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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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Automatic Samples Selection Using Histogram of Oriented Gradients (HOG) Feature Distance Inzar Salfikar; Indra Adji Sulistijono; Achmad Basuki
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v5i2.182

Finding victims at a disaster site is the primary goal of Search-and-Rescue (SAR) operations. Many technologies created from research for searching disaster victims through aerial imaging. but, most of them are difficult to detect victims at tsunami disaster sites with victims and backgrounds which are look similar. This research collects post-tsunami aerial imaging data from the internet to builds dataset and model for detecting tsunami disaster victims. Datasets are built based on distance differences from features every sample using Histogram-of-Oriented-Gradient (HOG) method. We use the longest distance to collect samples from photo to generate victim and non-victim samples. We claim steps to collect samples by measuring HOG feature distance from all samples. the longest distance between samples will take as a candidate to build the dataset, then classify victim (positives) and non-victim (negatives) samples manually. The dataset of tsunami disaster victims was re-analyzed using cross-validation Leave-One-Out (LOO) with Support-Vector-Machine (SVM) method. The experimental results show the performance of two test photos with 61.70% precision, 77.60% accuracy, 74.36% recall and f-measure 67.44% to distinguish victim (positives) and non-victim (negatives).

Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network Gezaq Abror; Rusminto Tjatur Widodo; M. Udin Harun Al Rasyid
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Wireless Sensor Network (WSN) can be applied for Air Pollution Level Monitoring System that have been determined by the Environmental Impact Management Agency which isÂ PM10, SO2, O3, NO2 and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (Time-Fuzzy) Scheduling as a reference for calculating time interval for sleep and activated node system to support power management scheme. This research contributed in power management design to be applied to the WSN system to reduce energy expenditure. From the test result in real hardware node system, it can be seen that Time-Fuzzy Scheduling is better in terms of using the battery and it is better in terms of energy consumption too because it is more efficient 51.85% when it is compared with Fuzzy Scheduling, it is more efficient 68.81% when it is compared with Standard Scheduling and it is more efficient 85.03% when compared with No Scheduling.

A Time-Series Phrase Correlation Computing System With Acoustic Signal Processing For Music Media Creation Keiichi Tsuneyama; Yasushi Kiyoki
EMITTER International Journal of Engineering Technology Vol 5 No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

This paper presents a system that analyzes the time-series impression change in the acoustic signal by a unit of music phrase. The aim is to support the music creation using a computer (computer music) by bringing out composers' potentially existing knowledge and skills. Our goal is to realize the cross-genre/cross-cultural music creation. Our system realizes the automatic extraction of musical features from acoustic signals by dividing and decomposing them into â€œphrasesâ€ and â€œthree musical elementsâ€ (rhythm, melody, and harmony), which are meaningful for human recognition. By calculating the correlation between the target â€œtarget music pieceâ€ and the â€œtypical phraseâ€ in each musical genre, composers are able to grasp the time-series impression change of music media by the unit of music phrase. The system leads to a new creative and efficient environment for cross-genre/cross-cultural music creation based on the potentially existing knowledge on the music phrase and structure.

A Similarity-Ranking Method on Semantic Computing for Providing Information-Services in Station-Concierge System Motoki Yokoyama; Yasushi Kiyoki; Tetsuya Mita
EMITTER International Journal of Engineering Technology Vol 5 No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

The prevalence of smartphones and wireless broadband networks have been progressing as a new Railway infomration environment.ã€€According to the spread of such devices and information technology, various types of information can be obtained from databases connected to the Internet. One scenario of obtaining such a wide variety of information resources is in the phase of userâ€™s transportation. This paper proposes an information provision system, named the Station Concierge System that matches the situation and intention of passengers. The purpose of this system is to estimate the needs of passengers like station staff or hotel concierge and to provide information resources that satisfy userâ€™s expectations dynamically. The most important module of the system is constructed based on a new information ranking method for passenger intention prediction and service recommendation. This method has three main features, which are (1) projecting a user to semantic vector space by using her current context, (2) predicting the intention of a user based on selecting a semantic vector subspace, and (3) ranking the services by a descending order of relevant scores to the userâ€™ intention. By comparing the predicted results of our method with those of two straightforward computation methods, the experimental studies show the effectiveness and efficiency of the proposed method. Using this system, users can obtain transit information and service map that dynamically matches their context.

