This PDF file contains the front matter associated with SPIE Proceedings Volume 11044 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

The aim of this study is to develop an automatic tissue characterization system, based on Optical Coherence Tomography (OCT) images, for smart laser surgery. OCT is rapidly becoming the method of choice for investigating thin tissues or subsurface imaging. In smart laser surgery, OCT could be used to indicate which tissue is being irradiated, thereby preventing the laser from ablating critical tissue such as nerves and veins. Automatic tissue characterization based on the OCT images should be sufficient to give feedback to the laser control. In this study, two main neural networks were trained to classify texture and optical attenuation of three different tissues (bone, fat, and muscle). One neural network texture classifier was trained to differentiate between patterned and patternless images. The other neural network was trained to classify patternless images based on their attenuation profile. The two neural networks were stacked as a binary tree. The ability of this hybrid deep-learning approach to characterize tissue was evaluated for accuracy in classifying OCT images from these three different tissues. The overall (averaged) accuracy was 82.4% for the texture-based network and 98.0% for the attenuation-based (A-Scan) network. The fully connected layer of the neural network achieved 98.7% accuracy. This method shows the ability of the neural network to learn feature representation from OCT images and offers a feasible solution to the challenge of heuristic independent tissue characterization for histology and use in smart laser surgery.

A study on development of non destructive and low cost device has been conducted to predict cavendish banana ripening stage by using visible lights reflectance method. The system uses green (500-560 nm, peak at 533 nm), orange (580-610 nm, peak at 597 nm), and red (600-650 nm, peak at 632 nm) lights which has high corellation to spectral analysis by spectrophotometer at 0.91, 0.76 and 0.83 for red, orange and green lights respectively. A classification of ripening stages of banana has been made based on the lights reflectance of peel. The highest accuracy is obtained by the red light at 100%, 92%, 33% and 75% for predictions of stage 4, 5, 6 and 7 respectively compared to visual assessment of standard color chart.

Information on mangrove species plays crucial role for sustainable management of coastal ecosystems. However, the current in-depth data acquisition for sustainable management of coastal ecosystems is still collected manually. The increased demand to obtain mangrove environmental data in a short time and at affordable cost has encouraged our research to develop an automatization method for determining the species based on the images of mangrove leaf. In this paper the authors used a deep learning method that uses the Convolutional Neural Network (CNN) to overcome manual leaf sample identification during image recognition process. CNN is used to process the machine learning on a personal computer. Stages on CNN were data input, preprocessing and training. CNN was implemented by using tensorflow libraries through the transfer learning process to recognize three mangrove species of northern coast of Probolinggo, East Java, Indonesia. The recognition process is based on images of the mangrove leaf shape. This method was simple and can be reproduced by anyone without the need for in-depth computer programming knowledge. In a relatively short time, the method has been proven to give high accuracy of predicted results. Field test showed that this method can determine and distinguish the leaves of the three species of mangrove well. In the future this method will be developed to identify mangrove plants using Unmanned Aerial Vehicle (UAV).

Profile measurement system based on optical method is becoming widely applied. Among many methods that has been developed, Digital Fringe Projection Profilometry (DFPP) technique provides high resolution results. In processing the 2D image to 3D image, DFPP goes through some steps, which are phase extraction, phase unwrapping, and baseline offset removal. The most important step is phase extraction because this part will extract the deformed fringe information that can determine the accuracy of the 3D reconstruction results. In this paper, there are two methods of phase extraction that is observed, which are phase shifting interferometry and spatial carrier interferometry. Experiments are done with a specific made object that has 3 depths and 2 types of indentations. The results of each phase extraction methods are compared on not only how they reconstruct the flat part and the indentation type, but also how they restore the depth information.

Wrinkle is one of skin properties used to indicate aging or environment damage in human body. This feature can be assessed through contact and non-contact methods. Dermatology industry often utilizes tools such as dermatoscopy, however it lacks the ability to yield wrinkle's depth and requires contact with skin, which are not preferable because possibility of deforming skin's natural texture. These lead to the development of digital fringe profilometry which utilize phase-shifted fringes being projected to the skin. This method can satisfy both wrinkle's depth and non-invasive measurement.

