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29,905 Article Results

Quantitative Analysis of Plant Growth Exposed to Electric Fields

10.12928/telkomnika.v14i2.2596
Hussein; Universiti Tun Hussein Onn Malaysia Ahmad , Mohd Hafizi; Institute of High Voltage and High Current Ahmad , Noor 'Aliaa; Universiti Teknologi Malaysia Awang , Izzah Hazirah; Universiti Teknologi Malaysia Zakaria
 Electromagnetic radiations present in the environment has a profound effect on the growth of vegetable plant primarily grown under the high power transmission lines. The high electric field generated due to ultra high voltage causes the increase and reduction in the size of the plants. Numerous research have been carried out to investigate the effect of electric field on the plants. However, the knowledge in term of quantitative analysis on the effect of electric field on the growth of vegetables is not entirely understood. Thus, this paper presents a study conducted to investigate the effect of high voltage DC electric fields on the young vegetables growth namely ‘Choy Sam’ and bean sprout. The experimental setup was designed which composed of two parallel plate electrodes. This research was focused on the percentage of germination and growing rate of young vegetables. The growth of the young vegetables during exposure was calculated by using statistical methods. The analysis of the results showed that the electric fields and the electric fields treated water have influenced the germination rate and height of stems of both young vegetables causing the increase in stem height.
Volume: 14
Issue: 2
Page: 390-403
Publish at: 2016-06-01

Quadrotor Path Planning Based on Modified Fuzzy Cell Decomposition Algorithm

10.12928/telkomnika.v14i2.2989
Iswanto; Universitas Muhammadiyah Yogyakarta Iswanto , Oyas; Universitas Gadjah Mada Wahyunggoro , Adha; Universitas Gadjah Mada Imam Cahyadi
The purpose of this paper is to present an algorithm to determine the shortest path for quadrotor to be able to navigate in an unknown area. The problem in robot navigation is that a robot has incapability of finding the shortest path while moving to the goal position and avoiding obstacles. Hence, a modification of several algorithms are proposed to enable the robot to reach the goal position through the shortest path. The algorithms used are fuzzy logic and cell decomposition algorithms, in which the fuzzy algorithm which is an artificial intelligence algorithm is used for robot path planning and cell decomposition algorithm is used to create a map for the robot path, but the merger of these two algorithms is still incapable of finding the shortest distance. Therefore, this paper describes a modification of the both algorithms by adding potential field algorithm that is used to provide weight values on the map in order for the quadrotor to move to its goal position and find the shortest path. The modification of the algorithms have shown that quadrotor is able to avoid various obstacles and find the shortest path so that the time required to get to the goal position is more rapid.
Volume: 14
Issue: 2
Page: 655-664
Publish at: 2016-06-01

Image Fusion in Hyperspectral Image Classification using Genetic Algorithm

10.11591/ijeecs.v2.i3.pp703-711
B. Saichandana , K. Srinivas , R. KiranKumar
Hyperspectral remote sensors collect image data for a large number of narrow, adjacent spectral bands. Every pixel in hyperspectral image involves a continuous spectrum that is used to classify the objects with great detail and precision. This paper presents hyperspectral image classification mechanism using genetic algorithm with empirical mode decomposition and image fusion used in preprocessing stage. 2-D Empirical mode decomposition method is used to remove any noisy components in each band of the hyperspectral data. After filtering, image fusion is performed on the hyperspectral bands to selectively merge the maximum possible features from the source images to form a single image. This fused image is classified using genetic algorithm. Different indices, such as K-means (KMI), Davies-Bouldin Index (DBI), and Xie-Beni Index (XBI) are used as objective functions. This method increases classification accuracy of hyperspectral image.
Volume: 2
Issue: 3
Page: 703-711
Publish at: 2016-06-01

Analysis of Reinforcement Based Adaptive Routing in MANET

10.11591/ijeecs.v2.i3.pp648-694
Rahul Desai , B P Patil
This paper describes and evaluates the performance of various reinforcement learning algorithms with shortest path algorithms that are widely used for routing packets through the network. Shortest path routing is the simplest policy used for routing the packets along the path having minimum number of hops. In high traffic or high mobility conditions, the shortest path get flooded with huge number of packets and congestions occurs, So such shortest path does not provides the shortest path and increases delay for reaching the packets to the destination. Reinforcement learning algorithms are adaptive algorithms where the path is selected based on the traffic present on the network at real time. Thus they guarantee the least delivery time to reach the packets to the destination. Analysis done on a 6 by 6 irregular grid and sample ad hoc network shows that performance parameters used for judging the network - packet delivery ratio and delay provides optimum results using reinforcement learning algorithms. 
Volume: 2
Issue: 3
Page: 648-694
Publish at: 2016-06-01

