Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal EECCIS Jurnal Qua Teknika
Haitsam, Haitsam
Unknown Affiliation
Engineering

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

Found 1 Documents
Search
Journal : Jurnal Qua Teknika

 1 
Deteksi Manusia dengan Sinyal Bioelectric Tanaman Haitsam, Haitsam
Jurnal Qua Teknika Vol 15 No 01 (2025): Maret 2025
Publisher : Universitas Islam Balitar Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/quateknika.v15i01.4061

Abstract

This research aims to utilize the bioelectric potential of plants as a tool to detect human presence in the surrounding area. The potential bioelectric signals of plants are recorded using a data logger and analyzed with the help of a computer for identification. Previous methods used time series models and Z-value tests, but challenges in achieving accurate estimates remain. We use Recurrent Neural Networks (RNN) to handle the processing of large datasets in this study. The experimental results show that the RNN model is very effective and achieves a high level of accuracy, with a perfect accuracy of 1.00 from the total duration of each class is 62030 seconds (379610 samples).303688 data samples are used as train datasets, while the others (75922 samples) are used as validation datasets This shows that RNN has great potential in processing plant bioelectric data to detect human presence with very high accuracy.
Co-Authors Permatasari, Delila Cahya Subairi Subairi Wahyu Dirgantara Yandhika Surya Akbar Gumilang Zahroya J.M.F. , Isvine