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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Indonesian Journal of Electrical Engineering and Computer Science
Ismail, Nurlaila
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Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Statistical analysis of agarwood oil chemical compound exists in four species of Aquilaria Zaidi, Amir Hussairi; Al-Hadi, Anis Hazirah ‘Izzati Hasnu; Huzir, Siti Mariatul Hazwa Mohd; Yusoff, Zakiah Mohd; Ismail, Nurlaila; Almisreb, Ali Abd; Tajuddin, Saiful Nizam; Taib, Haji Mohd Nasir
International Journal of Advances in Applied Sciences Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i3.pp727-732

Abstract

Aquilaria, renowned for its agarwood, and valued for its aromatic wood and rich resin, finds use in cosmetics, fragrances, incense, and medicine. Identifying the agarwood-producing species among 21 species of Aquilaria is challenging. This study analyzes chemical compounds in agarwood oil from 4 Aquilaria species: Aquilaria beccariana, Aquilaria crassna, Aquilaria malaccensis, and Aquilaria subintegra using gas chromatography-flame ionization detector (GC-FID). Statistical analysis explores compound abundance, employing methods like mean and Z-score tests. This analysis summarizes those 14 compounds that are consistently present based on zero and non-zero observations, and the Z-score test highlights five chemical compounds, with three compounds appearing in both analyses. These compounds can serve as a reference for future studies on Aquilaria species and agarwood oil, enhancing classification efforts.
Chemometric classification and authentication of four Aquilaria species from essential oil profiles using GC-MS/GC-FID and ANN Noramli, Nur Athirah Syafiqah; Ahmad Sabri, Noor Aida Syakira; Roslan, Muhammad Ikhsan; Ismail, Nurlaila; Mohd Yusoff, Zakiah; Taib, Mohd Nasir
International Journal of Advances in Intelligent Informatics Vol 11, No 4 (2025): November 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i4.2141

Abstract

Agarwood derived from Aquilaria species is among the most valuable aromatic resources, yet frequent species misidentification hampers conservation efforts and compliance with trade regulations. This study applied a chemometric ANN framework to classify four Aquilaria species (A. malaccensis, A. beccariana, A. subintegra, and A. crassna) based on essential oil composition. A total of 720 samples (180 per species, each analyzed in triplicate) were extracted via hydro-distillation and profiled using GC–MS coupled with GC–FID. Six compounds were consistently detected, and three (δ-guaiene, 10-epi-γ-eudesmol, γ-eudesmol) were retained for classification based on ≥95% detection frequency and >0.2% relative abundance. Pearson correlation guided feature selection, and ANN models were trained using both a 70:15:15 train–validation–test split and stratified 5-fold cross-validation with 1000 bootstrap resamples. As shown in Tables 5 and 6, the optimized network achieved near-perfect performance with mean accuracy of ~99.8% (95% CI: 99.6–100.0) and precision, recall, and F1-scores all exceeding 99.5%, while bootstrapped confidence intervals were tightly bounded at 100%, confirming robustness against data leakage. These findings demonstrate that correlation-guided feature selection combined with ANN modeling enables reproducible and highly accurate species authentication, offering a practical framework for integration into agarwood quality control, conservation monitoring, and international trade compliance.
Co-Authors Abdullah, Hasnain Ahmad Sabri, Noor Aida Syakira Ahmad, Azizah Al-Hadi, Anis Hazirah ‘Izzati Hasnu Almisreb, Ali Abd Bakar, Zahari Abu Che Hassan, Mohammad Arif Fahmi Haron, Mohamad Hushni Haron, Mohamad Hushnie Hasnu Al-Hadi, Anis Hazirah 'Izzati Huzir, Siti Mariatul Hazwa Mohd Mohamad Noor, Norhayati Mohd Huzir, Siti Mariatul Hazwa Mohd Kasim, Linda Mohd Nasir Taib Mohd Yusoff, Zakiah Nik Kamaruzaman, Nik Fasha Edora Noramli, Nur Athirah Syafiqah Nordin, Siti Aminah Othman, Norhalida Roslan, Muhammad Ikhsan Syafiqah Noramli, Nur Athirah Taib, Haji Mohd Nasir Tajuddin, Saiful Nizam Yassin, Ahmad Ihsan Mohd Yusoff, Zakiah Mohd Zaidi, Amir Hussairi