Fault Diagnosis of Power Network Based on GIS Platform and Bayesian Networks

10.12928/telkomnika.v14i2.2750
Yunfang; Agricultural University of Hebei Xie , Yuhong; Agricultural University of Hebei Zhou , Weina; Agricultural University of Hebei Liu
In order to determine the location of the fault components of the power network quickly and give troubleshooting solutions, this paper obtains a simplify structure of relay protection and circuit-breaker as key equipment by analyzing the power network topology of GIS platform and uses the Bayesian networks fault diagnosis algorithm and finally designs the power network fault diagnosis module based on GIS platform. Fault diagnosis algorithm based on Bayesian networks is a new method for power network fault diagnosis which deals with the power network fault diagnosis with incomplete alarm signals caused by the protection device’s and the circuit breaker’s malfunction or refusal to move, device failure of communication and other reasons in the use of Bayesian networks method.  This method establishes the transmission line fault diagnosis model by using Noisy-Or, Noisy-And node model and similar BP neural network back propagation algorithm, and obtains the fault trust degree of each component by using the formula, and finally determines the fault according to the fault trust degree. The practical engineering application shows that the search speed and accuracy of fault diagnosis are improved by applying the fault diagnosis module based on GIS platform and Bayesian network.
Volume: 14
Issue: 2
Page: 741-747
Publish at: 2016-06-01

Segway Line Tracer Using Proportional-Integral-Derivative Controllers

10.12928/telkomnika.v14i2.3156
Wijaya; Universitas Brawijaya Kurniawan , Mochammad Hannats Hanafi; Universitas Brawijaya Ichsan , Eko; Universitas Brawijaya Setiawan
Intelligent control, sensors and hardware integration are expected to generate an efficient transportation system and and minimum effort, to carry goods from one location to another location. Line tracer used by robot to transport follow the path, it has a system that uses a light sensor to read the color from a line that represent the path to make specific direction. Segway is two wheeled transportation item that have an efficient energy used. Nowadays line tracer can only work if it has three or more wheels and segway can only work with riders. This research segway designed by lego robot, PID (Proportional, Integral, Derivative) control used to control an input from gyroscope sensor in form of elevation angle of the earth. The control system are expected to control two wheeled Segway to reach steady state rapidly. So the Segway would run without involving human or without rider.
Volume: 14
Issue: 2
Page: 489-496
Publish at: 2016-06-01

The impact of LTE-FDD at the LTE-TDD for the co-existence under 2.6 GHz band for Malaysia

10.11591/ijeecs.v2.i3.pp657-667
L.M. Ahmed , M.F.L. Abdullah
For the co-existence scenario between LTE-FDD and LTE-TDD systems, if the two systems are using an adjacent frequency carrier, there will be a need for spatial separation between the eNodeBs of the two systems, otherwise the two systems will interfere each other. The study is implemented based on realistic parameters in order to help the network designer to make a decision about the best frequency allocation and network deployments in order to achieve higher performance under the lowest possible cost. Throughout this paper, the effect of the FDD system at the TDD is evaluated under wide range of ACIR and separation distances between the two systems eNodeBs as well. The results showed that, the recommended ACIR offset by the 3GPP is not enough for the LTE-TDD uplink throughput loss ratio to be acceptable, whereas 115 dB, 45 dB, and 35 dB of the ACIR is required for the throughput loss ratio in order to drop less than 5% for the co-located, Mid-point, and Edge-point eNodeBs deployment scenario respectively. Meanwhile, comparing to the uplink case, the downlink of the TDD system is much coherent; the recommended ACIR offset is only unacceptable for the co-located deployment case, whereas 50 dB of the ACIR is required for the system to drop less than 5%.
Volume: 2
Issue: 3
Page: 657-667
Publish at: 2016-06-01

