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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics IJOG : Indonesian Journal on Geoscience Indonesian Journal on Geoscience JAREE (Journal on Advanced Research in Electrical Engineering) Indonesian Journal on Geoscience Jurnal Sistim Informasi dan Teknologi
Kusuma, Hendra Siswanto
Institut Teknologi Sepuluh Nopember
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering

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Journal : JAREE (Journal on Advanced Research in Electrical Engineering)

 1 
Low Cost Optical-electronic Sensor Development Based on Raman Spectroscopy for Liquid Luqman Aji Kusumo; Totok Mujiono; Hendra Kusuma
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 4, No 2 (2020): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25796216.v4.i2.127

Abstract

Spectroscopy is a method that used to identifychemical structure of substances using its spectral patterncharacteristics. Optical spectroscopy term can be applied to anykind of optical photon interactions with matter. Ramanspectroscopy essentially shows spectral response like thewavelength of scattered light is shifted regarding initializingexcitation wavelength. In this paper, we propose a design of lowcost optical-electronic sensor based on Raman spectroscopy.This low cost optical-electronic sensor employs a violet-blue 405nm wavelength laser diode, a biconvex lens with 5 cm diameterand focus point, a test tube, and a Complementary Metal OxideSemiconductor (CMOS) sensor. We tested this low cost opticalelectronic sensor based on Raman spectroscopy in darkcondition. Combination of these hardware and components canprovide measurement result to any liquid sample. From thisexperiment, even all liquid samples that used to test thiscombination of hardware and components are transparent, theystill have different Raman spectra. This combination ofhardware and components can be implemented into someapplication for instance body liquid measurement such as blood.In specific application, we need to employ data analysis and abunch of data set which are organized into three different groupsuch as training data, validation data, and test data group,combined with this developed instrumentation.Keywords: CMOS sensor, laser diode, Raman scattering, Raman spectroscopy, spectroscope.
Object Extraction Using Probabilistic Maps of Color, Depth, and Near-Infrared Information Muhammad Attamimi; Kelvin Liusiani; Astria Nur Irfansyah; Hendra Kusuma; Djoko Purwanto
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 4, No 1 (2020): April
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25796216.v4.i1.106

Abstract

Object extraction is one of the important and chal-lenging tasks in the computer vision and/or robotics ? elds.This task is to extract the object from the scene using anypossible cues. The scenario discussed in this study was the objectextraction which considering the Space of Interest (SOI), i.e.,the three dimensional area where the object probably existed.To complete such task, the object extraction method based onthe probabilistic maps of multiple cues was proposed. Thanksto the Kinect V2 sensor, multiple cues such as color, depth, andnear-infrared information can be acquired simultaneously. TheSOI was modeled by a simple probabilistic model by consideringthe geometry of the possible objects and the reachability of thesystem acquired from depth information. To model the color andnear-infrared information, a Gaussian mixture models (GMM)was used. All of the models were combined to generate theprobabilistic maps that were used to extract the object fromthe scene. To validate the proposed object extraction, severalexperiments were conducted to investigate the best combinationof the cues used in this study.Keywords: color information, depth information, near-infrared information, object extraction, probabilistic maps.
Co-Authors Adi Soeprijanto Astria Nur Irfansyah Djoko Purwanto Fina Riandra Hasby Fahrudin Imam B. Sosrowidjojo Kelvin Liusiani Kharis Sugiarto Luqman Aji Kusumo Muhammad Attamimi R.Y. Perry Burhan, R.Y. Perry Riandra, Fina Riandra, Fina Sosrowidjojo, Imam B. Sosrowidjojo, Imam B. Totok Mujiono, Totok Tri Arief Sardjono Wirawan Wirawan Zetra, Yulfi