Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Electrical Vocational Education and Technology
Mawarid, Mahran
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Physics

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

Found 2 Documents
Search

 1 
Sistem Pengelolaan Akses Pintu Otomatis Berbasis Pengenalan Wajah di SMK Taruna Bhakti Depok Mawarid, Mahran; Djaohar, Mochammad; Hanifah Yuninda, Nur
Journal of Electrical Vocational Education and Technology Vol. 8 No. 2 (2025): Journal of Electrical Vocational Education and Technology, Volume 8 Issue 2, De
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JEVET.0082.01

Abstract

Abstrak Penelitian ini membahas pengelolaan akses Storage Room Teknik Elektronika di SMK Taruna Bhakti Depok yang masih menggunakan kunci manual, sehingga berisiko kehilangan, duplikasi, dan kesulitan manajemen akses. Kelemahan ini mengganggu keamanan aset dan operasional pembelajaran. Tujuan penelitian adalah merancang dan menguji sistem pengelolaan akses pintu berbasis pengenalan wajah untuk meningkatkan keamanan dan efisiensi akses. Penelitian ini dilakukan dengan menggunakan metode rekayasa teknik dengan jenis rekayasa maju (Forward Engineering). Penelitian ini mengevaluasi kinerja sistem pengelolaan akses berbasis pengenalan wajah menggunakan algoritma LBPH (Local Binary Patterns Histogram). Pengujian dilakukan dengan menggunakan 10 individu (5 terdaftar dan 5 tidak terdaftar) dengan pengujian sebanyak 5 kali pada masing-masing individu. Hasil pengujian menunjukkan akurasi sistem berhasil membuka pintu dengan persentase 100%. Rata-rata waktu proses pengenalan hingga membuka pintu adalah 6,54 detik, mencerminkan efisiensi sistem. Temuan ini menunjukkan bahwa sistem ini dapat diandalkan untuk pengelolaan akses yang aman dan cepat. Abstract This research discusses the access management of the Electronics Engineering Storage Room at SMK Taruna Bhakti Depok which still uses manual keys, thus risking loss, duplication, and access management difficulties. These weaknesses interfere with asset security and learning operations. The research objective is to design and test a face recognition-based door access management system to improve security and access efficiency. This research was conducted using engineering methods with the type of forward engineering. This research evaluates the performance of face recognition-based access management system using LBPH (Local Binary Patterns Histogram) algorithm. Tests were conducted using 10 individuals (5 registered and 5 unregistered) with 5 times testing on each individual. The test results show the accuracy of the system successfully opens the door with a percentage of 100%. The average time from the recognition process to opening the door was 6.54 seconds, reflecting the efficiency of the system. The findings show that the system is reliable for secure and fast access management.
Integration of Portable NIRS Spectroscopy with the Internet of Things (IoT) for a Rice Quality Monitoring System in Storage Warehouses Ana, Ayu Putri; Mulyanti, Dwi Retno; Alfikri, M Reza; Mawarid, Mahran
Jurnal Penelitian Pendidikan IPA Vol 12 No 1 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i1.14038

Abstract

Rapid and non-destructive monitoring of rice quality during storage is essential for supporting effective warehouse management. This study aims to develop and evaluate the integration of Portable Near-Infrared Spectroscopy (NIRS) with an Internet of Things (IoT) framework for real-time rice quality monitoring. A quantitative experimental approach was employed by acquiring NIRS spectra in the wavelength range of 740–1070 nm from fresh and aged rice samples. The spectral data were automatically transmitted via the IoT system to a centralized server for storage and analysis. Rice quality parameters, including moisture, fat, and protein content, were predicted using a Partial Least Squares Regression (PLS-R) model based on raw spectra without spectral pretreatment. The results indicate that the PLS-R model achieved good predictive performance for moisture and fat content, with validation correlation coefficients (R) ranging from 0.87 to 1.00 and Residual Predictive Deviation (RPD) values of 1.11–3.65 for moisture and 3.70–4.65 for fat in both fresh and aged rice samples. In contrast, protein prediction showed limited accuracy, particularly in fresh rice samples with an RPD value of 1.79. The IoT system primarily functioned as a real-time data acquisition and transmission platform, enabling integrated rice quality monitoring. Overall, the findings confirm that NIRS–IoT integration is feasible for monitoring rice quality based on moisture and fat content during storage.
Co-Authors Ana, Ayu Putri Djaohar, Mochammad Hanifah Yuninda, Nur Mulyanti, Dwi Retno