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Proceeding of the Electrical Engineering Computer Science and Informatics

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Published by Institute of Advanced Engineering and Science

ISSN : 2407439X EISSN : - DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, students, engineers and practitioners together to participate and present their latest research finding, developments and applications related to the various aspects of electrical, electronics, power electronics, instrumentation, control, computer & telecommunication engineering, signal processing, soft computing, computer science and informatics.

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Articles 649 Documents

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Indoor Agriculture: Measurement of The Intensity of LED for Optimum Photosynthetic Recovery Benediktus Anindito; Adri Gabriel Sooai; Mochammad Mizanul Achlaq; Moh Noor Al-Azam; Aris Winaya; Maftuchah Maftuchah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Indoor agriculture has begun in urban areas. With the narrowness of land and the model of vertical house development, makes this method of indoor agriculture has become a trend in several big cities in the world. Meanwhile, the one that is always needed by every plant is photosynthesis, and every natural photosynthesis of plants continually requires abiotic components of visible light from sunlight. That's why the indoor agriculture requires a replacement source of the sun with artificial sunlight. We can make this artificial sunlight from several light sources, such as incandescent lamps, compact fluorescent lamps (CFL), or the latest with Light Emitting Diode (LED). In this paper, we measured the intensity of light generated from several LEDs with some radiation distance to obtain the optimal energy for plants photosynthesis.

Measurement of Thermal Expansion Coefficient on Electric Cable Using X-Ray Digital Microradiography Yessi Affriyenni; Gede Bayu Suparta; Galandaru Swalaganata
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Electric cable is a medium to conduct electrical energy. Expansion and contraction caused by thermal changes may result in an aging effect on the cable. This paper presents the way to observe the expansion in electrical cable due to thermal changes using the x-ray microradiography. The observed electric cables were NYA, NYAF, and NYM, each with cross-sectional areas of 1.5 mm 2 and 2.5 mm 2 . The temperature was monitored using a DS18B20 sensor compiled into a microcontroller. In order to process and analyze the cables images, an ImageJ software was used. The image differences were compared based on the value of the digital image correlation. The physical analysis was carried out based on Adrian's FWHM and calculated using the regression method. The accurate structural dimension measurement using x-ray digital microradiography is about 50 μm/pixel. The average relative error measured was less than 3%.

Individual Factors As Antecedents of Mobile Payment Usage Radinal Setyadinsa; Muhammad Rifki Shihab; Yudho Sucahyo
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

The aim of this research was to discover the stances of individual elements as antecedents of mobile payment usage. Data was gathered by distributing a questionnaire, which in latter steps was analyzed quantitatively. This research collected 90 samples, of whom represented users of a mobile payment service in Indonesia. The collected dataset was statistically analyzed, by employing partial least square structural equational modelling (PLS-SEM), aided with SmartPLS3.0. The results showed that two types of individual factors, namely individual difference and behavioral belief played significant roles in shaping users' intention to use mobile payments. Individual differences, consisting of mobile payment knowledge and compatibility significantly influenced perceived ease of use. Behavioral belief, such as trust, was shown to significantly influenced perceived usefulness. Finally, perceived ease of use and perceived usefulness concertedly affected mobile payment users' intention to use.

Web-based Campus Virtual Tour Application using ORB Image Stitching Triyanna Widiyaningtyas; Didik Dwi Prasetya; Aji P Wibawa
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Information disclosure in the digital age has demanded the public to obtain information easily and meaningful. In this paper, we propose the development of web-based campus virtual tour 360-degree information system application at the State University of Malang, Indonesia which aims to introduce the assets of the institution in an interesting view to public. This application receives a stitched or panoramic image generated through the ORB image stitching algorithm as an input and displays it in virtual tour manner. This paper realizes the image stitching algorithm to present the visualization of the 360-degree dynamic building and campus environment, so it looks real as if it were in the actual location. Virtual tour approach can produce a more immersive and attractive appearance than regular photos.

Application for the diagnosis of pneumonia based on Pneumonia Severity Index (PSI) values Elyza Wahyuni; Ahmad Ramadhan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

There has been considerable research that addresses the diagnosis of pneumonia based on symptoms experienced by the patient, some using artificial intelligent methods such as monoton and non monoton methods with mixed results, based on previous studies to develop and improve previous research deficiencies because they refer to the results is expected to be useful by experts, especially lung specialists in Indonesia, The reference used by Indonesian pulmonary specialist is the value of Pneumonia Severity Index (PSI) which is used to classify Pneumonia level, then the expected results are qualitative and unambiguous outputs therefore fuzzy logic Sugeno method is very suitable to overcome the problem. Fuzzy logic Sugeno has been successfully applied in pneumonia disease and matched with the Pneumonia Severity Index Score in the amount of 75% based on 4 data has been tested.

