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31,456 Article Results

Effect analysis of the different channel length and depth of photovoltaic thermal system with ∇-groove collector

10.11591/ijece.v10i2.pp1200-1207
Saprizal Hadisaputra , Muhammad Zohri , Bahtiar Bahtiar , Ahmad Fudholi
The converted Solar energy as electrical and thermal energy was named photovoltaic thermal (PVT). The aim of this study is to the analysis of different length and depth channel effect of photovoltaic thermal with ∇-groove collector by a mathematical model. The matrix inversion was used to analyze the energy balance equation. Simulation results were conducted below the solar intensity of 800 W/m2 and mass flow rate between 0.0069 kg/s and 0.0491 kg/s. Electrical and thermal efficiency was done to assess the effect of different length and channel depth of PVT system with ∇-groove collector. The effect of different length and depth of ∇-groove collector for electrical and thermal performance is caused by changed mass flow rate. The effect Increasing of the mass flow rate of collector increased the thermal and electrical performance of the ∇-groove collector.
Volume: 10
Issue: 2
Page: 1200-1207
Publish at: 2020-04-01

Feature extraction of Jabon (Anthocephalus sp) leaf disease using discrete wavelet transform

10.12928/telkomnika.v18i2.10714
Felliks Feiters; Bogor Agricultural University Tampinongkol , Yeni; Bogor Agricultural University Herdiyeni , Elis Nina; Bogor Agricultural University Herliyana
Jabon (Anthocephalus cadamba (Roxb.) Miq) is one type of forest plants that have very rapid growth until the process of the harvest. One inhibitor is a disease that attacks the leaves in the form of spots and blight that can cause death during the growth process of this tree. The purpose of this process is to detect the object of diseases that attack the leaves of jabon at the time in the nursery. Images of affected jabon leaf disease segmented by reducing the RGB color cylinders to separate the disease object from the background. Reduced channel G-R provides information in the form of disease areas contained in the image of Jabon leaf. Furthermore, the characteristics of leaf disease can be detected well using DWT in the 3-level decomposition process with SVM classification results that can separate both classes of spots and blight by 84.672%.
Volume: 18
Issue: 2
Page: 740-751
Publish at: 2020-04-01

Foreign exchange prediction based on indices and commodities price using convolutional neural network

10.11591/ijeecs.v18.i1.pp494-501
Rian Rassetiadi , Suharjito Suharjito
The level of accuracy in predicting is the key in conducting forex trading activities in gaining profits. Some predictions are made only by using historical currency data to be predicted, this makes predictions less accurate because they do not consider external influences. This study examines external factors that can influence the results of predictions, by looking for the relationship between the value of indices such as NTFSE and S & P 500 and the value of commodities such as gold and silver to the prediction process of EUR / USD. Prediction carried out using a deep learning algorithm with the Convolutional Neural Network method uses 2 1-dimensional convolution layers with ReL activation. The data used is the value of Open, High, Low and Close prices on forex, indices and commodities which are combined into one with the close forex value target for the next 5 days. Testing of EUR / USD test data only gets MSE results of 0.00081894. While the results of testing of the combined test data between EUR / USD, indices and commodities producing MSE vary between 0.00068717 to 0.0109606 where the best combination is a combination of FTSE 100 and Natural Gas values. So it can be concluded that other factors included in predicting have an influence on the results obtained.
Volume: 18
Issue: 1
Page: 494-501
Publish at: 2020-04-01

Projective and hybrid projective synchronization of 4-D hyperchaotic system via nonlinear controller strategy

10.12928/telkomnika.v18i2.14664
Zaidoon Sh.; University of Mosul Al-Talib , Saad Fawzi; University of Mosul Al-Azzawi
Nonlinear control strategy was established to realize the Projective Synchronization (PS) and Hybrid Projective Synchronization (HPS) for 4-D hyperchaotic system at different scaling matrices. This strategy, which is able to achieve projective and hybrid projective synchronization by more precise and adaptable method to provide a novel control scheme. On First stage, three scaling matrices were given in order to achieving various projective synchronization phenomena. While the HPS was implemented at specific scaling matrix in the second stage.  Ultimately, the precision of controllers were compared and analyzed theoretically and numerically. The long-range precision of the proposed controllers are confirmed by third stage.
Volume: 18
Issue: 2
Page: 1012-1020
Publish at: 2020-04-01