Research on Community Detection Algorithm Based on the UIR-Q

10.12928/telkomnika.v14i2.2685
Zilong; Wuhan University of Technology Jiang , Wei; Hubei Polytechnic University Dai , Liangchen; Wuhan University of Technology Chen , Xiufeng; Wuhan University of Technology Cao , Yanling; Wuhan University of Technology Shao
Aiming at the current problems of community detection algorithm in which user’s property is not used; the community structure is not stable and the efficiency of the algorithm is low, this paper proposes a community detection algorithm based on the user influence and its parallelization method. In terms of the concept of user influence in the subject communication and the PageRank algorithm, this paper uses the properties of nodes of users in social networks to form the user influence factors. Then, the user with the biggest influence is set as the initial node of new community and and the local modularity is introduced into detecting the community structure.  in order to make the result of community detection quick and efficient. Many experiments show that the improved algorithm can efficiently detect the community structure with large scale users and the results are stable. Therefore, this algorithm will have a wide applied prospect.
Volume: 14
Issue: 2
Page: 725-733
Publish at: 2016-06-01

Comparative Analysis of Spatial Decision Tree Algorithms for Burned Area of Peatland in Rokan Hilir Riau

10.12928/telkomnika.v14i2.3540
Putri; Bogor Agricultural University Thariqa , Imas Sukaesih; Bogor Agricultural University Sitanggang , Lailan; Bogor Agricultural University Syaufina
 Over one-year period (March 2013 – March 2014), 58 percent of all detected hotspots in Indonesia are found in Riau Province. According to the data, Rokan Hilir shared the greatest number of hotspots, about 75% hotspots alert occur in peatland areas. This study applied spatial decision tree algorithms to classify classes before burned, burned, and after burned from remote sensed data of peatland area in Kubu and Pasir Limau Kapas subdistrict, Rokan Hilir, Riau. The decision tree algorithm based on spatial autocorrelation is applied by involving Neigborhood Split Autocorrelation Ratio (NSAR) to the information gain of CART algorithm. This spatial decision tree classification method is compared to the conventional decision tree algorithms, namely, Classification and Regression Trees (CART),  C5.0, and C4.5 algorithm. The experimental results showed that the C5.0 algorithm generate the most accurate classifier with the accuracy of  99.79%. The implementation of spatial decision tree algorithm succesfuly improve the accuracy of CART algorithm.
Volume: 14
Issue: 2
Page: 684-691
Publish at: 2016-06-01

Cluster Analysis for SME Risk Analysis Documents Based on Pillar K-Means

10.12928/telkomnika.v14i2.2385
Irfan; Bogor Agricultural University Wahyudin , Taufik; Bogor Agricultural University Djatna , Wisnu Ananta; Bogor Agricultural University Kusuma
In Small Medium Enterprise’s (SME) financing risk analysis, the implementation of qualitative model by giving opinion regarding business risk is to overcome the subjectivity in quantitative model. However, there is another problem that the decision makers have difficulity to quantify the risk’s weight that delivered through those opinions. Thus, we focused on three objectives to overcome the problems that oftenly occur in qualitative model implementation. First, we modelled risk clusters using K-Means clustering, optimized by Pillar Algorithm to get the optimum number of clusters. Secondly, we performed risk measurement by calculating term-importance scores using TF-IDF combined with term-sentiment scores based on SentiWordNet 3.0 for Bahasa Indonesia. Eventually, we summarized the result by correlating the featured terms in each cluster with the 5Cs Credit Criteria. The result shows that the model is effective to group and measure the level of the risk and can be used as a basis for the decision makers in approving the loan proposal. 
Volume: 14
Issue: 2
Page: 674-683
Publish at: 2016-06-01

Object Recognition Based on Maximally Stable Extremal Region and Scale-Invariant Feature Transform

10.12928/telkomnika.v14i2.2754
Hongjun; Suzhou University Guo , Lili; Suzhou University Chen
For the defect in describing affine and blur invariable of scale-invariant feature transform (SIFT) at large viewpoint variation, a new object recognition method is proposed in this paper, which used maximally stable extremal region (MSER) detecting MSERs and SIFT describing local feature of these regions. First, a new most stability criterion is adopt to improve the detection effect at irregular shaped regions and under blur conditions; then, the local feature descriptors of MSERs is extracted by the SIFT; and finally, the method proposed is comparing then correct rate of SIFT and the proposed through image recognition with standard test images. Experimental results show that the method proposed can still achieve more than 74% recognition correct rate at different viewpoint, which is better than SIFT.
Volume: 14
Issue: 2
Page: 622-629
Publish at: 2016-06-01

Improved Output Voltage Quality using Space Vector Modulation for Multilevel Inverters