A novel system of digital fringe profilometry technique is presented, which used newly improved camera technology preferred by the dermatological industry and a projector, both are commercially available, with new configuration suitable for skin measurement. The system is configured with certain height and angle to respectively project fringes and obtain images. Images will later be processed using phase shifting interferometry (PSI) and global phase unwrapping. The processing system will produce wrapped phase and absolute phase value. In order to prove system's feasibility, experiment was done by sampling two areas from three fingers. Quantitative analysis was done through statistical paired T-Test to see the system ability to acknowledge significant difference of two groups' skin topographic condition. Based on the T-Test, P value that was obtained is 0.003915, which concluded that the system is capable of quantifying two different skin topographic conditions and provide significantly different results.

Chlorophyll content in plants is of particular important green pigment that plays important role in photosythesis. Insufficient chlorophyll concentration in rice plants would influencing their growth, which will affect the yield as well as quality of harvested rice. Regular and periodic monitoring of chlorophyll content in leaves is essential to maintain the health of cultivated paddies, since leaf chlorophyll is mostly used as index to diagnose diseases and getting the status of nutrient and nitrogen in plants. In this paper, efforts to developed and calibrated a low cost but accurate Raspberry-Pi camera-based Chlorophyll meter is described. This kind simple measuring instruments will be useful to help Indonesian paddy farmers, that are mostly live below the poverty lines, to improve yield of their harvest product.

Delivering process of liquid fuels from refinery units into storage plants is no longer using transportation (trains or trucks) because it is so costly. So pipes are used for this delivering process. Densitometer is used to determine the time when valve close or open manually for guiding each fuel to each storage tank. Density parameter is not suitable to be the main parameter because the densities of each oil are almost the same. Therefore it needs to design an innovation of Raspberry-Pi's liquid fuel detection system to improve detection accuracy. in this research, fuel color data acquisition process on a transparent pipe on HSV color space (hue, saturation, value) are done by webcam then data processed by Raspberry - Pi to define the fuel type. Script programming has written in Python 2.7 and image processing is done with OpenCV library. Optimal intensity lighting at 25 lux and minimum at 8 lux. Each fuel and interface can be well known. The values, accuracy, standard deviation of hue and saturation readings respectively for pertamax are 98 - 100, 98.8%, 0,3 and 120 - 140, 98.48%, 3,07, for diesel are 19 - 25, 99.12%, 0,41 and 110 - 130, 97.35%, 3,79, and for kerosene are 92 – 100 , 98.93%, 1,38 and 30 - 45, 92.55%, 4,63. Determining the fuel concentration on the interface can’t be done because there is the same value of HSV bit.

Pothole detection system based on digital image correlation had been made using Kinect sensor that could detect and quantified pothole dimensions such as depth, area, volume and position. Pothole detection was start with normalization process on depth image from the pothole that was used as a quantifying object. Then thresholding was done on the normalized image in order to separate between pothole and its background. Dimension quantification was done by making the work model from the sensor characterization result. Next, validation system process was done by testing the artificial pothole with the depth variation of 2 cm, 4 cm, 6 cm, 8 cm, 10 cm and 12 cm, every depth variation had each given diameter of 5 cm, 10 cm, 15 cm, 20 cm, and 25 cm. Based on the results of the validation, the system has an error value of less than 7% on the hole diameter range of 5-25cm with a depth range of 6-12 cm. The depth resolution of the system is 0.43 cm while the system spatial resolution depends on the distance between sensor and the quantifying object, for sensor system with distance span of 120 cm would have spatial resolution on horizontal and vertical axis of 0.21 cm and 0.22 cm respectively.

People with visual disability unable to recognize the nominal of banknotes in conducting economic life, hence, rely on their touch and hear senses to recognize the banknotes. In this work, we investigated the LDR sensor to detect the nominal value of banknotes with voice output. It was found that the error rate 100% for IDR 2000, IDR 10000, IDR 100000, and IDR 50000, 75% error rate was for IDR 5000 and IDR 2000, and 50% error rate for IDR 1000.

