IEEE

Welcoming message from the 2017 3rd ICST chairman

Jumina¹

[1] Universitas Gadjah Mada, Indonesia

The 2017 3^rd International Conference on Science and Technology was held as a part of the Universitas Gadjah Mada Annual Scientific Conference (UASC) consisting four major events: International Conference on Science and Technology (ICST), International Conference on Tropical Agriculture (ICTA), International Conference on Health Sciences (ICHS), and International Conference on Southeast Asia Studies (ICSEAS). The 2017 3^rd International Conference on Science and Technology consisted of five symposia, namely the 5^th Annual Network on Natural and Unnatural Material Symposium (ANNUM 5), 2^nd Computer Symposium, 2^nd Geomaritime Symposium, 1^st OMICS Symposium, and 1^st Infrastructure Technology Symposium. Accepted papers of the conference would be published in journals and proceedings indexed by Scopus, EBSCO or DOAJ, among others are the Indonesian Journal of Chemistry, Indonesian Journal of Geography, Indonesian Journal of Biotechnology, or IEEEXplore Digital Library.

The Wireless Energy Transfer recharging system based on the ultra-high frequency by using Yagi-Uda directional antenna

Sunarno¹; Fahmy Rinanda Saputri¹; Memory Motivanisman Waruwu¹; Rony Wijaya²

[1] Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Indonesia

[2] Production House Unit, Faculty of Medicine, Universitas Gadjah Mada, Jl. Farmako No. 2 Sekip Utara, Sleman, D.I. Yogyakarta, Indonesia

In the near future, the Wireless Energy Transfer (WET) will be widely used, especially for electronics recharging in the human organ implantations. WET has been researched intensively by some researchers, but the low efficient energy transfer is still a problem. In order to figure out the efficiency of the energy transfer, the experiment had been conducted in Laboratory of Sensor and Telecontrol Systems. The complexities of the measurement system setup and assessment of the sufficient energy both transmitter and receiver will also be discussed. The experiment results deliver the new design of the WET, empiric data of the energy transfer, and the sufficient antenna model as well. In this research, The UHF transmitter generated radio frequency with output energy of 39.00-watt energy source. The range of various frequencies in this paper is 400 MHz to 489 MHz and the SWR is 1.2. The transmitter unit and the antenna were connected with the 50 ohm-coaxial cable. In order to transfer the energy, the transmitter system consisting Yagi-Uda model antenna was applied. The results show that the efficiency maximum of the measured energy transfer is 0.36%. In our investigations, the efficiency of the result also depends on the polarity of the Yagi-Uda Antenna used in the experiment. According to the results, the angle that the maximum energy transferred is 60°, on the contrary, the angle of 150° gives the lowest efficiency results. We found that the distance between the transmitter and receiver antenna contribute significantly to the amount of energy transferred from the system. In this case, the energy can be calculated from the current and voltage measurement. The energy transfer versus distance relationship shows that a specific trend was obtained. This specific trend seems are affected by the antenna characters used in the experiment. Based on the experiment results, the wireless energy transfer could be done by utilizing UHF radio wave. Even though the efficiencies were still relatively low, but it can be used for some specific purposes in the example, in the electronic human organ implant recharging and applicable for the general electronic devices in the special areas. This experiment data are very useful for the scientists, practicing who work in the WET research field.

Keywords: wireless energy transfer, ultra-high frequency, electronic human organ implant, radio transmitter, antenna

Comparison of machine learning algorithms for soil type classification

Pramudyana Agus Harlianto¹, Teguh Bharata Adji¹, and Noor Akhmad Setiawan¹

[1] Department of Electrical & Information Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

Machine learning algorithm can be applied for automating soil type classification. This paper compares several machine learning algorithms for classifying soil type. Algorithms that involve support vector machine (SVM), neural network, decision tree, and naïve bayesian are proposed and assessed for this classification. Soil dataset is taken from the real data. Simulation is run by using RapidMiner Studio. The performance observed is the accuracy. The result shows that SVM, with the use of linear function kernel, outperforms the others algorithms. The SVM best accuracy is 82.35%.

Robustness of PD control for transporting quadrotor with payload uncertainties

Gilang Nugraha Putu Pratama¹, Ibnu Masngut¹, Adha Imam Cahyadi¹, and Samiadji Herdjunanto¹

[1] Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

Considering its agility and capability to vertical take-off and landing, quadrotor is beneficial for transporting missions. In this paper we present a model of a transporting quadrotor with payload uncertainties, as well as its corresponding proportional-derivative (PD) control on Special Orthogonal-3. Practically, it is a challenging problem to compensate the inertia perturbation due to the uncertainties of the payload that is transported. It is where our proposed control law comes to urge. Finally, numerical simulation and results are presented to verify the effectiveness of our proposed control law.

