The term "Songket" comes from the Malay word "Sungkit", which means "to hook" or "to gouge". Every motifs names and variations was derived from plants and animals as source of inspiration to create many patterns of songket. Each of songket patterns have a philosophy in form of rhyme that refers to the nature of the sources of songket patterns and that philosophy reflects to the beliefs and values of Malay culture. In this research, we propose a system to facilitate an understanding of songket and the philosophy as a way to conserve Songket culture. We propose a system which is able to collect information in image songket motif variations based on feature extraction methods. On each image songket motif variations, we extracted philosophy of rhyme into impressions, and extracting color features of songket images using a histogram 3D-Color Vector quantization (3D-CVQ), shape feature extraction songket image using HU Moment invariants. Then, we created an image search based on impressions, and impressions search based on image. We use techniques of search based on color, shape and aggregation (combination of colors and shapes). The experiment using impression as query : 1) Result based on color, the average value of true 7.3, total score 41.9, 2) Result based on shape, the average value of true 3, total score 16.4, 3) Result based on aggregation, the average value of true 3, total score 17.4. While based using Image Query : 1) Result based on color, the average precision 95%, 2) Result based on shape, average precision 43.3%, 3) Based aggregation, the average precision 73.3%. From our experiments, it can be concluded that the best search system using query impression and query image is based on the color.Keyword : Image Search, Philosophy, impression, Songket, cultural computing, Feature Extraction, Analytical aggregation.

Induction Motor in Electrical drive system at a accelleration speed for example in electric cars have a hard speed setting is set on a wide range, causing an inconvenience for motorists and a fast response is required any change of speed. It is necessary for good system performance in control motor speed and torque at low speed or fast speed response, which is operated by Indirect Field Oriented Control (IFOC). Speed control on IFOC methods should be better to improving the performance of rapid response in the induction motor. In this paper presented a method of incorporation of Fuzzy Logic Controller and Backstepping (Fuzzy-Backstepping) to improve the dynamically response speed and torque in Induction Motor on electric car, so we get smoothness at any speed change and braking as well as maximum torque of induction motor. Test results showed that Fuzzy-Backstepping can increase the response to changes speed in electric car. System testing is done with variations of the reference point setting speed control system, the simulation results of the research showed that the IFOC method is not perfect in terms of induction motor speed regulation if it’s not use speed control. Fuzzy-Backstepping control is needed which can improve the response of output, so that the induction motor has a good performance, small oscillations when start working up to speed reference.Keywords: Fuzzy-Backstepping, IFOC, induction motor

Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time.Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm

This paper presents a stabilization control method for “x” configuration quadcopter. The control method used the combination of PD (Proportional Derivative) controller and PIAFC (Proportional Integral Active Force Control). PD is used to stabilize quadcopter, and PIAFC is used to reject uncertainty disturbance (e.g. wind) by estimating disturbance torque value of quadcopter. The PD with PIAFC provided better result where PIAFC could minimize uncertain disturbance effect. The simulation has successfully give comparation about controller performance (PD, PD-AFC, PD-PIAFC) by calculate RMS (Root Mean Square) value. PD with AFC gives better result than PD. AFC optimization using PI (PD-PIAFC) give best result if compared with PD or PD-AFC. PD-PIAFC has lowest RMS value of result control signal, 0.0389 for constant disturbance and 0.1008 for fluctuated disturbance.Keywords:“x” configuration quadcopter, stability, PD, PIAFC.

We present an implementation of Zero Forcing (ZF) equalizer in OFDM scheme using Software Defined Radio platform whereas NI USRP-2920 as the Radio Frequency (RF) front-end. ZF equalizer is employed to achieve reliable system at the receiver. Center frequency used for data transmission is 915 MHz. The reliability transmission and the performance of ZF equalizer are measured in term of different symbol mapping (i.e., M-PSK and M-QAM). The IQ rate determines the bandwidth available, whereas good performance is achieved with IQ rate less than 1 MHz.ZF equalizer achieves good performance when using BPSK, QPSK and 16-QAM modulation techniques. By applying ZF equalizer, bit error on BPSK and QPSK modulations can be reduced from 29,16% and 39,06% into 0%. This advantage of ZF equalizer also is able to press the bit error on 16- QAM and 64-QAM modulations into 3,125% and 8,85%, respectively.Keywords: OFDM,SDR, USRP,Zero Forcing Equalizer

Although many people love flowers, they do not know their name. Especially, many people do not recognize local flowers. To find the flower image, we can use search engine such as Google, but it does not give much help to find the name of local flower. Sometimes, Google cannotshow the correct name of local flowers. This study proposes an application to identify Indonesian flowers that runs on the Android platform for easy use anywhere. Flower recognition is based on the color features using the Hue-Index, shape feature using Centroid Contour Distance (CCD), and the similarity measurement using Entropy calculations. The outputs of this application are information about inputted flower image including Latinname, local name, description, distribution and ecology. Based on tests performed on 44 types of flowers with 181 images in the database, the best similarity percentage is 97.72%. With this application, people will be expected to know more about Indonesia flowers.Keywords: Indonesian flowers, android, hue-index, CCD, entropy