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Menampilkan 1–10 dari 29 artikel
Integrating Quantum, Deep, and Classic Features with Attention-Guided AdaBoost for Medical Risk Prediction
Kusuma, Muh Galuh Surya Putra
; Setiadi, De Rosal Ignatius Moses
; Herowati, Wise
; Sutojo, T.
; Adi, Prajanto Wahyu
; Dutta, Pushan Kumar
; Nguyen, Minh T.
Journal of Computing Theories and Applications
Vol 3
, No 2
(2025)
Chronic diseases such as chronic kidney disease (CKD), diabetes, and heart disease remain major causes of mortality worldwide, highlighting the need for accurate and interpretable diagnostic models. However, conventional machine learning methods often face challenges of limited generalization, feature redundancy, and class imbalance in medical datasets. This study proposes an integrated classification framework that unifies three complementary feature paradigms: classical tabular attributes, dee...
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Peningkatan Kesadaran Masyarakat Terhadap Hiperurisemia Melalui Pemeriksaan Asam Urat dan Edukasi Gaya Hidup Sehat di Yayasan Baptis Cengkareng
Tjie Haming Setiadi
; Alexander Halim Santoso
; Edwin Destra
; Steven Hizkia Lucius
; Ryan Dafano Putra Mahendri
; Andrew Philo
Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia
Vol 4
, No 2
(2025)
Uric acid is the final product of purine metabolism, which can increase due to high purine intake or impaired renal excretion. Accumulation of uric acid in the body is at risk of causing joint inflammation and other metabolic disorders. Early detection and dietary education are strategic steps to prevent complications of hyperuricemia. This activity uses the Plan-Do-Check-Act (PDCA) approach by examining uric acid levels using POCT and education on managing purine consumption. The examination wa...
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Integrating Hybrid Statistical and Unsupervised LSTM-Guided Feature Extraction for Breast Cancer Detection
Setiadi, De Rosal Ignatius Moses
; Ojugo, Arnold Adimabua
; Pribadi, Octara
; Kartikadarma , Etika
; Setyoko, Bimo Haryo
; Widiono, Suyud
; Robet, Robet
; Aghaunor, Tabitha Chukwudi
; Ugbotu, Eferhire Valentine
Journal of Computing Theories and Applications
Vol 2
, No 4
(2025)
Breast cancer is the most prevalent cancer among women worldwide, requiring early and accurate diagnosis to reduce mortality. This study proposes a hybrid classification pipeline that integrates Hybrid Statistical Feature Selection (HSFS) with unsupervised LSTM-guided feature extraction for breast cancer detection using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Initially, 20 features were selected using HSFS based on Mutual Information, Chi-square, and Pearson Correlation. To addres...
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Analisis User Experience pada Aplikasi E-Office Sumedang Menggunakan Metode User Experience Questionnaire (UEQ) Studi Kasus: Kantor Kecamatan Rancakalong
Modem : Jurnal Informatika dan Sains Teknologi
Vol 3
, No 2
(2025)
The purpose of this study is to analyze the use of the Sumedang E-Office application in order to improve service quality using the User Experience Questionnaire (UEQ) [1]. This study uses the User Experience Questionnaire (UEQ) survey methodology, and this study also collects survey data and a sample size of 25 people. The data sources for this study are primary data and secondary data. The research stage begins by determining the formulation of the problem, analyzing needs, defining questions,...
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Aspect-Based Sentiment Analysis on E-commerce Reviews using BiGRU and Bi-Directional Attention Flow
Setiadi, De Rosal Ignatius Moses
; Warto, Warto
; Muslikh, Ahmad Rofiqul
; Nugroho, Kristiawan
; Safriandono, Achmad Nuruddin
Journal of Computing Theories and Applications
Vol 2
, No 4
(2025)
Aspect-based sentiment Analysis (ABSA) is vital in capturing customer opinions on specific e-commerce products and service attributes. This study proposes a hybrid deep learning model integrating Bi-Directional Gated Recurrent Units (BiGRU) and Bi-Directional Attention Flow (BiDAF) to perform aspect-level sentiment classification. BiGRU captures sequential dependencies, while BiDAF enhances attention by focusing on sentiment-relevant segments. The model is trained on an Amazon review dataset wit...
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Asistensi Penerapan Nilai-Nilai Islami dalam Pembelajaran Akidah Akhlak di MTS Darunnajah
Tomi Bidjai
; Kusno Setiadi
; Resti Riancana
; Vini Desiyanti Monoarfa
; Nurhajja M Hadji
; Adrianto Adrianto
; Irma Irma
Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia
Vol 4
, No 1
(2025)
The application of Islamic values in learning aqidah and akhlak at MTs Darunnajah aims to shape students' characters in accordance with Islamic teachings. This activity is carried out to improve the understanding and practice of Islamic values in students' daily lives. The method used is a participatory approach, involving teachers and students in designing and implementing learning programs. The activity begins with a survey and observation to determine the conditions and needs of teaching...
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Feature Fusion with Albumentation for Enhancing Monkeypox Detection Using Deep Learning Models
Pratama, Nizar Rafi
; Setiadi, De Rosal Ignatius Moses
; Harkespan, Imanuel
; Ojugo, Arnold Adimabua
Journal of Computing Theories and Applications
Vol 2
, No 3
(2025)
Monkeypox is a zoonotic disease caused by Orthopoxvirus, presenting clinical challenges due to its visual similarity to other dermatological conditions. Early and accurate detection is crucial to prevent further transmission, yet conventional diagnostic methods are often resource-intensive and time-consuming. This study proposes a deep learning-based classification model by integrating Xception and InceptionV3 using feature fusion to enhance performance in classifying Monkeypox skin lesions. Giv...
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Penerapan Algoritma Machine Learning dalam Prediksi Prestasi Akademik Mahasiswa
Router : Jurnal Teknik Informatika dan Terapan
Vol 3
, No 1
(2025)
This study explores the application of machine learning algorithms, specifically Linear Regression and Decision Tree Regressor, for predicting student academic performance using academic grade data from Kaggle. The analyzed factors include attendance, assignment grades, midterm exam grades, and final exam grades. The research methodology encompasses data collection, preprocessing, model development, training, and validation. This study contributes to the field of educational data analytics by de...
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Penggunaan Ekspresi Regular dalam Meningkatkan Efisiensi Pencarian Produk pada Aplikasi E-Commerce
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Vol 3
, No 1
(2025)
Product search is one of the important features in e-commerce applications to provide an optimal user experience. This research discusses the implementation of regular expressions as a method to improve the efficiency of product search. With this approach, the system can match string patterns more flexibly, even when there are variations in user input, such as misspellings or inconsistent formatting. The results show that the application of regular expressions can reduce search time by 30% and i...
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A Quantum Circuit Learning-based Investigation: A Case Study in Iris Benchmark Dataset Binary Classification
Journal of Computing Theories and Applications
Vol 2
, No 3
(2025)
This study presents a Quantum Machine Learning (QML) architecture for perfectly classifying the Iris flower dataset. The research addresses improving classification accuracy using quantum models in machine-learning tasks. The objective is to demonstrate the effectiveness of QML approaches, specifically the Variational Quantum Circuit (VQC), Quantum Neural Network (QNN), and Quantum Support Vector Machine (QSVM), in achieving high performance on the Iris dataset. The proposed methods result in pe...
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