Data service orchestration for law enforcement and open criminal justice data interoperability (National Crime Information Center, Indonesian National Police case studies)

Muhammad Angga Rinjani¹, Teguh Bharata Adji¹, Adhistya Erna Permanasari¹, and Fahmi Dzikrullah²

[1] Department of Electrical Engineering and Information Technology, Engineering Faculty, Gadjah Mada University, Yogyakarta, Indonesia

[2] PT. Gamatechno Indonesia, e-Government Division, Cik Di Tiro Street 34 Special Region of Yogyakarta, 55234, Indonesia

Information communication and technology (ICT) adoption in law enforcement services has been transformative and shifted from the system application oriented to the open data oriented, where information can be more easily exchanged among law enforcement organizations. Therefore, interoperability is the essential requirement for an open data service provision that progresses towards higher levels of integration among government levels and branches to enhance the quality of public services, transparency, accountability, cost-effective service provision and government operation, optimization of public policies for better outcomes and integrated government processes. In this paper, we proposed a proof of concept of data service orchestration for law enforcement that aims to integrate internal and external agencies of the criminal justice information system. Through this system, the law enforcement agencies could provide an exchange services environment with greater ease and deliver public value through open criminal justice data initiatives to increase prestige as well as improving institutional transparency and accountability.

Servo state feedback based on Coefficient Diagram Method in magnetic levitation system with feedback linearization

Alfian Ma'arif¹, Adha Imam Cahyadi¹, Oyas Wahyunggoro¹, and Herianto²

[1] Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

[2] Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

The challenge design of servo state feedback controller is how to determine the parameter value of integral gain and state feedback gains. This paper proposes CDM (Coefficient Diagram Method) to determine gains of servo state feedback controller. We apply this controller in the nonlinear plant, magnetic levitation system, and firstly transform the system to be linear using feedback linearization. CDM is one of the polynomial methods in a control system that based on the equivalent time constant and stability index. The simulation observes the performance of the system with various stability index besides the CDM standard parameter and also compares the CDM with another method i. e. LQR. The simulation shows that the CDM standard parameter can give a good performance of the system so that can avoid the effort of trial and error.

High-resolution automated Fugl-Meyer Assessment using sensor data and regression model

Ricky Julianjatsono¹, Ridi Ferdiana¹, and Rudy Hartanto¹

[1] Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Motor function assessment is a critical component in post-stroke rehabilitation program. Fugl-Meyer Assessment (FMA) is regarded as the most comprehensive tool to describe post-stroke patient's motor function and is widely utilized. However, the FMA scoring system classifies patient's motor function within only three levels (0, 1, or 2) for each assessment item. Hence, it's difficult to observe minor improvement in patient's motor function. To address this issue, a high-resolution scoring system was proposed in this research. Six regression models were built for six upper-extremity FMA items. These models were trained using data gathered from Microsoft Kinect sensor and glove sensor. The trained models could predict FMA scores with the resolution of 14 fractional digits. The representativeness of the predicted scores was evaluated by calculating their Pearson's correlation with the actual kinematic variables. All predicted scores represent patient's motor function better than standard FMA score. In addition, the highest correlation's mean of 0.58 was found on shoulder elevation item which utilized Neural Network Regression algorithm. This algorithm also outperformed the other in most assessment items. The ability to observe the changes in patient's motor function in detail helps therapists providing more responsive treatment and could likely increase the patient's adherence toward the given treatment.

Web Engineering Education through blended learning

Ridi Ferdiana¹

[1] Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

Web technology is growing with one website deployed per second. It can be said that any business will have a website. Therefore, web engineer become an essential part to make it happen. However, web technology is not simple, there are more than 50 web frameworks that can be used to develop a website. There are more than 10 web programming languages that can be chosen to develop a website. This paper proposes an idea to accelerate the learning curve for new web developers. The paper uses ADDIE (Analyze, Design, Develop, Implement, and Evaluate) framework to develop an e-learning that will support the classroom as a blended learning experience. Accordingly, this article proposes learning plan namely Web Engineering Education (W2E). W2E proposes structured blended learning approach and capstone design course model to achieve the body knowledge of web developers. This paper will describe the body knowledge for web engineering, the learning curve that proposed for a new web developer, and evaluation technique that can be used to evaluate the web developer.

Simulation of modified tubular linear permanent magnet generator for wave energy conversion in Indonesia

F. Danang Wijaya¹, Budi Azhari¹, and Sarjiya¹

[1] Department of Electrical Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Conventional tubular linear permanent magnet generator (LPMG) is composed of permanent magnets which are placed in translator, and stator which is made of iron. However, this topology suffers from the relatively huge cogging force due to the interaction between the magnet and the iron, also a large core losses from hysteresis and eddy current. To reduce the force and the losses, modified design of LPMG was proposed by reducing the iron proportion of the stator. The modified tubular LPMG would be applied for 1 kWp wave energy power plant in the south coast of Java, Indonesia. The reduction of the iron was then compensated by increasing number of stator winding turn to maintain the output power as desired. Resulted design was then simulated by using finite element magnetic software of FEMM to check the output values based on magnetic flux distribution. The results of the simulation showed that the modified design needs 11.4% more stator winding turns to produce equal power. However, the cogging force and the mechanical loss decreases by 24.7%. The design also reduces 57.2% of both hysteresis loss and eddy current loss, and 57.1% of weight.

