obtained 0.99515, the highest entropy was also obtained at 7.4186, The best UACI value is 0.0071158 and the best NCPR value is obtained at 93.9068% then, for the best CC value is obtained at 0.99953. As well as the NCC value, the value obtained is the same all in each test, namely with a value of 1.
Improving Heart Disease Severity Prediction Using SMOTE for Imbalanced Data Rahayu, Ayu Hendrati; Sudrajat, Ari
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 2 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i2.11180

Abstract

The heart disease is a prevalent and potentially fatal condition affecting individuals worldwide. In this study, we address the challenge of predicting the severity of heart disease using supervised learning techniques. Leveraging a dataset comprising various demographic and clinical attributes, we propose a solution that employs machine learning models to accurately predict the severity level of heart disease. Among the evaluated models, Random Forest emerges as the top performer, showcasing exceptional precision, recall, accuracy, and F1-score across all severity levels, with an overall accuracy of 98.8%. This highlights the robustness of the Random Forest model in accurately classifying instances across different severity levels. Following closely behind, the KNN algorithm demonstrates commendable performance, achieving an accuracy of 92% and showcasing competitive precision, recall, and F1-score values, particularly for higher severity levels. Despite its notable aspects, XGBoost ranks third among the evaluated models, with an accuracy of 90.4%. While XGBoost excels in certain aspects, such as recall for Level 3 severity, it falls short in overall performance compared to Random Forest and KNN. For future research, exploring ensemble methods that combine the strengths of different algorithms could yield even better classification results, providing avenues for further improvement in predicting the severity of heart disease
Co-Authors Aditia Gusman Apnena, Riri Damayanti Ari Sudrajat Aris Haris Rismayana Arya Aditya Asep Maulana Castaka Agus Sugianto Dini Rohmayani Encep Hada Encep Hada Fathia Mawar Firdaus Firdhani Faujiyah Gerinata Ginting Gerinata Ginting Gerinata Ginting Ginting , Gerinata Haikal, Rafli Intan Puji Lestari Intan Pujilestari Iqtait, Musab Luqman Nul Hakim Luqmanul Hakim Marlina, Lusi Monica, Rizqy Dimas Muhammad Ridwan Narisya Nur Intan Paba Neni Rohaeni Neni Rohaeni Nia Ekawati Novi Irawati Novita Lestari Anggreini Pitriani, Kania Pujilestari, Intan Riri Damayanti Apnena Rizqy Dimas Monica Rizqy Dimas Monica Rochmawati Rochmawati Sabila Nopiyanti Setiawan, Nadia Meythalia Shakila, Ramilla Shandy Tresnawati Siti Nuraini Buransa Suharto . Suharto Suharto Suharto Suharto Taufik Fajar Mustafa wibowo, teguh iman Wiwin Tri Antika Wowo Trianto Yesti Suryati