Water turbidity testing is needed in the process of water treatment for water to be consumed. Therefore, an effort is needed to develop a tool that serves as a detector of turbidity of water, in order to set a standard parameters of water clarity that can be consumed by the community. In this research, the physics parameters related to water consumption, ie turbidity or turbidity are discussed. Turbidity describes the optical properties of water determined by the amount of light scattered by the materials present in the water. The direction of the transmitted light path will change when light touches the particles in the water column. The particle size affects the value of turbidity, where in the testmilk powder and coffee are suspended matter that causes water turbidity. The particle size of milk powder is smaller than coffee, therefore, the light is more scattered in milk solution than with turbidity value about 3.01 NTU while coffee 2.67 NTU at 5 gr / l solution.

Tomatoes that are being distributed to the market require certain level of maturity. Determination of maturity requires classification. Automatic tomato classification is the process of sorting tomatoes into different classes using machine vision and image processing. Tomatoes have two types of pigments used for photosynthesis. In the early stage of maturity, tomatoes are green color due to high chlorophyll level. As the tomatoes mature, chlorophyll will dissolve and begin to disappear. The loss of chlorophyll, the lycopene that has a red color will be clearly visible on the tomatoes. The color system used is RGB, then threshold, color analysis, and the final step is the perception of color. It can be concluded that image processing can be used to determine the selection of tomato maturity based on the color. Variables that can be used to determine the maturity level of tomatoes is the ration of the RGB value obtained by the image.

In this paper, we presented the use of SMS fiber structure and an OTDR interrogator for intrusion detection. A long of MMF section in SMS fiber structure was employed as a sensing area which an intrusion activity can induce a displacement to the MMF section. It was demonstrated that the given displacement on the MMF section can influence the reflective power on both fiber splice event and fiber-end event. It was shown that the reflective power on fiber-end event more sensitive to the splice event. The proposed scheme offers simpler configuration for the detection in the MMF section.

Currently a combination of fluorescence microscopy with spectroscopic analysis in a balance way has played an important role in providing new and exciting information for the in vivo study of cell, such as diatoms, photosynthetic marine microorganisms. Diatoms contain photosynthetic pigments, carotenoid and chlorophylls molecules, in their machinery to harvest the sunlight energy for growth. Lacking of these pigments might influence to the overall metabolisms of the cells. Here we reported our work to construct a simple homebuilt confocal fluorescence spectromicroscopy to study the cells of Chaetoceros muelleri diatom. The setup was design to get simultaneous data of the image of the single fluorescence cell and the emission spectrum of it.

Bean's moisture content is one of important parameters in determining the quality of the processed agricultural products, particularly for coffee beans, where moisture content will be a determining factor in the aroma and the taste of roasted coffee products. In this paper efforts to quantify the moisture content of the examined coffee bean based on LIBS spectra, as one of coffee bean's quality parameters that can be extracted at once from single shot LIBS measurement.

The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of invivo skin chromophores. We have successfully developed an MSI system with a new approach. Our MSI system captures 11 mono-spectral images of human skin which is too little for providing an accurate diagnostic information. We need something to reconstruct the 11 monoband data sets to the wider range hyperspectral data sets. In this paper, we proposed a method to build a hyperspectral reflectance cube based on artificial neural network (ANN) algorithm. ANN is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure the involves acquisition, by a spectrometer. This neural network is then used to retrieve a hyperspectral reflectance cube between 380 and 880 nm with a 5 nm resolution. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). The reconstruction results are very good. The average GFC was 0,9988 and the average RMSE was 0.023. We also tested the quality of reconstruction with healthy skin data sets and the results are good enough. For skin data sets, the average GFC was 0.9855 and the average RMSE was 0.0608.

Olive oil is one of the oil product that is most adulterated by cheap substance such as grease, tallow, and lard. In the other hand, tapered POF is widely used for many sensing applications, particularly for chemical and biosensor. In this paper, the spectroscopy-based tapered POF for detecting lard adulteration in olive oil was investigated experimentally. The taper length and taper waist diameter were varied to evaluate the spectra characteristic of the tapered POF. The samples were made of olive oil adulterated by lard with the concentration of 0 – 5%. The result showed that the changes in taper geometry led the changes in some peaks. The new peaks were introduced at the wavelength of 650, 745, and 930 nm. However, the change of the samples caused the wavelength shifting at the range of 920 – 930 nm. As the lard concentration in olive oil increased, the intensity at the wavelength of 930 nm decreased. Hence, the wavelength of 930 nm is potential to be utilized in intesity-based tapered POF for detecting lard adulteration.

