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Charis Fathul Hadi
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Prodi Teknik Elektro, Fakultas Teknik , Universitas PGRI Banyuwangi Jl.Ikan Tongkol No. 22 Banyuwangi 68416, Jawa Timur
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Journal Zetroem
Published by Universitas PGRI Banyuwangi
ISSN : 2656081X     EISSN : 2656081X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
jurnal zetroem yang dapat dimuat dalam jurnal ini meliputi bidang keilmuan Teknik Elektronika, Teknik Kendali, Sistem Tenaga, Telekomunikasi, Informatika, Sistem Distribusi. Makalah dapat berupa ringkasan laporan hasil penelitian atau kajian pustaka ilmiah. Makalah yang akan dimuat hendaknya memenuhi format yang telah ditentukan.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 145 Documents
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Sintesis CaTiO3 Berbasis Limbah Cangkang Telur Bebek Untuk Aplikasi Sel Surya Muhammad, Al Jalali; Wa Ode Sitti Ilmawati; Aslan Ndita
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.v7i2.6261

Abstract

Duck’s eggshell is one type of organic waste that has not been used optimally. Duck eggshell contain CaCO3 as a CaO source, so they are potentially processed as CaTiO3. The purpose of this study was to investigate the effect of sintering temperature on morphology, phase, functional groups, and optical properties of CaTiO3. The sintering temperatures were used in this research from 800oC, 900oC and 1000oC for 4 hours. SEM analysis show that there was the different of morphology properties to each samples. Homogeneity of CaTiO3 particles can be seen from spherical distribution of CaTiO3 particles, especially at 800oC. In this research was found orthorombic crystal structure of CaTiO3 to each sintering temperatures.According to the XRD patterns, it can be seen that there was a simillar patterns to each samples. Each peaks of CaTiO3 that formed on 2 (23,329o; 29,960o; 33,152o; 40,990o; 47,568o; and 49,211o) have the growth orientations respectively are (400), (510), (440), (444), (800), and (820). Particle size at sintering temperature of 800oC, 900oC and 1000oC respectively are 43,60438 nm, 33,43218 nm, and 29,35699 nm).
Perancangan Alat Pemantauan Konsumsi Listrik Multipoint Berbasis IOT untuk Meningkatkan Efisiensi Energi Charlie William; Hugeng; Lamto Widodo
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.v7i2.6287

Abstract

Konsumsi energi listrik yang tidak efisien dapat menyebabkan pemborosan daya dan peningkatan biaya operasional. Penelitian ini bertujuan untuk merancang dan mengimplementasikan alat pemantauan konsumsi listrik multipoint berbasis Internet of Things (IoT) yang mampu mengirimkan data penggunaan daya secara nirkabel dan real-time. Sistem dirancang menggunakan sensor PZEM-004T (Closed CT) sebagai pengukur daya, mikrokontroler ESP32 sebagai unit pemroses utama, modul NRF24L01 sebagai media komunikasi antar node, serta WiFi untuk konektivitas ke Google Spreadsheet sebagai basis data dan antarmuka pengguna daring. Proses penelitian meliputi tahapan perancangan perangkat keras, pemrograman sistem, integrasi modul, serta pengujian fungsionalitas pada dua skenario beban, yaitu kombinasi charger laptop dan 3D printer. Hasil pengujian menunjukkan bahwa sistem mampu memantau parameter listrik—tegangan, arus, daya aktif, energi, dan faktor daya—dengan akurasi tinggi dan latensi rendah. Pada pengujian pertama, Node 1 mencatat rata-rata 212,42 V dan 21,64 W, sedangkan Node 2 mencatat 211,81 V dan 35,59 W. Pada pengujian kedua, Node 1 menunjukkan daya rata-rata 35,55 W, sementara Node 2 sebesar 85,10 W. Sistem terbukti dapat bekerja stabil untuk pemantauan multipoint tanpa kabel tambahan, dengan kemampuan pencatatan data otomatis dan akses daring. Hasil penelitian ini menunjukkan bahwa rancangan alat ini efektif digunakan sebagai solusi monitoring energi berbasis IoT untuk mendukung efisiensi dan manajemen energi listrik di lingkungan rumah tangga maupun industri.
Optimalisasi Teknik Image Enhancement untuk Klasifikasi Varietas Apel Menggunakan SVM dan CNN Johan, Anju Alicia; Fitri, Zilvanhisna Emka; Imron, Arizal Mujibtamala Nanda; Arif, Praditya Zainal
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.v7i2.5513

Abstract

One of the largest export commodities in Indonesia is fruit commodities, one of which is apples. Apples have many varieties that differ in shape, color and size, which can cause identification and highlighting of apples to have limitations by requiring manual inspection from experts. This manual inspection is influenced by the expert's ability and experience in assessing the texture, color pattern, smell and characteristics of apples. In addition, the large diversity of apple varieties does not guarantee the completeness and ease of access related to information and data on apple varieties. The availability of this information is very important in supporting increased fruit production and determining superior apple varieties. So, a system is made that can classify apple varieties such as ana apples, manalagi apples, fuji apples, red delicious apples and rome beauty apples automatically. The apple variety classification methods used are SVM and CNN. The accuracy result of the SVM method is 94% based on texture feature parameters. While the CNN accuracy result is 100% Using learning rate 0.001 and epoh 20.
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.

Page 15 of 15 | Total Record : 145

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