Data Mining Approach for Breast Cancer Patient Recovery Tresna Maulana Fahrudin; Iwan Syarif; Ali Ridho Barakbah
EMITTER International Journal of Engineering Technology Vol 5 No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Breast cancer is the second highest cancer type which attacked Indonesian women. There are several factors known related to encourage an increased risk of breast cancer, but especially in Indonesia that factors often depends on the treatment routinely. This research examines the determinant factors of breast cancer and measures the breast cancer patient data to build the useful classification model using data mining approach.The dataset was originally taken from one of Oncology Hospital in East Java, Indonesia, which consists of 1097 samples, 21 attributes and 2 classes. We used three different feature selection algorithms which are Information Gain, Fisherâ€™s Discriminant Ratio and Chi-square to select the best attributes that have great contribution to the data. We applied Hierarchical K-means Clustering to remove attributes which have lowest contribution. Our experiment showed that only 14 of 21 original attributes have the highest contribution factor of the breast cancer data. The clustering algorithmdecreased the error ratio from 44.48% (using 21 original attributes) to 18.32% (using 14 most important attributes).We also applied the classification algorithm to build the classification model and measure the precision of breast cancer patient data. The comparison of classification algorithms between NaÃ¯ve Bayes and Decision Tree were both given precision reach 92.76% and 92.99% respectively by leave-one-out cross validation. The information based on our data research, the breast cancer patient in Indonesia especially in East Java must be improved by the treatment routinely in the hospital to get early recover of breast cancer which it is related with adherence of patient.

Application of Sliding Mode Control in Indirect Field Oriented Control (IFOC) for Model Based Controller Angga Wahyu Aaditya; Dedid Cahya Happyanto; Bambang Sumantri
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Indirect Field Oriented Control (IFOC) is one of the vector control methods that can be applied to induction motor in the industrial world rather than Direct Field Oriented Control (DFOC) because of the flux is obtained from the formulation. However, IFOC can not guarantee the robustness and stability of the systems. Stability analysis such as Lyapunov Stability Theory can be used to make the system stable but not the robustness. Model based controller that can guarantee the stability and robustness such as sliding mode control (SMC) and fuzzy needs to be added in IFOC system to achieve proportional response system. Robust current regulator using sliding mode control was designed in this paper from state space model for model based controller. In transient response and under disturbance SMC shows better performance than PID in rising time and robustness at rotor speed and stator current.

Capacitive Energy Storage (CES) Optimization For Load Frequency Control in Micro Hydro Power Plant Using Imperialist Competitive Algorithm (ICA) Muhammad Ruswandi Djalal; Muhammad Yunus; Andi Imran; Herlambang Setiadi
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

This research will discuss a strategy of frequency control at micro hydro power plant using Capacitive Energy Storage (CES). CES is a device that can store and release energy quickly. To optimize CES performance, proper tuning is required to optimize CES performance. To obtain optimal CES parameter on micro hydro, artificial intelligence method based on Imperialist Competitive Algorithm (ICA) is used. Proportional Integral Derivative Controller (PID) is still a controller that can not be separated from the system, therefore in this research will be combined with CES as the main controller for frequency control on micro hydro. The simulation results show that the application of ICA in optimizing PID-CES parameters, can well improve micro hydro performance. The control models discussed in this research are Proportional Controller (P), Proportional Integral Controller (PI), Proportional Derivative Controller (PD), PID Controller, CES Controller and PID-CES Controller. From the simulation results obtained, P controller overshoot of -0.0001254, with PI Controller -0.000125, with PD Controller -0.0001252, with PID controller -0.0001249, with CES controller -0.0001224, and with PID-CES -1.371e-05. From the results of some of the controller models, it can be concluded that the PID-CES controller proposed in this study has a very significant effect to reduce the frequency oscillation in micro hydro, and it is very suitable to be applied for frequency control at micro hydro.