An increased level of calcium in saliva due to cigarettes consumption can be analyzed using LIBS (Laser-Induced Breakdown Spectroscopy). The saliva was collected from light smokers, moderate smokers and heavy smoker. The LIBS system used the optimum conditions at 0.5μs time delay, 100 mJ laser energy and 3 accumulation of shoots, and in an atmospheric gas conditions. The elements present in the saliva are 99% composed of water and some anorganic elements such as sodium, potassium, magnesium, calcium, fluorine. Ca element (Calcium) is a prominent element contained in saliva that acts mostly in buffering process of the oral cavity. The result data showed that an increase of cigarette consumption per day was followed by the increase of Ca emission intensity at a wavelength 422 nm. There was a 30% increase in Ca emission intensity of light smoker group compared to non-smoker group, a 37% increase in Ca emission intensity of the moderate smoker group compared to the non-smoker group, and 51% in Ca emission intensity of the heavy smoker group compared to the non-smoker group. This result indicates that a demineralisation (solubility) process has occurred which is related to a dissolution of Ca element in tooth lattice into saliva.

The quantitative evaluations were carried out in NIR spectroscopy that was implemented for monitoring and predicting the concentration of glucose samples. The collected absorbance data was preprocessed in developing PLS model before calibration using Savitzky-Golay filter. The spectrum was corrected by subtracting the offset of the regression to the absorption value and dividing this difference by the slope using Leave One Out Cross Validation (LOOCV) of the training set to determine the optimum number of PLS components. The Samples of glucose solution consist of 21 different molarity from 3000 to 5000 mg/dl with the interval of 100 mg/dl in step. Results obtained shown the linear dependency of the reference and predicted glucose concentration, with RMSECV and R2CV value are 104.92 mg/dl and 0.9728, respectively. The RMSECV shown the lowest error present and R2CV were close to one, indicates that the PLS model suited to accurately predict the variability glucose concentration.

Chlorophyll is a main biochemistry component for photosynthesis and a health indicator for plant. Chlorophyll concentration can be measured by non-destructive and non-contact method using Diffuse Reflectance Spectroscopy. Phantom consist of intralipid, aquades, gelatin and chlorophyll. Chlorophyll with certain concentration that known by absorption technique is used to be a primary stage for DRS. Non linear least square data fitting using diffuse reflectance mathematical model is used to determine parameters from phantom. The value of parameters is used for chlorophyll concentration measurement and will be compared with the chlorophyll concentration from absorption technique. When the system have been quantified well, the system will be used for chlorophyll concentration measurement for leaves without a complicated sample preparation such as absorption technique. Phantom reflectance spectroscopy has been tested and has a similar spectrum shape with leave's reflectance. Chlorophyll concentration measurement has been tested from three species of vegetables with three variation concentration and got error value for mustard, spinach and kale respectively 3%-10% ; 2.5%-10% and 16%-31%.

Fruit consumption rate of Indonesian population is still far below the level of sufficiency of fruits consumption recommended by the Food Agriculture Organization / World Health Organization (FAO / WHO). Maintaining the quality of fruit is expected to maintain stability in the fulfillment of national fruit needs. Early detection to determine the growth rate can be seen from the level of greenery or chlorophyll content during the growth period. So we need a method to measure the concentration of chlorophyll in the leaves by using Diffuse Reflectance Spectroscopy which is non destructive. This technique does not require complicated sample preparation as in the determination of chlorophyll content through Absorption Spectroscopy. Tissue model of leaf (phantom) is made of gelatin with known chlorophyll content variation, used as a preliminary stage for testing Diffuse Reflectance Spectroscopy technique. Determination of chlorophyll content by Absorption Spectroscopy technique will be used as a comparison. To determine the value of optical parameters (absorption coefficient μ_a and reduced scattering coefficient μ_s'), obtained from fitting between the measured reflectance spectra of phantom and the reflectance model of leaves. Chlorophyll content determined from correlation equation y = 0,944 x + 5,0069 with a coefficient of determination (R²) of 0,9422 for mango leaves, y = 0,5759 x + 5,6772 with coefficient of determination (R²) of 0.9945 for starfruit leaves, y = 0,1168 x + 3,7704 with a coefficient of determination (R²) of 0.9789 for guava leaves.

