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EMITTER International Journal of Engineering Technology

EMITTER
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Published by Politeknik Elektronika Negeri Surabaya

ISSN : 2355391x EISSN : - DOI : -

Core Subject : Science,

Computer Science & IT

EMITTER International Journal of Engineering Technology is a BI-ANNUAL journal published by Politeknik Elektronika Negeri Surabaya (PENS). It aims to encourage initiatives, to share new ideas, and to publish high-quality articles in the field of engineering technology and available to everybody at no cost. It stimulates researchers to explore their ideas and enhance their innovations in the scientific publication on engineering technology. EMITTER International Journal of Engineering Technology primarily focuses on analyzing, applying, implementing and improving existing and emerging technologies and is aimed to the application of engineering principles and the implementation of technological advances for the benefit of humanity.

Arjuna Subject : -

Articles 436 Documents

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Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor Bayu Praharsena; Era Purwanto; Arma Jaya; Muhammad Rizani Rusli; Handri Toar; Ridwan wk
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

The operation of induction motors with high performance contributes significantly to the global energy savings but hysteresis loss is one of the factors causing decreased performance. Stator flux density (B) and magnetic field intensity (H) must be plotted to know hysteresis loss quantity. Unfortunately, since the rotor rotates in time series, the stator flux density is unmeasurable quantities, itâ€™s hard to direct sensored this properties because of limited airgap space and costly to install additional instrument. The purpose of this paper is to evaluate the hysteresis loss quantity in induction motor using a novel method of multilayer perceptron feed forward neural network as stator flux estimator and magnetizing current model as magnetic field intensity properties. This method is effective, because itâ€™s non-destructive method, without an additional instrument, low cost, and suitable for real-time motor drive systems. The FFNN estimator response is satisfying because accurately estimate stator flux density for evaluating hysteresis loss quantity including its magnitude and phase angle. By using the proposed model, the stator flux density and magnetizing current can be plotted become hysteresis loss curve. The performance of flux response, speed response, torque response and error deviation of stator flux estimator has been presented, investigated, compared and verified in Simulink Matlab.

Arrhythmia Classification Using Long Short-Term Memory with Adaptive Learning Rate Hilmy Assodiky; Iwan Syarif; Tessy Badriyah
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Arrhythmia is a heartbeat abnormality that can be harmless or harmful. It depends on what kind of arrhythmia that the patient suffers. People with arrhythmia usually feel the same physical symptoms but every arrhythmia requires different treatments. For arrhythmia detection, the cardiologist uses electrocardiogram that represents the cardiac electrical activity. And it is a kind of sequential data with high complexity. So the high performance classification method to help the arrhythmia detection is needed. In this paper, Long Short-Term Memory (LSTM) method was used to classify the arrhythmia. The performance was boosted by using AdaDelta as the adaptive learning rate method. As a comparison, it was compared to LSTM without adaptive learning rate. And the best result that showed high accuracy was obtained by using LSTM with AdaDelta. The correct classification rate was 98% for train data and 97% for test data.

Trusted Data Transmission Using Data Scrambling Security Method with Asymmetric Key Algorithm for Synchronization Nihayatus Sa'adah; I Gede Puja Astawa; Amang Sudarsono
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Security is a major concern of the internet world because the development of the Internet requires the security of data transmission. The security method helps us to store valuable information and send it over an insecure network so that it can not be read by anyone except the intended recipient. Security algorithm uses data randomization method. This method of data information randomization has a low computation time with a large number of bits when compared to other encryption algorithms. In general, the encryption algorithm is used to encrypt data information, but in this research the encryption algorithm is used for synchronization between the sender and the intended recipient. Number of bits on asymmetric key algorithm for synchronization are the 64-bits, 512-bits and 1024-bits. We will prove that security methods can secure data sent with low computational time with large number of bits. In the result will be shown the value of computing time with variable number of bits sent. When data are sent by 50 bytes, encryption time required 2 ms using 1024 bits for synchronization technique asymmetric key algorithm.Â