Comparative analysis and implementation of structured edge active contour

10.11591/ijece.v10i2.pp1842-1848
Brijesh N. Shah , Jaymin K. Bhalani
This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image.In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared.It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.
Volume: 10
Issue: 2
Page: 1842-1848
Publish at: 2020-04-01

DWT-SMM-based audio steganography with RSA encryption and compressive sampling

10.12928/telkomnika.v18i2.14833
Fikri; Telkom University Adhanadi , Ledya; Telkom University Novamizanti , Gelar; Telkom University Budiman
Problems related to confidentiality in information exchange are very important in the digital computer era. Audio steganography is a form of a solution that infuses information into digital audio, and utilizes the limitations of the human hearing system in understanding and detecting sound waves. The steganography system applies compressive sampling (CS) to the process of acquisition and compression of bits in binary images. Rivest, Shamir, and Adleman (RSA) algorithms are used as a system for securing binary image information by generating encryption and decryption key pairs before the process is embedded. The insertion method uses statistical mean manipulation (SMM) in the wavelet domain and low frequency sub-band by dividing the audio frequency sub-band using discrete wavelet transform (DWT) first. The optimal results by using our system are the signal-to-noise ratio (SNR) above 45 decibel (dB) and 5.3833 bit per second (bps) of capacity also our system has resistant to attack filtering, noise, resampling and compression attacks.
Volume: 18
Issue: 2
Page: 1095-1104
Publish at: 2020-04-01

Physical security with power beacon assisted in half-duplex relaying networks over Rayleigh fading channel: performance analysis

10.12928/telkomnika.v18i2.15857
Phu Tran; Industrial University of Ho Chi Minh City Tin , Duy-Hung; Ton Duc Thang University Ha , Luu Gia; Posts and Telecommunications Institute of Technology Ho Chi Minh City Campus Thien , Tran Thanh; National Key Laboratory of Digital Control and System Engineering Trang
In this research, we proposed and investigated physical security with power beacon assisted in half-duplex relaying networks over a Rayleigh fading channel. In this model, the source (S) node communicates with the destination (D) node via the helping of the intermediate relay (R) node. The D and R nodes harvest energy from the power beacon (PB) node in the presence of a passive eavesdropper (E) node. Then we derived the integral form of the system outage probability (OP) and closed form of the intercept probability (IP). The correctness of the analytical of the OP and IP is verified by the Monte Carlo simulation. The influence of the main system parameters on the OP and IP also is investigated. The research results indicated that the analytical results are the same as the simulation ones.
Volume: 18
Issue: 2
Page: 1072-1078
Publish at: 2020-04-01

Integration of IoT and chatbot for aquaculture with natural language processing

10.12928/telkomnika.v18i2.14788
M.; Politeknik Elektronika Negeri Surabaya (PENS) Udin Harun Al-Rasyid , Sritrusta; Politeknik Elektronika Negeri Surabaya (PENS) Sukaridhoto , Muhammad Iskandar; Politeknik Elektronika Negeri Surabaya (PENS) Dzulqornain , Ahmad; Politeknik Elektronika Negeri Surabaya (PENS) Rifai
The development of internet of things (IoT) technology is very fast lately. One sector that can be implemented by IoT technology is the aquaculture sector. One important factor in the success of aquaculture is a good and controlled water quality condition. But the problem for the traditional aquaculture farmers is to monitor and increase the water quality quickly and efficiently. To resolve the above-mentioned problem, this paper proposes a real-time monitoring system for aquaculture and supported with chatbot assistant to facilitate the user. This system was composed of IoT system, cloud system, and chatbot system. The proposed system consists of 7 main modules: smart sensors, smart aeration system, local network system, cloud computing system, client visualization data, chatbot system, and solar powered system. The smart aeration system consists of NodeMCU, relay, and aerator. The smart sensors consist of several sensors such as dissolved oxygen, pH, temperature, and water level sensor. Natural language processing is implemented to build the chatbot system. By combining text mining processing with naive Bayes algorithm, the result shows the very good performance with high precision and recall for each class to monitor the quality of water in aquaculture sector.
Volume: 18
Issue: 2
Page: 640-648
Publish at: 2020-04-01

Controlling a knee CPM machine using PID and iterative learning control algorithm