Analysis of ferrite effect in Axial Flux Permanent Magnet Generator using magnetic circuit approach

Prih Sumardjati Mulyaseputra¹, Sasongko Pramono Hadi¹, Fransisco Danang Wijaya¹, and Suharyanto¹

[1] Departemen Teknik Elektro dan Teknologi Informasi, Universitas Gadjah Mada - Yogyakarta, Indonesia

In this paper, four models of AFPMG (Axial Flux Permanent Magnet Generator) are analyzed and compared to get the best model correspond to highest magnetic flux density that produced by those generators. Before analyzing performance of those models, leakage flux are modeled and analyzed by using magnetic circuit approach to defining the optimal distance of magnet to the magnet on the rotor disk. Therefore, optimal size of AFPMG are determined according to the optimal distance from magnet to magnet. The analysis results show that AFPMG with ferrite core and ferrite ring has the highest value of magnetic flux density. By the addition of ferrite material in AFPMG, it can increase the value of magnetic flux density. On the other hand, it is also can decrease leakage flux value. Analytical results then will be validated using finite-element method (FEM).

The prediction of energy-absorption on the car crush box

Hadi Saputra¹, Jamasri², and Heru S.B. Rochardjo²

[1] Departement of Mechanical Engineering, Institut Sains dan Teknologi AKPRIND, Yogyakarta, Indonesia

[2] Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

This paper describes a computationally aided design process of a thin-walled structure of a retail car crash box subjected to a progressive crashing in longitudinal axial direction. The study was broken up into three phases: (1) digitising of the existing retail car crash box structure, (2) the crash simulation of the structure using dynamic explicit formulation (3) the verification of the simulation of the accident. In the digitalization phase of this structure, the perimeter of the cross section, the shape, the length and the thickness of profile were made the same as the Original Equipment Manufacturer (OEM) the product of a compact car found in the local market. The crashing procedure and parameter follow the New Car Assessment Program (NCAP) by National Highway Traffic Safety Administration (NHTSA). It found that the value of energy absorbed by the crash box was 5.91 KJ. The specific energy absorption is 21.53 KJ/kg. The crash force efficiency is 0.54. The simulation method, that was verified using square tube structure, resulting in the value that matches to the current simulation done by another researcher.

Lung detection using Adaptive Border correction

Rizki Nurfauzi¹, Hanung Adi Nugroho¹, and Igi Ardiyanto¹

[1] Department of Electrical and Information Engineering, University of Gajah Mada, Indonesia

Juxta-pleural is one of the lung nodules types that attached to the chest wall and has the same intensity. The presence of this type of nodules can be a mistake in lung segmentation. We propose a method for lung segmentation with bidirectional peak detection method that gives the result of lung border to be a solution to the problem. The method we propose has been tested with 140 3D CT images from ILDC-IDRI dataset which only contains juxta-pleural and juxta-vascular nodules, result shows only 14.3% of under-segmentation. We have compared with another two methods which are Morphological Closing and Adaptive Border Marching (ABM). The proposed method achieved the fastest computation level at 0.18 sec/slice or three times faster than the speed of morphological methods (0.56 sec/slice) and 40 times faster than the speed of ABM method (7.12 sec/slice). The propose method has potential to be implemented in embedded systems.

Evaluation of spatial and regional planning map using remote sensing and GIS in East Lombok Indonesia

F. Khikmah¹, M. Andhika¹, H. D. Dewanto¹, A. Venuary¹, M. F. Arfiansyah¹, W. N. Fauziah¹, M. A. E. Raharja¹, and I. N. Hidayati¹

[1] Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia

Temporary of preservation regional planning map need to evaluate and renewable execute so deviate possibilities can be prevented. This study is conducted to evaluate the regional planning map in East Lombok based on potential land-use using directive and existing land-use map. Directive land-use map is made by overlaying of some parameters, such as the slope, soils, and rainfall using GIS. Existing land-use map produced by visual interpretation is utilizing Landsat 8 OLI satellite imagery. The field survey did use stratified random sampling to validate parameters, accuracy field survey is about 68% of the existing land-use map. Result based on spatial and regional planning map evaluation of East Lombok using directive land-use and the existing land-use map of suitability is good enough reach 80.15% and not suitable reach 19.85%.