Rule-based Sentiment Degree Measurement of Opinion Mining of Community Participatory in the Government of Surabaya Berlian Juliartha Martin Putra; Afrida Helen; Ali Ridho Barakbah
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Diskominfo Surabaya, as a government agency, received much community participatory for improvement of governmental services, with increasing number of 698, 2717, 4176 and 4298 participatory data respectively in 2011, 2012, 2013 and 2014. It is challenging for Diskominfo Surabaya to set a target by giving the response back within 24 hours. Due to task complexity to address the degree of participatory and to categorize the group of participatory, they faced difficulty to fulfill the target. In this research, we present a new system for measuring the sentiment degree of community participatory. We provide 5 functions in our system, which are: (1) Data Collection, (2) Data Preprocessing, (3) Text Mining, (4) Sentiment Analysis and (5) Validation. We propose our rule-based technique for the sentiment analysis of opinion mining with detection of 8 important parts, which are (1) Verb, (2) Adjective, (3) Preposition, (4) Noun, (5) Adverb, (6) Symbol, (7) Phrase, and (8) Complimentary. For applicability of our proposed system, we made a series of experiment with 410 data of community participatory in Twitter for Diskominfo Surabaya and compared with other sentiment classification algorithms which are SVM and Naive Bayes Classifier. Our system performed 77.32% rate of accuracy and outperformed to other comparing algorithms.

Adaptive Modulation and Coding (AMC) around Building Environment for MS Communication at The Train Andrita Ceriana Eska
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

This paper focused at communication systems when train moved. The communication propagation was influenced by building environment. The communication condition that used uplink direction. Mobile station was placed inside the train where moved with 500 km/hour velocity. The analysis was used consists of Doppler effect, atmospheric, and building environment. The variation communication frequency was used consists of 2.6 GHz, 5 GHz, and 10 GHz. Diffraction mechanism caused building was used single knife edge method. The result was showed SNR value from the communication frequency variation, distance comparison between LOS and NLOS, alteration adaptive modulation and coding (AMC), and coverage area percentage. Modulation and Coding Scheme (MCS) was used for AMC consists of QPSK, 16 QAM, and 64 QAM. Decreases of SNR value can be occured when communication distance for NLOS condition farther then LOS condition. That distance became increases because was obstructed with high building. Changeable of AMC value was caused propagation condition. The coverage area percentage when communication frequency that was used consists of 2.6 GHz, 5 GHz, and 10 GHz was obtained 88.4%, 88.4%, and 81.7%.

Classification Algorithms of Maternal Risk Detection For Preeclampsia With Hypertension During Pregnancy Using Particle Swarm Optimization Muhlis Tahir; Tessy Badriyah; Iwan Syarif
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Preeclampsia is a pregnancy abnormality that develops after 20 weeks of pregnancy characterized by hypertension and proteinuria. Â The purpose of this research was to predict the risk of preeclampsia level in pregnant women during pregnancy process using Neural Network and Deep Learning algorithm, and compare the result of both algorithm. There are 17 parameters that taken from 1077 patient data in Haji General Hospital Surabaya and two hospitals in Makassar start on December 12th 2017 until February 12th 2018. We use particle swarm optimization (PSO) as the feature selection algorithm. This experiment shows that PSO can reduce the number of attributes from 17 to 7 attributes. Using LOO validation on the original data show that the result of Deep Learning has the accuracy of 95.12% and it give faster execution time by using the reduced dataset (eight-speed quicker than the original data performance). Beside that the accuracy of Deep Learning increased 0.56% become 95.68%. Generally, PSO gave the excellent result in the significantly lowering sum attribute as long as keep and improve method and precision although lowering computational period. Deep Learning enables end-to-end framework, and only need input and output without require for tweaking the attributes or features and does not require a long time and complex systems and understanding of the deep data on computing.