A Relative Rotation between Two Overlapping UAV's Images Martinus Edwin Tjahjadi; Fransisca Agust
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

In this paper, we study the influence of varying baseline components on the accuracy of a relative rotation between two overlapping aerial images taken form UAV flight. The case is relevant when mosaicking UAV's aerial images by registering each individual image. Geotagged images facilitated by a navigational grade GPS receiver on board inform the camera position when taking pictures. However, these low accuracies of geographical coordinates encoded in an EXIF format are unreliable to depict baseline vector components between subsequent overlapping images. This research investigates these influences on the stability of rotation elements when the vector components are entered into a standard coplanarity condition equation to determine the relative rotation of the stereo images. Assuming a nadir looking camera on board while the UAV platform is flying at a constant height, the resulted vector directions are utilized to constraint the coplanarity equation. A detailed analysis of each variation is given. Our experiments based on real datasets confirm that the relative rotation between two successive overlapping image is practically unaffected by the accuracy of positioning method. Furthermore, the coplanarity constraint is invariant with respect to a translation along the baseline of the aerial stereo images.

Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique Quota Alief Sias; Irham Fadlika; Irawan Dwi Wahyono; Arif Nur Afandi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Z-Source Inverter (ZSI) is famous power converter who has capability to deal with voltage sags, improved power factor and wide voltage range of output. Quasi Z Source Inverter (QZSI) is the modern ZSI who has continuous current of input and can reduce stress of the passive component. This paper proposes simple boost QZSI circuit as Maximum Power Point Tracking (MPPT) using Grey Wolf Optimization (GWO) algorithm in photovoltaic system. Grey Wolf algorithm has been compared with the Perturb and Observed (P&O) technique for gaining the maximum power from the sun. Both techniques can get the optimum power of solar panel not only at constant sun light condition but also under varying irradiance levels. The value of average power obtained from GWO technique is greater than P&O. Although the value of solar radiation changes, the output voltage remains stable and both algorithms carry on obtaining optimal power of the sun.

Re-Ranking Image Retrieval on Multi Texton Co-Occurrence Descriptor Using K-Nearest Neighbor Yufis Azhar; Agus Eko Minarno; Yuda Munarko
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Some features commonly used to conduct image retrieval are color, texture and edge. Multi Texton Co-Occurrence Descriptor (MTCD) is a method which uses all three features to perform image retrieval. This method has a high precision when doing retrieval on a patterned image such as Batik images. However, for images focusing on object detection like corel images, its precision decreases. This study proposes the use of KNN method to improve the precision of MTCD method by re-ranking the retrieval results from MTCD. The results show that the method is able to increase the precision by 0.8% for Batik images and 9% for corel images.

Automatic User-Video Metrics Creations From Emotion Detection Darari Nur Amali; Adnan Rachmat Anom Besari; Ali Ridho Barakbah; Dias Agata
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

In this digital era, digital content especially video, is increasing in number from time to time. Typically, a video service provider like Youtube will perform video analysis based on the video content such as colours, textures, shapes, and other features that exist in video content. The result of this analysis was used to understand user preference and to personalize video for each user. With technological developments, especially in Machine Learning and Computer Vision technology, video analysis can be based on other things beyond the video. In this context, it is the audience's impression. Thus, with the analysis of audience impressions in real-time, it is expected that the video can be analysed using the emotion parameters of the audience while the video is playing, and this can be done automatically and real-time. This system generates impression statistic for each video which concluded from every user who has watched the video and save those data in the database. Method used to analyse the result is by recruiting respondent and give some questionnaires. Respondents were asked to watch some videos and were asked to compare the impression metric which created by the system with user's real impression. The result shos that the automatic video-metric creation from emotion detection has been able to measure user's impression of the video with more than 80% accuracy stated by 75% of 20 respondents of the survey.

Impact of Matrix Factorization and Regularization Hyperparameter on a Recommender System for Movies Gess Fathan; Teguh Bharata Adji; Ridi Ferdiana
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Recommendation system is developed to match consumers with product to meet their variety of special needs and tastes in order to enhance user satisfaction and loyalty. The popularity of personalized recommendation system has been increased in recent years and applied in several areas include movies, songs, books, news, friend recommendations on social media, travel products, and other products in general. Collaborative Filtering methods are widely used in recommendation systems. The collaborative filtering method is divided into neighborhood-based and model-based. In this study, we are implementing matrix factorization which is part of model-based that learns latent factor for each user and item and uses them to make rating predictions. The method will be trained using stochastic gradient descent with additional tricks and optimization of regularization hyperparameter. In the end, neighborhood-based collaborative filtering and matrix factorization with different values of regularization hyperparameter will be compared. Our result shows that matrix factorization method with lowest regularization hyperparameter outperformed the other methods in term of RMSE score. In this study, the used functions are available from Graphlab and using Movielens 100k data set for building the recommendation systems.

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