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All Journal Science in Information Technology Letters ABDIMASTEK
Khoirunnisa, Ninda
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Enhancing the performance of heart arrhythmia prediction model using Convolutional Neural Network based architectures Ismi, Dewi Pramudi; Khoirunnisa, Ninda
Science in Information Technology Letters Vol 5, No 2 (2024): November 2024
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v5i2.1794

Abstract

Heart disease is one of the diseases that exposes high mortality worldwide. This conventional way of predicting heart disease is usually expensive, time-consuming, and prone to human error. Early detection of heart disease is important as it helps to prevent deaths caused by this disease.  Machine learning utilization as the non-invasive means for predicting heart disease is considered as a fast and affordable method to prevent the fatality of heart disease. This work aims at utilizing  Convolutional neural network (CNN)  to enhance the performance of an Arrhythmia prediction model. We have built an Arrythmia prediction model using neural networks comprising multiple convolutional layers and maxpooling layers. Our proposed model is trained using the MIT-BIH Arrhythmia dataset. The model performance has been evaluated and the model achieves  98.43% of performance  accuracy
A comparative study on SMOTE, CTGAN, and hybrid SMOTE-CTGAN for medical data augmentation Khoirunnisa, Ninda; Rosyda, Miftahurrahma
Science in Information Technology Letters Vol 6, No 1 (2025): May 2025
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v6i1.2203

Abstract

The imbalance of clinical datasets remains a challenge in medical data mining, often resulting in models biased toward majority outcomes and reduced sensitivity to rare but clinically critical cases. This study presents a comparative evaluation of three augmentation strategies—Synthetic Minority Oversampling Technique (SMOTE), Conditional Tabular GAN (CTGAN), and a hybrid SMOTE+CTGAN—on the Framingham Heart Study dataset for cardiovascular disease prediction. Augmented datasets were evaluated using Decision Tree, Random Forest, and XGBoost classifiers across multiple metrics, including accuracy, precision, recall, and F1-score. Results demonstrate that classifiers trained on imbalanced data achieved high accuracy but poor minority recall (0.40), confirming model’s bias toward majority class. SMOTE yielded the strongest improvements in minority recall (up to 0.88 with XGBoost) and balanced F1 across classes, though at the cost of reduced majority recall. CTGAN and SMOTE+CTGAN delivered more moderate improvements in minority recall (0.66–0.77) while preserving higher majority recall (0.86), providing a gentler trade-off. These findings indicate that while SMOTE remains a robust baseline for addressing imbalance, hybrid and GAN-based approaches offer practical alternatives for preserving majority performance. The results highlight that augmentation choice should be informed by clinical context.
Pelatihan Aplikasi Keuangan Menggunakan Excel bagi Guru-Guru TK ABA Ngabean Zahrotun, Lisna; Soyusiawaty, Dewi; Khoirunnisa, Ninda; Sari, Hana Jelita
ABDIMASTEK Vol. 4 No. 2 (2025): Desember
Publisher : Universitas Muhammadiyah Jember

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

Abstract

Dalam mengelola keuangan organisasi maupun Lembaga lebih memanfaatkan sistem informasi keuangan, hal ini dilakukan karena mempermudah dalam pembukuan dan pelaporan keuangan. Banyak Lembaga pemerintahan yang sudah menggunakan aplikasi dalam pengelolaan keuangan salah satunya adalah Lembaga Pendidikan. Namun tidak semua jenjang Pendidikan sudah memiliki dan mampu menggunakan aplikasi keuangan. Salah satunya adalah TK ABA Ngabean yang masih menggunakan pencatatan manual daram pengelolaan keuangan sekolah. Tujuan dari pelatihan ini adalah mempermudah kegiatan pencatatan transaksi keluar masuk dan pelaporan keuangan. Aplikasi keuangan dibangun Excel Visual Basic for Application dan Macro. Hal ini disesuaikan dengan kemampuan pemahaman dari Guru dan Tenaga Administrasi TK ABA Ngabean. Selain itu aplikasi ini hanya membutuhakn perangkat yang sederhana melalui Microsoft excel. Pelatihan dilakukan selama 1 hari secara luring dan dilanjutkan pendampingan secara daring. Dari hasil pengujian aplikasi menggunakan metode SUS dengan 14 responden diperoleh nilai 71.6, artinya aplikasi ini layak dan dapat membantu pengelolaan keuangan terutama  pencataan transaksi dan pelaporan sekolah.
Co-Authors Dewi Pramudi Ismi, Dewi Pramudi Dewi Soyusiawaty Lisna Zahrotun Rosyda, Miftahurrahma Sari, Hana Jelita