10.12928/telkomnika.v14i2.3111
Auzani; Universiti Teknikal Malaysia Melaka Jidin , Syamim; Universiti Teknikal Malaysia Melaka Sanusi , Tole; Universitas Ahmad Dahlan Sutikno , Nik Rumzi; Universiti Teknologi Malaysia Nik Idris
Space vector modulation (SVM) has received wide acceptance due to many benefits over other techniques such as higher output voltages, lower total harmonic distortion (THD), high-efficiency and flexible to be implemented in vector control systems. In digital implementation, the SVM equations can be optimally computed by eliminate the use of complex forms. In this paper, the simple SVM based on two-level inverter is employed for higher levels of inverters. This is to retain the simplicity of SVM computation for three-level and five-level cascaded H-bridge multilevel inverter (CHMI). Moreover, the proposed method utilizes two controller boards to perform high computational workloads and to eliminate glitch and error problems. Experiment results show that the THD of output voltage in five-level CHMI gives the smallest value among the results obtained from other levels.
Volume: 14
Issue: 2
Page: 387-389
Publish at: 2016-06-01

Development of Coastal Radar Network at Sunda Strait

10.12928/telkomnika.v14i2.2497
Sulistyaningsih; Indonesian Institute of Sciences (LIPI) Sulistyaningsih , Mashury; Indonesian Institute of Sciences (LIPI) Wahab , Dadin; Indonesian Institute of Sciences (LIPI) Mahmudin , Deni; Indonesian Institute of Sciences (LIPI) Permana , Yudi Yulius; Indonesian Institute of Sciences (LIPI) Maulana , Topik Teguh; Indonesian Institute of Sciences (LIPI) Estu
In this paper, development on a coastal surveillance Radar network, which is called ISRA (Indonesian Sea Radar), is presented. This Radar network was developed for surveillance at the Sunda Strait. The radar network monitors the sea traffics and activities at the Sunda Strait, which an international shipping route. There were three Radars installed for this network. All these Radars in this research use FM-CW (Frequency Modulated Continuous Wave) technology. This FM-CW has an advantage of low power consumption, low cost of operational, longer life time and high reliability. Another important feature of this Radar is the LPI (Low Probability of Intercept) capability, where the signal transmission of this Radar cannot be easily detected by a Radar detector (electronic support measure) so that this Radar can be used for a covert operation. Detected targets by Radars are shown on the display and on the web based display for the Radar network. These three Radars on the remote sites can be monitored and controlled via an internet connection from the control room in our Bandung office, which is 300 KMs away. The results of this research and development show the Indonesian capability to build a complex system such as a chain of coastal surveillance Radar network. The knowledge obtained from this research will be used to develop more advanced Radars for different applications.
Volume: 14
Issue: 2
Page: 507-514
Publish at: 2016-06-01

Dual DC Motor Speed Control Based on Two Independent Digital PWM Signals using PIC16F877A Microcontroller

10.11591/ijeecs.v2.i3.pp592-606
Ayman Y. Yousef , M. H. Mostafa
In this paper a dual open loop speed control system based on two independent PWM signals of small permanent magnet DC (PMDC) motors using PIC16F877A microcontroller (MCU) has been designed and implemented. The Capture/Compare/PWM (CCP) modules of the MCU are configured as PWM mode and the MCU is programmed using flowcode software package to generate two PWM signals with various duty cycles at the same frequency. A dual H-bridge channel chip SN754410 is used to drive the motors. The variation of PWM duty cycles is related directly to controlling the DC motors terminal voltage which directly proportional with speed of each motor. The complete PWM control system model has been simulated using proteus design suite software package. The development of hardware and software of the dual DC motor speed control system has been explained and clarified.
Volume: 2
Issue: 3
Page: 592-606
Publish at: 2016-06-01

Hierarchical i* Modeling in Requirement Engineering

10.12928/telkomnika.v14i2.3333
Kridanto; Institute of Technology Bandung Surendro , Cicely Martini; Institute of Technology Bandung Asihwardji
Requirement engineering is the earliest phases of the development process of information systems in which there is a process to understand the needs of system users and formulate it into a format that facilitates the process of analysis. Requirement engineering approach through intentional perspective is one of the arguments that appear in the field. In intentional modeling, the focus will lie on the motive of every actor, how each actor can achieve their motives, and what dependencies present in order to achieve that motive. Some existing intentional modeling still has some limitations. Modeling is still having complexity problem when it will be used to model real-world situations that are quite large. Another disadvantage is how to describe the hierarchical conditions in intentional modeling. This research is to develop existing intentional modeling, in order to overcome limitations in describing the hierarchical conditions.
Volume: 14
Issue: 2
Page: 784-790
Publish at: 2016-06-01
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