10.12928/telkomnika.v18i2.14876
Dechrit; Rajamanggala University of Technology Thanyaburi Pathumtani Maneetham , Petrus; Politeknik Mekatronika Sanata Dharma Sutyasadi
A conventional continuous passive motion (CPM) machine uses simple controller such as On/Off controller. Some better CPMs use PID controller. These kind of CPMs can not distinguish load different due to the different size of the patient leg. This may cause the CPM no longer follow the trajectory or the angle commands. Meanwhile, each patient may have different scenario of therapy from the others. When progress on the patient exists, the range of the flexion may be increased step by step. Therefore, the treatment can be different in term of the range of flexion from time to time. This paper proposes CPM with hybrid proportional integral derivative (PID) and iterative learning controller (ILC). The system has capability in learning the trajectory tracking. Therefore, the CPM will be able to follow any load or trajectory changes applied to it. The more accurate CPM machine can follow the trajectory command, the better its performance for the treatment. The experiment showed that the system was stable due to the PID controller. The tracking performance also improved with the ILC even there exist some disturbances.
Volume: 18
Issue: 2
Page: 1047-1053
Publish at: 2020-04-01

Benchmark and comparison between hyperledger and MySQL

10.12928/telkomnika.v18i2.13743
Onno W.; Institut Informatika dan Bisnis Darmajaya Purbo , Sriyanto; Institut Informatika dan Bisnis Darmajaya Sriyanto , Suhendro; Institut Informatika dan Bisnis Darmajaya Suhendro , Rz Abd.; Institut Informatika dan Bisnis Darmajaya Aziz , Riko; Institut Informatika dan Bisnis Darmajaya Herwanto
In this paper, we report the benchmarking results of Hyperledger,  a Distributed Ledger, which is the derivation Blockchain Technology.  Method to evaluate Hyperledger in a limited infrastructure is developed. Themeasured infrastructure consists of 8 nodes with a load of up to 20000 transactions/second. Hyperledger consistently runs all evaluation, namely, for 20,000 transactions, the run time 74.30s, latency 73.40ms latency, and 257 tps. The benchmarking of Hyperledger shows better than a database system in a high workload scenario. We found that the maximum size data volume in one transaction on the Hyperledger network is around ten (10) times of MySQL. Also, the time spent on processing a single transaction in the blockchain network is 80-200 times faster than MySQL. This initial analysis can provide an overview for practitioners in making decisions about the adoption of blockchain technology in their IT systems.
Volume: 18
Issue: 2
Page: 705-715
Publish at: 2020-04-01

Scheme for motion estimation based on adaptive fuzzy neural network

10.12928/telkomnika.v18i2.14752
Fredy; Universidad Distrital Francisco José de Caldas Martinez , Cristian; Universidad Distrital Francisco José de Caldas Penagos , Luis; Universidad Distrital Francisco José de Caldas Pacheco
Many applications of robots in collaboration with humans require the robot to follow the person autonomously. Depending on the tasks and their context, this type of tracking can be a complex problem. The paper proposes and evaluates a principle of control of autonomous robots for applications of services to people, with the capacity of prediction and adaptation for the problem of following people without the use of cameras (high level of privacy) and with a low computational cost. A robot can easily have a wide set of sensors for different variables, one of the classic sensors in a mobile robot is the distance sensor. Some of these sensors are capable of collecting a large amount of information sufficient to precisely define the positions of objects (and therefore people) around the robot, providing objective and quantitative data that can be very useful for a wide range of tasks, in particular, to perform autonomous tasks of following people. This paper uses the estimated distance from a person to a service robot to predict the behavior of a person, and thus improve performance in autonomous person following tasks. For this, we use an adaptive fuzzy neural network (AFNN) which includes a fuzzy neural network based on Takagi-Sugeno fuzzy inference, and an adaptive learning algorithm to update the membership functions and the rule base. The validity of the proposal is verified both by simulation and on a real prototype. The average RMSE of prediction over the 50 laboratory tests with different people acting as target object was 7.33.
Volume: 18
Issue: 2
Page: 1030-1037
Publish at: 2020-04-01

Enhanced whale optimization algorithm for active power loss diminution

10.11591/ijict.v9i1.pp19-23
Kanagasabai Lenin
In this paper Enhanced whale Optimization Algorithm (EWO) proposed to solve the optimal reactive power problem. Whale optimization algorithm is modeled by Bubble-net hunting tactic. In the projected optimization algorithm an inertia weight ω ∈ [1, 0] has been introduced to perk up the search ability. Whales are commonly moving 10-16 meters down then through the bubbles which are created artificially then they encircle the prey and move upward towards the surface of sea. Proposed Enhanced whale optimization algorithm (EWO) is tested in standard IEEE 57 bus systems and power loss reduced considerably.
Volume: 9
Issue: 1
Page: 19-23
Publish at: 2020-04-01