Machinery equipment early fault detection using Artificial Neural Network based Autoencoder

Teguh Handjojo Dwiputranto¹, Noor Akhmad Setiawan¹, and Teguh Bharata Aji¹

[1] Department of Electrical Information Engineering, Universitas Gadjah Mada, Jogjakarta, Indonesia

Machinery equipment early fault detection is still in an open challenge. The objective of this paper is to introduce a parametric method Artificial Neural Network based Autoencoder implemented to perform early fault detection of a machinery equipment. The performance of this method is then compared to one of the industry state of the art nonparametric methods called Similarity Based Modeling. The comparison is done by analyzing the implementation result on both artificial and real case dataset. Root Mean Square Error (RMSE) is applied to measure the performance. Based on the result of the research, both of these methods are effective to do pattern recognition and able to identify data anomaly or in this case is fault identification.

A review on driver drowsiness based on image, bio-signal, and driver behavior

Bagus G. Pratama¹, Igi Ardiyanto¹, and Teguh B. Adji¹

[1] Department of Electrical and Information Engineering, University of Gadjah Mada, Indonesia

The ratio of accidents caused by drowsiness, increases slightly year by year. The most victims of this case are young adult and mostly happens in developed country. Therefore, to reduce the number of accidents caused by drowsiness, researchers around the world develope some methods for detecting drowsiness on driver's face automatically. They propose various features such as visual, non-visual, and vehicular. Visual features are extracted from driver's face and recorded by camera. Non-visual features are signals emerged from driver's body and to acquire those signals, they use special sensor attached to driver's body. Vehicular features are obtained by observing the behavior of driver during driving. From those features which are propsed by researchers, we discussed 3 ideas that can be considered as guidance to lead researcher in developing drowsiness detection. The first idea is creating the dataset of drowsiness facial expression because it can predict drowsiness and fatigue. Second idea is to combine visual, non-visual, and vehicular features into one for better detection. And last one is developing wearable hardwares such as smartwatch for drowsiness detection which are easy to use and user friendly.

Linking multidimensional context to support tourism recommender system

Kusuma Adi Achmad¹, Lukito Edi Nugroho¹, Widyawan¹, and Achmad Djunaedi²

[1] Dept. of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

[2] Dept. of Architecture and Planning, Universitas Gadjah Mada, Yogyakarta, Indonesia

The trend of the utilization of information technology has made it easier for service providers and users to share information. However, the trade-off eases the generating of excessive information. This makes it difficult to search, sort, and select the information. Therefore, to cope with the excessive information, filtering through the recommendation system is needed. Two-dimensional recommendation system defines the interaction users and items, however, it has several limitations, such as cold start problem, limited content analysis, sparsity, and scalability. To overcome this, the solution is a recommendation of a multidimensional approach by taking into account the additional contextual information including location, time, and social activities. The preparation of the multidimensional recommendation system is done through a literature review. Related to tourism context, a conceptual model of multidimensional context-based recommendation systems, such as tourist (user), destination (item), location, time, social, and the weather is proposed.

Development of orthosis design for Spastic Cerebral Palsy through biomechanical approach

Djoko Kuswanto¹, Syukriyatun Ni'amah¹, and Farah Aulia Rahma¹

[1] Department of Industrial Design, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia

CP patients in Indonesia is estimated at around 1-5 per 1,000 live births to 80% is a type of Spastic CP. In patients with Spastic CP legs stiffness that causes the formation of abnormal posture, walking gait, and decreased motor skills which can be treated by wearing the orthosis. HKAFO often used as a device for therapy and AFO used for daily. Control posture patients in daily activity be the most important point in increasing gross motor function. To maximize the use of orthosis for daily activity needed design development with the approach biomechanical aspect. Approach which includes power of motion feet, angles motion joints, and adjustment to the different character of CP Spastic.

Cost-based power distribution optimization scheduling in microgrid

Andhika Lady Maharsi¹, F. Danang Wijaya¹, and I Wayan Mustika¹

[1] Departement of Electrical Engineering and Information Technology Faculty of Engineering, Universitas Gadjah Mada, Indonesia

Renewable energy is one of the solutions of energy limitation problem in the world. It often works with some independent plants of renewable energy that work together under the circumstances of center control. The renewable energy system (RES) such as photovoltaic (PV), wind turbine (WT) has a serious lack of stability power output or uncertain power. Because of that, the microgrid system (MGs) is built to optimize the power flow and minimize the impact of energy fluctuation. Not only about the power flow, but also the cost analysis is important in order to find the optimized power resource combination to reduce cost. This paper proposes a cost-based power distribution scheduling optimization in a microgrid. The power resource conducted from PVs, WT, biomass, and storage system performed by 0-1 Knapsack problem formula. In order to find the optimized cost, genetic algorithm (GA) is used. The output shows the optimized cost, output power which depends on energy load and true power resource combination of microgrid scheduling.