Nuclei Detection and Classification System Based On Speeded Up Robust Feature (SURF) Neneng Nur Amalina; Kurniawan Nur Ramadhani; Febryanti Sthevanie
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Tumors contain a high degree of cellular heterogeneity. Various type of cells infiltrate the organs rapidly due to uncontrollable cell division and the evolution of those cells. The heterogeneous cell type and its quantity in infiltrated organs determine the level maglinancy of the tumor. Therefore, the analysis of those cells through their nuclei is needed for better understanding of tumor and also specify its proper treatment. In this paper, Speeded Up Robust Feature (SURF) is implemented to build a system that can detect the centroid position of nuclei on histopathology image of colon cancer. Feature extraction of each nuclei is also generated by system to classify the nuclei into two types, inflammatory nuclei and non-inflammatory nuclei. There are three classifiers that are used to classify the nuclei as performance comparison, those are k-Nearest Neighbor (k-NN), Random Forest (RF), and State Vector Machine (SVM). Based on the experimental result, the highest F1 score for nuclei detection is 0.722 with Determinant of Hessian (DoH) thresholding = 50 as parameter. For classification of nuclei, Random Forest classifier produces F1 score of 0.527, it is the highest score as compared to the other classifier.

Analysis on Handwritten Document Text to Identify Human Personality Characteristics by Using Preprocessing and Feature Extraction Lukie Perdanasari; Riyanto Sigit; Achmad Basuki
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

It is important that a company uses the right means to recruit employees with certain personal characteristics as needed. Nowadays, the techniques to respond to psychological tests on peopleâ€™s characteristics have been widely understood by most job applicants, so that it is difficult to know their true personality. Graphology is a way to identify a personâ€™s characteristics by analyzing the handwriting from the document text made by the applicant. The two types of text document of each applicant are obtained from people of different ages and different writing times. The methods of graphology used in this research for identifying the handwriting are preprocessing and feature extraction. The preprocessing method uses projection integrals, shear transformations, and template matching. While the feature extraction process applies 10 features, they are, margins, line spacing, space between words, size of writing, style, zone, direction of writing, slope of writing, width of writing and shape of the letter. The result of the experiment from five writers shows the accuracy of writing identification equals to 82%, while personality identification equals to 67,4%.

Performance and Economic Analysis of Multi-Rotor Wind Turbine Navjot Singh Sandhu; Saurabh Chanana
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Power production of a wind turbine is dependent upon its rotor size and at present wind turbines with large rotor diameter (>175 m) are available in the market. However major problems associated with such large size conventional turbines are their cost & noise pollution. Due to these reason researchers have diverted their attention towards lower sized equivalent multi-rotor wind turbines. These turbines are found to be cheaper and good performers. Keeping it in view, in this paper an effort has been made to compare the energy yield and economics of two types of wind turbines i.e. single rotor & multi rotor wind turbine. Power, energy and cost models as proposed are used to determine the annual energy yield and economics of multi-rotor turbines. Simulation results as presented in this paper justify the suitability of multi-rotor wind turbine in place of single rotor configuration. Such turbines deliver more energy yield with low installation cost in contrast to single rotor turbines.

Technique of Standing Up From Prone Position of a Soccer Robot Nur Khamdi; Mochamad Susantok; Antony Darmawan
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

One of the humanoid robots being developed in the field of sports is a soccer robot. A soccer robot is a humanoid robot that can perform activities such as playing football. And a variety method fall down of robot soccer such: falling down toward the front direction, side direction, and rear direction. This paper describes the most stands up methods of a soccer robot from its prone position. The proposed method requires only limited movement with degrees of freedom. The movement standing-up of soccer robot has been implemented on the real robot. Tests we performed showed that reliable standing-up from prone position is possible after a fall and such recovery procedures greatly improve the overall robustness of a Soccer Robot.

Page 28 of 44 | Total Record : 436

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