Curcumin stability is strongly influenced by temperature because if storage is not done properly then its bioavability will be low in the body, in fact the storage of curcumin does not always correspond to storage advice due to lack of temperature control. This study was conducted to determine the effect of Curcuma Plus Immuns storage temperature containing curcumin by spectrophotometry method. The samples of Curcuma Plus Imuns were stored in three different conditions: cold temperature (4 °C), room temperature (27 °C), and hot temperature (48 °C), then the sample was dissolved in 96% ethanol, and checked its power intensity using optical power meter Thorlabs. The result of characterization of curcumin optical properties in the sample of Curcuma Plus Imuns shows that curcumin has the highest absorbance value at 410 nm wavelength. Storage of Curcuma Plus Immunes in cold and hot temperatures can cause the concentration of curcumin to decrease, so storage at room temperature is the best storage temperature.

Anti reflection coating (ARC) is used in solar cell that functions to increase the quantity of light absorption. To obtain maximum results would require a good combination between ARC’s materials and the synthesis technique. TiO₂-SiO₂ was used as ARC materials because it has good passivity and high refractive index value. Pulsed Laser Deposition (PLD) method was used for synthesis technique because it has high photon energy and high temperature. Characterization are done by using Field Effect Scanning Electron Microscope (FESEM), X-Ray Diffraction (XRD), and Ultraviolet-Visible (UV-Vis) Spectrophotometry. The best result, anti reflection coating TiO₂-SiO₂ successfully reduced the reflection value from 35.69% to 14.11% for silicon substrate. It was gained with the properties of laser’s wavelength at 532 nm, laser’s energy at 100 mJ, and deposition time at 20 seconds.

The Mach-Zehnder Interferometer is one of the fundamental components in a photonic circuit. It has a variety of functions, such as wavelength filtering, optical switching, and optical sensing. Gallium Nitride (GaN) semiconductor-based devices have been a source of interest for photonic device researchers, owing to their ability to operate at high temperatures and high power levels. In this work, we have investigated the effect of wavelength variation on the relative power in the Mach- Zehnder Interferometer structure, based on two directional couplers using GaN on Sapphire as a preliminary study to design the wavelength selections. The structure was optimised using OptiBPM with the beam propagation method. We optimised the structure by varying length of the waveguide and the gap between the top and bottom waveguide. Based on the results of the numerical experiment, we found the best length and gap value of the Mach-Zehnder Interferometer to be 14500 μm and 36μm. It also shown that optical field propagation is uniform and the relative power reaches 0.93 at a 1.55μm wavelength. The simulation was conducted using a wavelength range from 1.50 up to 1.60 μm with increments of 0.01 μm to obtain the performance of structure at the C-band range. By varying wavelength from 1.50 up to 1.60 μm, the result indicate that the optical field propagation is uniform and the relative power almost stable at 0.9.

The introduced design is a 1 × 8 optical power splitter using MMI structure and taper output branches in GaN semiconductors. The design has been conducted theoretically using 3D FD-OptiBPM to improve the power distribution. The modelling structure used 300 nm AlN and 200 nm AlGaN as the buffer layer on Sapphire respectively. The numerical experiment is carried out at an optical telecommunication wavelength at λ = 1.55 μm. The refractive indices of the layers used are n_TE = 2.279 ± 0.001 and n_TM = 2.316 ± 0.001. The result showed that the optimum width and thickness of input and output rib waveguides are 4 μm and support only single mode propagation. The MMI-based optical power splitter with a length of 2010 μm and a width of 85 μm is the best result. In this proposed design, the output power splitted in almost uniform into eight output branches. It is also shown that the total relative power at the output ports is 0.96 with an excess loss of 0.28 dB and power imbalance of 0.13 dB.