A systematic review: B-cell conformational epitope prediction from epitope characteristics view

Binti Solihah¹, Edi Winarko¹, Afiahayati¹, Sri Hartati¹, and Moh. Edi Wibowo¹

[1] Department of Computer Science and Electronic, Universitas Gadjah Mada, Yogyakarta, Indonesia

B-cell conformational epitope identification is the crucial issue in vaccinology. Limitation on experimental methods in the biological side, dataset and availability of computational resources opens a chance on developing prediction method which can accelerate epitope identification. A number of methods have been developed but their performance is still medium. Epitope prediction is a knowledge-based method. Presenting the statistical or computational based epitope characteristics together with epitope prediction method will facilitate the newcomer on identifying importance feature, improve the existing feature and propose the new feature. To reach the goal of the review, the research papers are collected from both epitope analysis research and epitope prediction methods research. The prediction methods are evaluated on what characteristics of epitope have been implemented on feature representation and are shown in a mapping table.

Mango leaf image segmentation on HSV and YCbCr color spaces using Otsu thresholding

Eko Prasetyo¹, R. Dimas Adityo¹, Nanik Suciati², and Chastine Fatichah²

[1] Department of Informatics, Engineering Faculty, University of Bhayangkara Surabaya, Jl. Ahmad Yani 114, 60231, Indonesia

[2] Department of Informatics, Information Technology Faculty, Institute of Technology Sepuluh Nopember (ITS), Kampus ITS, Jl. Raya ITS, Sukolilo, Surabaya 60111, Indonesia

Research detection of mango tree type that hasn't yet-fruitful needs good result of image segmentation. This is due it use color, texture, and shape as feature. Especially shape feature, we have to produce good image segmentation result as input of feature extraction. For color and texture, we need image segmentation result to be some region of interest in the feature extraction. In this research, we use segmentation by thresholding with Otsu method. We apply Otsu thresholing on Hue, Saturation, Intensity (HSV), and Luminance, Chromaticity Blue, Chromaticity Red (YCbCr) color space for mango leaves. All components of color space are used except Luminance. Segmentation is done by converting input image Red, Green, Blue (RGB) into color space required, then use the color components required, then applying Otsu threshold method, then use several morphology steps to produce good segmentation results. Then the results are compared with ground truth images. Performance testing of color space components provides the best performance component, it is Cr, then Saturation, Cb, Intensity, and Hue respectively. We use Precision, Recall, and F-measure as performance measurement. Precision is a percentage of positive detected in detection result. The Recall is the percentage of real positive detected. While F-measure is weighted harmonic mean of Precision and Recall. The results of empirical testing on components Cr, the average performance of segmentation obtained as follows: Precision is 0.995, Recall is 0.971, and F-measure is 0.983. This performance proves Cr as the right color space component for image segmentation of mango leaves by thresholding.

Monte Carlo simulation and clustering for customer segmentation in business organization

Andry Alamsyah¹ and Bellania Nurriz¹

[1] School of Economics and Business, Telkom University, Bandung, Indonesia

Utilizing data for segmentation analysis can bring a streamlined way to get potential insight as of decision making support in a business organization. Using appropriate data analytical technique help the organizations in profiling their customer segments accurately. The result brings an effective marketing strategy. However, there are times in doing data analytic, the organization needs another variable of data where the value is unavailable, for example: customer's income data which mostly hard to collect. By using Monte Carlo simulation, the value of customer's income can be generated and then compared with customer spending to construct customer segmentation model. An unsupervised learning for customer segmentation model using K-Means clustering enables us to see the grouping patterns of customer's income towards their spending. Clusters of the dataset might be interpreted as a group of customers that having a similar character. This paper shows us how to generate customer's income data and create data cluster to optimizing customer potential by utilizing data. Furthermore, the result brings us insight into which group of the customer might unserved properly considering their average income with their spending behavior.

Design and implementation of surveillance embedded IP camera with improved image quality using gamma correction for surveillance camera

Setiya Purbaya¹, Dodi Wisaksono Sudiharto¹, and Catur Wirawan Wijiutomo¹

[1] School of Computing, Telkom University, Bandung, Indonesia

The need for a security improvement of an area generally associated with the assets which are located in that area. The protection mechanism of these assets creates the need for a device which can be used as a monitoring tool. A surveillance camera is a popular device for monitoring an area. For the purposes of data integration, the camera surveillance based on IP (Internet Protocol) is widely used. However, the maintenance of a file server and the provision of the data storage require substantial funding and effort. In addition, if the surveillance activity is carried out in the indoor room, sometimes the lack of lighting in the room can make data retrieval becomes not clearly visible. Thus it creates the need for restoring the data by improving its image quality. This study is going to design a device such as IP surveillance camera which based on an embedded system, with improved image recording feature by using gamma correction and data storage feature which integrates with cloud service through a network based on IP (Internet Protocol). In the image correction mechanism, the measurement of image quality improvement is executed by using a histogram. The measurement of image quality improvement based on the human perspective is also provided.

