Article Per Year (5 Year)
p-Index From 2021 - 2026
1.203
P-Index
This Author published in this journals
All Journal Komunikasi Fisika Indonesia Bulletin of Electrical Engineering and Informatics Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse) Science, Technology, and Communication Journal
Minarni Shiddiq, Minarni
Unknown Affiliation
Aerospace Engineering Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Science, Technology, and Communication Journal

 1 
Wavelength dependence of optical electronic nose for ripeness detection of oil palm fresh fruits Husein, Ikhsan Rahman; Shiddiq, Minarni; Sari, Dewi Laila; Putri, Annisa
Science, Technology and Communication Journal Vol. 2 No. 3 (2022): SINTECHCOM Journal (June 2022)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v2i3.212

Abstract

Electronic noses have been developed as an artificial sense to imitate the human nose based on volatile gases. They have been used in agriculture to monitor and predict fruit qualities such as ripeness and chemical contents. Electronic noses with semiconductor gas sensors have a limitation of volatile gases detected. Therefore, optical electronic noses using an output coupler become an alternative due to the wavelength dependency of the gas types. The ripeness of oil palm fresh fruit bunches (FFBs) is one of the main factors in determining the quality of crude palm oil. Electronic detection is preferable to substitute the manual methods for ripeness detection. This study built an optical electronic nose and analyzed the wavelength dependence on the detection performance. The electronic nose consisted of an infrared LED and a photodiode enclosed in a chamber, a microcontroller, and a sample chamber. We tested four infrared LEDs with 760, 780, 840, and 910 nm wavelengths. The samples were fruitlets taken from oil palm FFBs, previously categorized as unripe, ripe, and overripe. The fruits were grounded, inserted into the sample chamber, and preheated to increase the volatile gas concentration.  Trapezoid areas represented the time-varying output voltages for each LED. The results showed that overripe fruits had slightly higher trapezoid areas. LED of 840 nm wavelength obtained higher trapezoid areas. LED of 780 nm was the best candidate for the electronic nose due to linearity in increasing trapezoid areas. The results showed the potential of the optical electronic nose for oil palm fruits.
Fluorescence spectrum analysis on leaf and fruit using the ImageJ software application Defrianto, Defrianto; Shiddiq, Minarni; Malik, Usman; Asyana, Vepy
Science, Technology and Communication Journal Vol. 3 No. 1 (2022): SINTECHCOM Journal (October 2022)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v3i1.218

Abstract

In this study, ImageJ has been used to process fluorescence spectroscopic images of spinach leaf treated with three variations of sunlight. In addition, apples and tomatoes are also used in imaging by treatment immersed in hot water, pierced, and pressed. Leaf and fruits are illuminated by laser diodes and LEDs of different wavelengths. ImageJ is used to calculate the RGB and gray values of the image with two segmentations, namely the intact image and the threshold. The results show that the thresholding method gives the best results because it automatically reduces the image background. In addition, the threshold background can also be easily set in this imaging. For the spinach leaf experiment, LED with a wavelength of 680 nm showed significant differences in each treatment of sunlight intensity. Meanwhile, in the apple and tomato experiment, the diode laser with a wavelength of 405 nm showed significant results. Both types of fruit with this puncture treatment turned out to provide higher intensity than pressed fruit.
Physical properties of oil palm fresh fruit bunch varieties Shiddiq, Minarni; Hamzah, Yanuar; Nasir, Zulfa; Amanullah, Farid; Rabin, Mohammad Fisal; Dasta, Vicky Vernando
Science, Technology, and Communication Journal Vol. 6 No. 1 (2025): SINTECHCOM Journal (October 2025)
Publisher : Lembaga Studi Pendidikan dan Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v6i1.336

Abstract

Identification of oil palm fresh fruit bunches (FFB) based on variety is a crucial step in sorting and grading FFBs to produce good-quality crude palm oil (CPO). Most palm oil mills receive two varieties of FFBs at the reception stations, Tenera and Dura, and only a certain percentage of the Dura variety is allowed in a transporting truck. The conventional identification is destructive, cutting several fruits off an FFB bunch and checking for fruit Mesocarp and shell thickness. The method suffers a high increase in free fatty acid (FFA) content. This study is a preliminary study using computer vision and image processing to differentiate the two varieties based on their physical properties. The samples consisted of 20 Dura and 20 Tenera FFBs, 10 unripe and 10 ripe FFBs. The FFB images were acquired for both front and back sides using a color CMOS camera. ImageJ software was used to obtain the number of outer fruits and bunch surface area, used to calculate fruitlet density. Both varieties are also compared based on mass and by red, green, and blue (RGB) intensities. The results were compared to the results measured manually. The results showed that the Tenera variety exhibited higher fruit density, fruitlet count, RGB intensity compared to the Dura variety. Both varieties have higher correlations between fruit density and their masses. These results show the potential of computer vision and image processing methods to differentiate Tenera and Dura varieties, used for sorting and grading oil palm FFBs.
Co-Authors Adhy Prayitno, Adhy Amanullah, Farid Anand, Barri Annisa Putri Arpyanti, Nisa Asyana, Vepy Ayunita, Dyna Dasta, Vicky Vernando Defrianto Defrianto Dodi Sofyan Arief, Dodi Sofyan Feri Candra Harmailil, Ihsan Okta Husein, Ikhsan Rahman Midriem Mirdanies Nasir, Zulfa Rabin, Mohammad Fisal Rabin, Mohammed Fisal Rahmondia N. Setiadi Roni Salambue Saktioto Saktioto Sari, Dewi Laila Usman Usman Wahyudi, Dilham Wardana, Fiqra Yanuar Hamzah