In the last decade, coherent narrow linewidth optical system technology has contributed to reaching a new generation called high-speed optical communication. This technology has improved the transmission capacity of long-haul fiber optic transmission systems. State of the art in the market is a bit rate up to 100 Gbps per channel, where in one fiber optic can be traversed by 80 channels or 8 TB per fiber. The main key of the high-speed transmission is narrowing the laser linewidth which will increase the laser coherency. Some techniques have been proposed before such as the use of quantum well structure, distributed feedback braggers and application of external cavity resonators that have been able to narrow semiconductor linewidth lasers. In this paper we make a theoretical analysis to attempt for narrowing the linewidth semiconductor laser with laser current injection control. We intend the application of narrowing linewidth technique for the free-space optical communications in the case of visible light communication where the demand of laser source with narrower linewidth of signal is one of the key to improve the performance. The analysis is performed based on Schawlow-Townes equation. We prove that increasing the current injection twice causes linewidth constriction twice. The analysis and simulations are performed using Optiwave software.

Optical fiber has been used to fulfil the increasing need of high speed and high capacity data transfer. With 4.3 million users and 18.3% growth projection per year, fixed broadband sector of PT Telkom Indonesia relies on the quality of fiber optic backbone infrastructure, which represented by the Signal to Noise Ratio (SNR) and Bit Error Rate (BER). So, it is necessary to analyze SNR and BER parameters of fiber optic backbone in the segment between STO Lamongan 1 and STO Kebalen, Surabaya. SNR is logarithmic ratio of received signal and noise power, while BER is the measure of incorrect bit identification probability. The measurement process taken in STO Kebalen`s receiver by connecting BER Tester into one of the DWDM ports in Optical Transport Network (OTN) platform for 24 hours. It showed the result of BER 10^-23. To better analyze SNR and BER parameters completely, it needs a simulation brought by Optisystem software. The 100 Gbps, 84 km, 10 channels DWDM backbone is simulated in 193.1-194 THz with 100 GHz of frequency spacing. Parameters of the simulation are following the characteristic of the backbone itself and components datasheets. WDM analyzer and BER analyzer are used as measurement instrument. The simulation shows that SNR and BER of the system is acceptable based on standards and different at each frequency or wavelength channel. Maximum SNR is 72.37 at 193.6 THz, while minimum BER reaches 2.05 × 10^-30 at 193.5 THz. To obtain the optimum BER of 10^-12, two kinds of treatment, dispersion compensating fiber installation and transmitter power addition on 193.1, 193.2, 193.9, and 194 THz are simulated.

The comparison between two different bottom-up synthetic techniques had been prepared in order to synthesis the carbon dots (CD) from organic waste, i.e. the hydrothermal (HT) and microwave irradiation (MI) techniques. The CD were extracted from two different sources, i.e. from watermelon rind (wet organic waste) and peanut skin (dry organic waste). All of the products were characterized using spectroscopy characterization to determine their optical characteristics. It was obtained that all of the CD absorbing light in the UV region (around 300 nm) and emitting light in the visible light region (around 500 nm) which is called as photoluminescence (PL). The time-resolved PL (TRPL) was also observed within all of the products, which shows that they have TRPL around 3 to 4 ns, thus those CD categorized as fluorescence. Then, both CD from watermelon rind (WR) and peanut skin (PS) were examined using FTIR and it was obtained that both CD has carboxyl group content. After that, both products were also compared based on their performance as Fe³⁺ and Pb²⁺ sensors (1 nM–10^-1 M with 10 interval). The best performance was achieved by PS CD, due to its consistency in optical characteristics degradations (negative degradation) due to PL-turn off sensor method with the regression of each optical characteristics (absorbance, PL, and TRPL) are 0.6542, 0.6567, and 0.6168.