Parallelization of modular exponentiations of polynomials

M. Ridwan Apriansyah Budikafa¹ and Reza Pulunga¹

[1] Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia

Modular exponentiations are very important in many fields of computer science, including network security protocols. Modular exponentiations of polynomials are a type of modular exponentiations, where the base and modulus are polynomials. In this paper, a parallel modular exponentiation algorithm, which was proposed by Lara et al., is extended to solve modular exponentiations of polynomials in parallel, and further compared to two other proposed parallel algorithms. Essentially those algorithms differ only in their load-balancing methods. The result is, for exponents of length up to 2048 bits, the implementation of Lara et al.'s algorithm results in 28.01% faster running time compared to the implementation of the sequential algorithm. The result also shows that this algorithm is more efficient than the two other proposed algorithms.

Real time monocular visual odometry using Optical Flow: Study on navigation of quadrotors UAV

Syaiful Mansur¹, Muhammad Habib¹, Gilang Nugraha Putu Pratama¹, Adha Imam Cahyadi¹, and Igi Ardiyanto¹

[1] Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

Navigation is an important thing in so many intelligent systems. Nowadays, without any hesitation Global Positioning System (GPS) is the most common method for navigation. Nevertheless, in certain environments, GPS will become inaccurate due to the multi-path problem. In this paper, we propose a dead-reckoning system for quadrotor using feature-based monocular visual odometry to overcome that problem. The visual odometry design will be implemented into the fix bottom camera which is the monocular camera in quadrotor. The algorithm is validated by performing several tests. The results of the tests verify that the visual odometry algorithm can determine the position and orientation with good accuracy.

The application of Wavelet Recurrent Neural Network for lung cancer classification

Devi Nurtiyasari¹, Dedi Rosadi¹, and Abdurakhman¹

[1] Department of Mathematics, Universitas Gadjah Mada, Yogyakarta, Indonesia

Lung cancer is one of the deadliest types of cancer in the world. Lung cancer detection is necessary to determine the next steps in dealing with the patients. One of the methods that can be used for lung cancer detection is a classification method based on lung cancer image. Most of the models for lung cancer classification based on lung cancer image are various types of the neural network model with binarization image pre-processing. As an image is containing noise, it is needed to remove the noise from the original image before the binarization process. Wavelet is a model that can be used to remove the noise from the original image, i.e. image denoising process. Recurrent Neural Network is neural network development model which is able to accommodate the network output to be re-input of the network. The architecture of Recurrent Neural Network uses Elman network that has feedback link from the hidden layer to the input layer. The combination model of Wavelet and Recurrent Neural Network, called Wavelet Recurrent Neural Network, can be used for lung cancer classification by applying Wavelet for lung image denoising process and Recurrent Neural Network for the classification process. Classification of lung cancer using Wavelet Recurrent Neural Network provide results with sensitivity, specificity, and accuracy were respectively 93.75%, 66.67%, and 84% for training data and 88.24%, 75%, and 84% for testing data.

Low-cost switched array-wide band antenna for Search and Rescue disaster management

Elyas Palantei¹, Syafruddin Syarif¹, Arif Hidayat², and Sutan Takdir Ali Munawar²

[1] Electrical Engineering Departement Hassanuddin University, UNHAS, Makassar, Indonesia

[2] Indonesian National Institute of Aeronautics and Space (LAPAN), Parepare, Indonesia

The activity of SAR (Search and Rescue) is an activity that requires speed in finding the location point. Successfully search for victims can save many lives. Direction finder is proposing to accelerating search survivors. Direction finder can detect the direction and track the radio transmitter using Doppler function. The design, measuring, testing and integrating wideband switched parasitic antenna for direction finder application are conducted in the research. In this paper direction finder antenna made with simple devices and the materials can be found in Indonesia. The proposed architecture has advantages for cost-effective, easy to design and to integrate. The antenna design successfully reaches maximum gain by simulation and field test. The antenna success passes S11 measurement, in accord with international standards of antenna manufacturing. The antenna successfully tracks the transmitter using zero cross detector software.

Parallel implementation of genetic algorithm for searching optimal parameters of artificial neural networks

Eko Dwi Nugroho¹, Moh Edi Wibowo¹, and Reza Pulungan¹

[1] Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia

Genetic algorithm is a population-based evolutionary optimization approach, and this has been used to train artificial neural networks successfully. When a large number of individuals make up the population, however, the running time of the algorithm often becomes very long. Parallel computation is a technique that can potentially be used to address this issue. This research investigates the adoption of parallel genetic algorithm for searching optimal parameters of artificial neural networks (multilayer perceptrons). Paralellization is conducted using Message Passing Interface, where sub-populations (and their fitness values) are exchanged between processors while selection, crossover, and mutation processes, which are necessary to generate new sub-populations, are performed independently between processors. Experiments of this research show that parallelization has indeed reduced the running time of genetic algorithm. The proposed method produces an average running time of 2.066, 2.656, and 47.788 seconds/generation for the game of Tic-Tac-Toe, car evaluation, and game of chess (King-Rook vs. King-Pawn) datasets, respectively. For comparison, the average running time of the serial version of the algorithm is 14.397, 12.961, and 350.963 seconds/generation for the same three datasets, respectively.