Rogowski coil sensor in the digitization process to detect partial discharge

10.12928/telkomnika.v18i2.14282
Eka Putra; Universitas Andalas Waldi , Asri Indah; Universitas Andalas Lestari , Rudy; Universitas Andalas Fernandez , Syaifa; Universitas Andalas Mulyadi , Yoshinobu; Toyohashi University of Technology Murakami , Naohiro; Toyohashi University of Technology Hozumi
This paper presents the construction of a Rogowski Coil sensor with an air core to detect partial discharge using a digital oscilloscope. Two types of sensors are used. The first is the primary sensor winding with back wire, and the second is without back wire, labeled BW and WBW, respectively. The numbers of primary-turn in the sensors are 5, 10, 20, and 40 turns. The performance of the sensors is tested using two types of tests. First, the wave response test with a fixed imitation partial discharge magnitude input is used to select the optimum sensitivity with the lower sampling rate, aims to select the peak or valley value as a magnitude partial discharge value. The second test is using an imitation partial discharge ramp to check the linearity of the sensors. The imitation of the partial discharge inputs is generated by a commercial charge calibrator. The wave response test results show an increase in the number of turns that corresponds to an increase of the sensor output for both sensors in a non-linear trend. In determining the sampling rate, the detection of magnitude in the valley is better than the peak. All sensors act linear toward the imitation partial discharge ramp either in BW or WBW conditions.
Volume: 18
Issue: 2
Page: 1062-1071
Publish at: 2020-04-01

Forecasting rupiah exchange rate with learning vector quantization neural network

10.11591/ijeecs.v18.i1.pp24-31
Linawati Linawati , Made Sudarma , I Putu Oka Wisnawa
The classification technique and data forecasting will probably be one of the techniques that will often be needed in handling or managing big data. So, from that the author analyzes the possible development of the existing algorithms. The purpose is to find possibilities in the use of reliable algorithms in a particular field, then can be adopted and implemented to develop forecasting techniques in the future. Based on these considerations, the authors conducted experiments by applying LVQNN to conduct shortterm forecasting on daily period of the Rupiah exchange rate. The literature that is used as a reference is the discovery of architectural data classification processes that resemble forecasting techniques. So, when there is a combination of Rupiah exchange histories, it is possible to find these combinations into certain classes based on predetermined parameters and historical data combination data and forecast values in the past. In this research the factors chosen as indicators that affect the Rupiah exchange rate are the amount of exports, the amount of imports, the inflation rate and also the world oil price. In this research the highest accuracy value in the testing process for the population reached 99.0991%. The increase in the percentage value of forecasting accuracy is influenced by the composition of the data. In this study the formation of data composition is influenced by distinct data. The selection of parameters which become distinct claused determines how the composition of the data will be formed. If the composition of the data is not correct, the test results will not be good. If the number of weights vector is smaller than the input data, the forecasting accuracy will decrease. Because the weight vector cannot represent data combinations that used during training or testing.
Volume: 18
Issue: 1
Page: 24-31
Publish at: 2020-04-01

HAR-MI method for multi-class imbalanced datasets

10.12928/telkomnika.v18i2.14818
H.; STMIK IBBI Hartono , Yeni; STMIK IBBI Risyani , Erianto; Akademi Teknologi Industri Immanuel Ongko , Dahlan; Universitas Malikussaleh Abdullah
Research on multi-class imbalance from a number of researchers faces obstacles in the form of poor data diversity and a large number of classifiers. The Hybrid Approach Redefinition-Multiclass Imbalance (HAR-MI) method is a Hybrid Ensembles method which is the development of the Hybrid Approach Redefinion (HAR) method. This study has compared the results obtained with the Dynamic Ensemble Selection-Multiclass Imbalance (DES-MI) method in handling multiclass imbalance. In the HAR-MI Method, the preprocessing stage was carried out using the random balance ensembles method and dynamic ensemble selection to produce a candidate ensemble and the processing stages was carried out using different contribution sampling and dynamic ensemble selection to produce a candidate ensemble. This research has been conducted by using multi-class imbalance datasets sourced from the KEEL Repository. The results show that the HAR-MI method can overcome multi-class imbalance with better data diversity, smaller number of classifiers, and better classifier performance compared to a DES-MI method. These results were tested with a Wilcoxon signed-rank statistical test which showed that the superiority of the HAR-MI method with respect to DES-MI method.
Volume: 18
Issue: 2
Page: 822-829
Publish at: 2020-04-01
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