A Single-mode multimode single-mode (SMS) fiber structure coated with MWCNTs is proposed and demonstrated for the detection of magnesium ion. The SMS fiber has a length of 30 mm multimode fiber and was fabricated by connecting two optical fiber single-mode and multimode fiber. As the magnesium concentration increases from 0% to 5%, the output power of the SMS fiber structure decreases linearly with sensitivity and resolution of 3.0261 dBm/% and 0.0379 % respectively, for the SMS fiber structure coating with MWCNTs. MWCNTs as magnesium ion sensors will change the refractive index of fiber as the magnesium ion concentration changes due to the optical properties of adsorption. Hence, the SMS fiber structure coating with MWCNTs is more sensitive than the one without coating for magnesium concentration detection.

The waveguide parameter optimisation for a simple 1 × 2 optical power divider based on three parallel rectangular waveguides in a gallium-nitride (GaN) semiconductor/sapphire is reported. The optical power divider works according to coupled-mode phenomena. The optimisation was conducted using the 3D FD-BPM method. The results showed that the best geometrical values are 780 μm length and 18 μm width accordingly. It is also shown that at propagation length of 780 μm, the optical power is successfully divided into a uniform two output beams, each with 47.5% of total input power. It is shown that at a wavelength of 1.55 μm, the optical power divider has an excess loss of 0.23 dB.

Electric current measurement has become an important aspect in electric current quality monitoring. In the development of electric technologies, electrical system needs new current measurement technology with high sensitivity and resolution. In this study, an optical fiber current sensor has been developed using SMS fiber structure and ferrofluid for an alternating current measurement. This optical fiber current sensor works with the change of refractive index of ferrofluid. Ferrofluid is colloidal suspension that is made from Fe₃O₄ nanoparticle and surfactant (oleic acid, citric acid, etc). The refractive index of ferrofluid will change due to the magnetic field that affects ferrofluid. The experiment was done by measuring the change of output power of optical fiber current sensor using Optical Power Meter due to current flow in the wire. The alternating current range used in this study is 0-10A. The results show that the SMS fiber current sensor has a sensitivity of 3.049dB/A in the range 2-7A, 95% of precision rate and a resolution of 0.037A.

Palm oil is one of common consumed raw food and found adulterated with another materials such as lard. Palm oil adulteration can cause some problems in norms and health. Some methods have been developed in detect lard mixing in foods such as spectroscopy based methods, including infrared spectroscopy and some methods which is complex, expensive, and need of experts. In other side, plastic optical fiber with u-shaped configuration has been developed as biosensors. Through utilization of evanescent field and effect of the change in refractive index to the transmitted power, it has been design a sensor based on plastic optical fiber to detect lard adulteration in palm oil. Experiments show that the most optimal sensor design based on plastic optical fiber with u-shaped configuration is sensor with Infrared LED as light source, 50 mm curvature radius of bend, dan 2 cm length of peeled cladding. From the experiments, sensitivity of the sensor is 0.15630352 μW / % lard concentration.

We demonstrate the singlemode-multimode-singlemode (SMS) fiber structure for formalin detection. Formalin is a formaldehyde compound in water with an average concentration of 37 % and 15 % of methanol and water. Formalin consists of two substances; formaldehyde and water. Formaldehyde contamination in foods causes a negative effect for body. International Agency for Research on Cancer (IARC) classifies formaldehyde into Group 1 (carcinogenic to humans). Detection contamination of formalin in foods is very important. In this work, SMS fiber structure was used for formalin detection due to easy fabrication, cheap and more accurate in readings. This experiment utilized a difference in refractive index that affects the power output from optical fiber.

In this work, we investigated the effect of temperature and viscosity changes on the quality of cooking oil based on Ushaped SMS fiber structure. Quality of cooking oil has always been a topic of interest among researchers because the quality of cooking oil is related to human health. In this work, the cooking oil was heated with varied temperature from 30°C, 50°C, 100°C, 150°C, 200°C, and 250°C and the viscosity of cooking oil was measured using an Oswald Viscometer. It is found that, the data losses obtained are from -14.3, -14.29, -14,27, -14.21, -14.15, and -14.07 dB. The highest viscosity of the cooking oil significantly increases the losses of output power. The refractive index change of the viscosity of the cooking oil causes a change in the output power of the sensor. In conclusion, an U-shaped SMS fiber for the measuring of the cooking oil viscosity is simple, low cost, and excellent repeatability detection was successfully achieved in this study.