Performance comparison of SISO and MIMO-OFDM based on SDR platform

Ridlo Qomarrullah¹, I Wayan Mustika¹, Selo¹, and Satriyo Dharmanto²

[1] Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Jl. Grafika No. 2, Yogyakarta, Indonesia

Multikom Global Mediatama, Jakarta, Indonesia

Due to requirement of reliable high-speed wireless communication, OFDM combined with multiple antennas (MIMO) system is a key technology for next-generation wireless communications to improve transmission performance. In this paper, we conduct field experiment for SISO and MIMO-OFDM using USRP N210 hardware as SDR platform. The research is conducted in LOS and NLOS environment with 16-QAM modulation technique. The result shows that MIMO-OFDM achieves better performance than SISO-OFDM. 2×2 MIMO spatial diversity with Alamouti STBC algorithm gives 2 dB diversity gain at BER of 5.10^-4 in LOS scheme and 6.7 dB in NLOS scheme at BER of 5.10^-3.

Semantic search with rule reasoning for scholarship information search

Kartikadyota Kusumaningtyas¹ and Khabib Mustofa¹

[1] Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia

Tendency to pursue graduate study has become a positive trend in Indonesia. This is supported by the growing number of agency or institution that organizes a postgraduate scholarship program with a wide range of requirements. Generally, finding information through the Internet is done by a keyword-based search engine which possibly gives several irrelevant results and relies on user's ability in selecting keywords. This research aims to provide an alternative by building semantic search system for finding scholarship information that allows natural language sentence instead of keywords. It implements rule reasoning to obtain implicit knowledge by defining the rules from basic knowledge that explicitly defined. Among the rules that are used in this system, data range restriction is used to determine data based on certain thresholds. The experiment results show that the system has recall rate 98.51% and precision rate 100% from 90 of 105 input sentences that are able to be processed by the system.

Direct comparison method of information dissemination using legacy and Social Network Analysis

Andry Alamsyah¹, Bernaully Cinditha Sarniem¹, and Indrawati¹

[1] School of Economics and Business, Telkom University, Bandung, Indonesia

Big data is a new phenomenon that force organization to find new way to process, to save, and to analyze data in various forms. Big data challenge is getting bigger and faster but also the opportunities of harvesting information from it. Organization prefers using big data's technology for many advantages, mainly because it is cheaper, effective, efficient and faster than previous system. In some research area, there are conflicting approach to solve the problem by using legacy methodology or by using big data approach. One of the fastest methodology in big data approach is Social Network Analysis. One of research area measured as the research object in this paper is information dissemination.

Long distance Automatic Number Plate Recognition under perspective distortion using zonal density and Support Vector Machine

Noprianto¹, Sunu Wibirama¹, and Hanung Adi Nugroho¹

[1] Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

Automatic Number Plate Recognition (ANPR) is one of computer vision applications to extract information in vehicles plate number. Nevertheless, perspective distortion is unavoidable when taking pictures of the plate number. Another factor that causes inaccuracy is the distance of the camera from the plate number. To solve these problems, we propose a new method to automatically detect and recognize vehicle plate number with regards to perspective distortion and distance of capturing plate number. We used zonal density with Support Vector Machine (SVM) as a classifier. We tested our algorithm on 21 vehicles plate number with 1, 3, and 5 meter of capturing distance. Our method yields an accuracy of 89.77%, 82.86%, and 65.22% for 1, 3, and 5 meters capturing distance, respectively. Compared with previous work, our method is able to preserve high accuracy when segmenting characters of plate number taken from 5 meter distance.

Big data analytic for estimation of origin-destination matrix in Bus Rapid Transit system

Widyawan¹, Bagas Prakasa², Dzaky Widya Putra³, Sri Suning Kusumawardani¹, Budi Triwibowo Yuli Widhiyanto³, and Fathurrochman Habibie³

[1] Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

[2] Vocational College, Universitas Gadjah Mada, Yogyakarta, Indonesia

[3] Department of Computer Science and Electronics, Universitas Gadjah Mada, Yogyakarta, Indonesia

In the field of transportation, the origin-destination matrix is one of the main and important components, especially in analyzing, planning, and managing a public transport network. The traditional survey can be used to determine passengers travel patterns and generate origin-destination matrix, but it is inefficient and cost a lot of resources. In the recent years, various methods have been studied to estimate origin-destination matrix to reduce costs and increase the accuracy of passengers flow. Many of them take advantages of big data technology to gather passengers travel information, mostly using smart card data. In this paper, we perform origin-destination matrix estimation using information from the smart card that was collected from automatic fare collection systems in Jakarta's Bus Rapid Transit. There are approximately 160 million records from 20 months of transactions between June 2014 and January 2016. This study utilized trip chaining algorithm that generates 610 daily OD matrices, 87 weekly OD matrices and 20 monthly OD matrices. The analysis is performed at a station and a line level, with an addition of passenger behavioral pattern.

