Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Wood Research Journal : Journal of Indonesian Wood Research Society Wood Research Journal : Journal of Indonesian Wood Research Society Indonesian Journal of Forestry Research
Sofianto, Imran Arra'd
Unknown Affiliation
Agriculture, Biological Sciences & Forestry

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Prediction of Density in Standing Trees of Various Wood Species in Natural Forests Using Near-infrared Spectroscopy Sofianto, Imran Arra'd
Wood Research Journal Vol 14, No 1 (2023): Wood Research Journal
Publisher : Masyarakat Peneliti Kayu Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51850/wrj.2023.14.1.25-33

Abstract

Density plays an important role as basic information for applying wood as construction materials. Recent years, the application of near-infrared spectroscopy as non-destructive testing (NDT) has been promising. Density prediction for standing trees in huge variation trees and species of natural forest needs to be investigated using NDT as of eco-green harvesting. The combination of density information and near-infrared spectroscopy is enabled to build a prediction model. This research applied increment cores sampling for density prediction analysis using near-infrared spectroscopy method. The research combined increment cores samples from multiple wood species to be analyzed in one chemometrics analysis of cross-validation partial least squares regression (CV-PLSR) to build a prediction model of density.  The research resulted coefficient of determination for cross-validation (R2CV) of 0.76 with number of latent variable (LV) 10 from the 1st derivative with 13 smoothing-point spectra and wavelength of 1200 – 1800 nm as the best prediction model. The result seemed sufficient enough with those number of LV for this small tube wood sampling of increment cores from multiple wood species. This research proved that building a prediction model for multiple wood species is possible to be done.
Prediction of Density in Standing Trees of Various Wood Species in Natural Forests Using Near-infrared Spectroscopy Sofianto, Imran Arra'd
Wood Research Journal Vol 14, No 1 (2023): Wood Research Journal
Publisher : Masyarakat Peneliti Kayu Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51850/wrj.2023.14.1.25-33

Abstract

Density plays an important role as basic information for applying wood as construction materials. Recent years, the application of near-infrared spectroscopy as non-destructive testing (NDT) has been promising. Density prediction for standing trees in huge variation trees and species of natural forest needs to be investigated using NDT as of eco-green harvesting. The combination of density information and near-infrared spectroscopy is enabled to build a prediction model. This research applied increment cores sampling for density prediction analysis using near-infrared spectroscopy method. The research combined increment cores samples from multiple wood species to be analyzed in one chemometrics analysis of cross-validation partial least squares regression (CV-PLSR) to build a prediction model of density.  The research resulted coefficient of determination for cross-validation (R2CV) of 0.76 with number of latent variable (LV) 10 from the 1st derivative with 13 smoothing-point spectra and wavelength of 1200 – 1800 nm as the best prediction model. The result seemed sufficient enough with those number of LV for this small tube wood sampling of increment cores from multiple wood species. This research proved that building a prediction model for multiple wood species is possible to be done.
IDENTIFICATION OF LIGNOCELLULOSE-LIKE MATERIAL USING SPECTROSCOPY ANALYSIS Adi, Danang Sudarwoko; Fatriasari, Widya; Narto; Triwibowo, Dimas; Darmawan, Teguh; Amin, Yusup; Sofianto, Imran Arra'd; Pari, Rohmah; Agustiningrum, Dyah Ayu; Rahmanto, Raden Gunawan Hadi; Dewi, Listya Mustika; Himmi, Setiawan Khoirul; Djarwanto; Damayanti, Ratih; Dwianto, Wahyu
Indonesian Journal of Forestry Research Vol. 11 No. 2 (2024): Indonesian Journal of Forestry Research
Publisher : Association of Indonesian Forestry and Environment Researchers and Technicians

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59465/ijfr.2024.11.2.299-306

Abstract

Lignocellulose materials, such as bamboo, rattan, and wood, have been largely used for furniture and crafts. On the other hand, the utilization of lignocellulose-like materials, which have a similar texture and appearance to those from nature, has been increasing recently due to their superior durability. This research aimed to identify the lignocellulose-like material using spectroscopy analysis, such as Raman and Near Infrared (NIR) which is well-known as a non-destructive, quick, and accurate approach for material identification. We investigated 4 types of lignocellulose-like materials that were provided by Dewan Serat Indonesia (The Indonesian Fiber Council) from an industry that produces them. The NIR analysis was performed at wavenumbers 10,000-4,000 cm-1. The natural lignocellulose (bamboo and wood) and the polymers (polyethylene and polyproline) were used as standards. Raman analysis was further employed to identify the composition of selected lignocellulose-like materials by comparing their spectra with the library software. The results showed that the original NIR spectra of lignocellulose-like and those natural materials were different, indicating that the NIR analysis can differentiate those materials. The NIR spectra of lignocellulose-like materials were similar to those of polyethylene spectra. Those lignocellulose-like were also identified as polyethylene due to the similarity of the Raman spectra and their library spectra.
Co-Authors Danang Sudarwoko Adi Djarwanto Dyah Ayu Agustiningrum, Dyah Ayu Himmi, Setiawan Khoirul Listya Mustika Dewi Narto Pari, Rohmah Rahmanto, Raden Gunawan Hadi Ratih Damayanti Teguh DARMAWAN Triwibowo, Dimas Wahyu DWIANTO Widya FATRIASARI Yusup AMIN