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All Journal Jurnal Informatika dan Teknik Elektro Terapan E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal ABDINUS : Jurnal Pengabdian Nusantara Journal Zetroem Abditeknika - Jurnal Pengabdian Kepada Masyarakat Seminar Nasional Ilmu Terapan Software Development Digital Business Intelligence and Computer Engineering Jurnal ELTEK
Subono, Subono
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Journal : Journal Zetroem

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Analisis Kinerja Multimodal Dense Neural Network untuk Deteksi Hipoksia Janin pada Dataset Tidak Seimbang Yusuf, Dianni; Subono, Subono
ZETROEM Vol 7 No 2 (2025): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v7i2.6204

Abstract

This study aims to develop a Multimodal Dense Neural Network (MDNN) for detecting fetal hypoxia using an imbalanced Cardiotocography (CTG) dataset. The primary challenges in fetal hypoxia diagnosis include the imbalance between Normal, Suspect, and Hypoxia classes and the limited interpretability of conventional deep learning models. To address these issues, a robust preprocessing pipeline was designed, consisting of Physiological Clipping (50–200 bpm), Median Absolute Deviation (MAD) normalization, SMOTETomek balancing, and Gaussian noise augmentation. The MDNN architecture integrates two parallel branches: Fetal Heart Rate (FHR) signals and clinical parameters (pH, Apgar score, and base deficit), fused through a Dense Fusion Layer to generate compact multimodal representations. Experimental results demonstrate that the proposed MDNN achieved 99.7% accuracy, 99.5% F1-score, and 0.993 AUC, outperforming CNN (84.6%), ResNet18 (82.3%), and MLP (87.5%). The confusion matrix showed good generalization capability with per-class accuracies of 69% (Normal), 56% (Suspect), and 67% (Hypoxia). SHAP feature importance analysis identified FHR pattern (0.45) and pH level (0.25) as the most influential features in classification. These findings confirm that the proposed MDNN is robust, computationally efficient, and clinically interpretable, making it a promising framework for real-time fetal hypoxia diagnosis in modern clinical environments.
Analisis Efektivitas Metode Responsible, Accountable, Consulted, Informed (RACI) dalam Sistem Manajemen Process Approval subono, subono; Yusuf, Dianni
ZETROEM Vol 7 No 2 (2025): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v7i2.6450

Abstract

The approval management process plays an essential role in improving efficiency and accountability in organizational decision-making. PT Asta Berkah Autonomous, a company specializing in automation system development, faces challenges in transparency and efficiency due to manual approval procedures conducted through Google Forms and email. This study aims to design and implement a web-based approval management system integrated into the Asta Project application using the Responsible, Accountable, Consulted, Informed (RACI) method. The RACI method is applied to clearly define the roles and responsibilities of each stakeholder, ensuring a structured and transparent approval workflow. The system development process adopts the Rapid Application Development (RAD) approach, emphasizing iterative design and user involvement. System testing was conducted using Blackbox Testing and User Acceptance Testing (UAT) based on ISO 9126 quality standards. The results demonstrate that the implementation of the RACI method enhances role clarity, process efficiency, and transparency among participants. The developed system successfully reduces submission time, simplifies approval tracking, and supports faster and more accurate decision-making. This implementation significantly contributes to improving productivity and governance of the approval process within PT Asta Berkah Autonomous. System testing using Blackbox Testing and User Acceptance Testing (UAT) based on ISO 9126 quality standards. The results show that all system functions operated successfully (100% valid), with an average user satisfaction score of 84.44%, categorized as excellent. The application of the RACI method significantly improved efficiency, transparency, and accountability in the company’s approval process. Overall, the developed system contributes to digital transformation efforts and enhances corporate governance effectiveness.
Co-Authors Agustina, Nur Anis Alfaini, Husnul Alif Akbar Fitrawan, Alif Akbar Avian, Cries Ayatullah, Mohamad Dimyati Dianni Yusuf Eka Novita Sari, Eka Novita Erni Yudaningtyas Fuad Al Haris, Muhammad Hidayat, Alfin Indira Nuansa Ratri Lutfi Hakim Muhammad Aziz Muslim Nuril Jazilah, Alisa Prasetyo, Junaedi Adi Puspita, Nanda Ayu Rini, Eka Mistiko Rohmatillah, Mahdin Sepyan Purnama Kristanto Suardinata, I Wayan Suwardiyanto, Devit Syamsiana, Ika Noer Vivien Arief Wardhany Wibowo, Galih Hendra