Combination of DNS traffic analysis: A design to enhance APT detection

Muhammad Salahuddien Manggalanny¹ and Kalamullah Ramli¹

[1] Department of Electrical Engineering, University of Indonesia, Kampus Baru UI Depok, Indonesia

An activity of Advanced Persistent Threat (APT) is very dynamic. A single detection method will be ineffective. New modus and techniques are being developed rapidly and overcome the effort to acknowledge it. This design proposed a new approach through a combination of previous successful detection method based on DNS traffic analysis altogether, to address today's APT challenges. A preliminary experiment shows promising and better accuracy of APT recognition and faster response.

Performance comparison of caching strategy on wordpress multisite

Mandahadi Kusuma¹, Widyawan², and Ridi Ferdiana²

[1] Mahasiswa Pasca Sarjana Jurusan Teknik Elektro dan Teknik Informatika Universitas Gadjah Mada, Jln. Grafika 2 Yogyakarta 55281 Indonesia

[2] Departemen Teknik Elektro dan Teknologi Informasi Universitas Gadjah Mada, Jln. Grafika 2 Yogyakarta 55281 Indonesia

The usage of http accelerator for web server is common, meanwhile Object cache on wordpress multisite can be stored using redis database. By utilizing http accelerator and redis as cache combination strategy on wordpress multisite we can maximize the wordpress client capacity. The conducted experiment already done show us that the most stable setup for cache combination is by separating object cache by its type. This setup could reduce mysql diskread activity by 60%. For static object such as image, css, and js suitable to be cached in http accelerator using varnish cache and for database activity object cache can be stored on database cache using redis cache. Using redis cache can reduce mysql server cpu usage for 25% and network traffic upto 94%. On client side, combination of varnish static cache and redis cache give 0% error rate it means the client capacity increased but the APDEX score not the best and average responsetime 17% slower (250ms difference) but it has 0% error rate for the same load compared to “varnish cache” and “varnish full cache + redis cache”.

Research of university sites internal links distribution

Ivan Blekanov¹, Sergei Sergeev¹, Aleksei Maksimov¹, and Roman Moskalets¹

[1] Applied Mathematics and Control Processes, Saint Petersburg State University, 7-9 Universitetskaya Naberezhnaya, 199034, Russian Federation

The article covers the university websites webpages distribution analysis in terms of the number of incoming internal links. Papers by A. Broder and R. Kumar (2000), Barabasi and Albert (1999) represent, that the distribution follows a power law with the exponent of around 2.1. However, we have recently developed a method that allows to size up website's webpages by studying just 10% of the site itself. Within the research we came across the idea, that university sites have particular characteristics, therefore they have a different exponent. This article contains the description of the experiment results conducted by the article authors, the experiment includes 97 university sites from top 500 Webometrics ranking. Power approximating curves, that describe incoming links distribution, have been drawn for each site. The average exponent among all sites is about 1.8.

Construction inverted index for dynamic collections visualization in thematic virtual museums system

Sajarwo Anggai¹, Ivan Stanislavovich Blekanov¹, and Sergei Lvovich Sergeev¹

[1] Applied Mathematics and Control Processes, St. Petersburg State University, 7-9 Universitetskaya Naberezhnaya, 199034, Russian Federation

Thematic virtual museum system main goal is providing more relevant information based on user characteristic, behavior and desire. Thematic exhibition as main unique feature very considering on users' whole activities. Barry and Maria define creation of new knowledge, transformative and self-directed experiences, engagement with the full diversity of visitors, and transparency as the source of a viewpoint of the exhibition as museum specific evaluation criteria. Museum exhibition is not book on the wall rather than leading visitors to new attitudes, values and ideas even in very different cultural backgrounds or religious beliefs. The system with interactive information in the thematic exhibition which has been processing and delivering to the user will be leading to the better understanding by traveling in similar fields. In order to accomplish those tasks, this research have been performed and constructed thematic virtual museums inverted index to gain fastest retrieval document collections. The system is using special architecture and multi system indexing in thematic virtual museum inverted index. This index can manage collection in many forms of data structured, semi structured or unstructured which have processed by data access layer engine. In this paper showed a design and modification of the inverted index experimental result for thematic virtual museums system and a sample of exhibition visualization to get more precision by embedding method.