Feature Extraction For Application of Heart Abnormalities Detection Through Iris Based on Mobile Devices Entin Martiana Kusumaningtyas; Ali Ridho Barakbah; Aditya Afgan Hermawan
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

As the WHO says, heart disease is the leading cause of death and examining it by current methods in hospitals is not cheap. Iridology is one of the most popular alternative ways to detect the condition of organs. Iridology is the science that enables a health practitioner or non-expert to study signs in the iris that are capable of showing abnormalities in the body, including basic genetics, toxin deposition, circulation of dams, and other weaknesses. Research on computer iridology has been done before. One is about the computer's iridology system to detect heart conditions. There are several stages such as capture eye base on target, pre-processing, cropping, segmentation, feature extraction and classification using Thresholding algorithms. In this study, feature extraction process performed using binarization method by transforming the image into black and white. In this process we compare the two approaches of binarization method, binarization based on grayscale images and binarization based on proximity. The system we proposed was tested at Mugi Barokah Clinic Surabaya.Â We conclude that the image grayscale approach performs better classification than using proximity.

Botnet Detection Using On-line Clustering with Pursuit Reinforcement Competitive Learning (PRCL) Yesta Medya Mahardhika; Amang Sudarsono; Ali Ridho Barakbah
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Botnet is a malicious software that often occurs at this time, and can perform malicious activities, such as DDoS, spamming, phishing, keylogging, clickfraud, steal personal information and important data. Botnets can replicate themselves without user consent. Several systems of botnet detection has been done by using classification methods. Classification methods have high precision, but it needs more effort to determine appropiate classification model. In this paper, we propose reinforcedÂ approach to detect botnet with On-line Clustering using Reinforcement Learning. Reinforcement Learning involving interaction with the environment and became new paradigm in machine learning. The reinforcement learning will be implemented with some rule detection, because botnet ISCX dataset is categorized as unbalanced dataset which have high range of each number of class. Therefore we implemented Reinforcement Learning to Detect Botnet using Pursuit Reinforcement Competitive Learning (PRCL) with additional rule detection which has reward and punisment rules to achieve the solution. Based on the experimental result, PRCL can detect botnet in real time with highÂ accuracy (100% for Neris, 99.9% for Rbot, 78% for SMTP_Spam, 80.9% for Nsis, 80.7% for Virut, and 96.0% for Zeus) and fast processing time up to 176 ms. Meanwhile the step of CPU and memory usage which are 78 % and 4.3 GBÂ for pre-processing, 34% and 3.18 GB for online clustering with PRCL, and Â 23% and 3.11 GB evaluation. The proposed method is one solution for network administrators to detect botnet which has unpredictable behavior in network traffic.

Automatic Abstractive Summarization Task for New Article Afrida Helen
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Understanding the contents of numerous documents requires strenuous effort. While manually reading the summary or abstract is one way, automatic summarization offers more efficient way in doing so. The current research in automatic summarization focuses on the statistical method and the Natural Processing Language (NLP) method. Statistical method produce Extractive summary that the summaries consist of independent sentences considered important content of document. Unfortunately, the coherence of the summary is poor. Besides that, the Natural Processing Language expected can produces summary where sentences in summary should not be taken from sentences in the document, but come from the person making the summary. So, the summaries closed to human-summary, coherent and well structured. This study discusses the tasks of generating summary. The conclusion is we can find that there are still opportunities to develop better outcomes that are better coherence and better accuracy.

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