Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Melinda
Universitas Syiah Kuala
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Engineering Public Health Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Increasing Teacher Professionalism at SMK Negeri Penerbangan Aceh Through Training Scientific Writing and Scientific Work Development: Meningkatkan Profesionalisme Guru di SMK Negeri Penerbangan Aceh Melalui Pelatihan Tata Tulis Ilmiah dan Pengembangan Karya Ilmiah Yuwaldy Away; Saminan; Rika Sri Utami; Safrizal Razali; Melinda; Muslimsyah
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 7 No. 3 (2023): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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

Abstract

SMK Negeri Penerbangan Aceh is one of the educational institutions in the Aceh region that focuses on vocational education. In this community service initiative, the team identified the challenges faced by teachers at this school, as the lack of motivation and time constraints in writing academic papers. In an effort to address these issues, the team designed and implemented a training program that encompasses academic writing techniques and the use of research software. The evaluation results show a significant improvement in the motivation, self-confidence, and knowledge of teachers related to academic paper writing. This program also facilitates collaboration among teachers, members of the team, and guest speakers. This collaboration provides emotional support and a deeper understanding of research strategies and the application of technology in developing academic papers. The contribution of this community service initiative aids teachers at SMK Negeri Penerbangan Aceh in enhancing their ability to write academic papers, which supports the requirements for promotion and professional career advancement. This training program also has the potential to be implemented in other educational institutions facing similar challenges in improving teacher professionalism.
Comparative Analysis of Multispectral Image Classification Based on EfficientNetB0, ResNet152, DenseNet161, DenseNet121, and HSV Segmentation Melinda; Yudha Nurdin; Alfatirta Mufti; Syifa Anzella; Siti Rusdiana; Donata D Acula
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 1 (2026): February 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i1.6873

Abstract

This study established a classification system based on Convolutional Neural Networks (CNNs) to detect High-High Fluctuation (HHF) patterns in multispectral data derived from pure water (H2O) and a water-sodium hydroxide (NaOH) solution. This study combines HSV color-space-based segmentation to identify areas with the highest signal amplitude, thereby enhancing the feature extraction of the CNN model. Data augmentation techniques, including random flipping, rotation, and color jitter, along with training parameters such as a learning rate of 0.0001 and a batch size of 32, have been shown to effectively improve model generalization and reduce overfitting. Four different CNN architectures were evaluated: ResNet-152, DenseNet-161, DenseNet-121, and EfficientNet-B0. As a result, ResNet152 achieved the highest accuracy of 97.6%, attributed to its network depth and residual connections that effectively address the vanishing gradient problem. DenseNet161 and DenseNet121 also demonstrated competitive performance, achieving accuracies of 96.7% and 96.2%, respectively, which is supported by their dense connectivity that optimizes feature reuse. Conversely, EfficientNetB0, despite showing lower accuracy (90%), provides significant computational efficiency, making it suitable for real-time applications. These results underscore the importance of selecting a CNN architecture that balances accuracy and efficiency for multispectral data classification.
Co-Authors Alfatirta Mufti Donata D Acula Muslimsyah Rika Sri Utami Safrizal Razali Saminan Siti Rusdiana Syifa Anzella Yudha Nurdin Yuwaldy Away