Indonesian Journal of Electrical Engineering and Informatics 

About: Indonesian Journal of Electrical Engineering and Informatics is an academic journal published by Institute of Advanced Engineering and Science (IAES). The journal publishes majorly in the area(s): Computer science & Electric power system. It has an ISSN identifier of 2089-3272. It is also open access. Over the lifetime, 504 publications have been published receiving 2146 citations.

Big Data-Survey

Abstract: Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.

Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System

Abstract: Nowadays, there is a growing interest in the smart home system using Internet of Things. One of the important aspect in the smart home system is the security capability which can simply lock and unlock the door or the gate. In this paper, we proposed a face recognition security system using Raspberry Pi which can be connected to the smart home system. Eigenface was used the feature extraction, while Principal Component Analysis (PCA) was used as the classifier. The output of face recognition algorithm is then connected to the relay circuit, in which it will lock or unlock the magnetic lock placed at the door. Results showed the effectiveness of our proposed system, in which we obtain around 90% face recognition accuracy. We also proposed a hierarchical image processing approach to reduce the training or testing time while improving the recognition accuracy.

E-Learning Success Model: An Extention of DeLone & McLean IS' Success Model

Abstract: Learning by using e-learning system at this time become an important part of university to carrying out the education Learning by e-learning system is very supportive to conventional learning, so it is necessary to measure the success of e-learning implementation In this article, the research model was developed by integrating DeLone& McLean IS concept of success model and adoption model of e-learning success The variables that used in this research is technical system quality, service quality, content and information quality, use, user perceived satisfaction, and individual impact Data collection is by conducting surveys to e-learning users which is lecturers and students To test the model that has been developed, conducted a survey on UPN "Veteran" Jakarta with the total number of respondents as many as 180 respondents and obtained 157 respondents who fill the questionnaire correctly This research, shows both the use and satisfaction of e-learning system have an impact for individual performance This research also found that educational system quality and technical quality are the main factors that encourage user satisfaction with e-learning system, while the use of e-learning system that influenced by content & information quality, also user perceived satisfaction for e-learning system

Phishing or Hijacking? Forgers Hijacked DU Journal by Copying Content of Another Authenticate Journal

Abstract: 2 Hijacked journals are journals that are created by forgers and use same name and ISSN similar authenticate journals. These journals publish papers of authors by requesting publication charges without any peer review because they have financial goals. In many cases, forger select journals that have print version and create the fake website then cheat authors (1- 3). We found a new hijacked journal that name "DU Journal." Original DU journal is Thomson Reuters indexed and has Arts & Humanities Citation Index. This journal is established by DU Verlag, Steinackerstrasse in Switzerland. Journal's ISSN is monthly ISSN: 0012-6837 and available at this URL: http://www.du-magazin.com. Fake journal is placed in this URL http://dujournal.eu.pn. DU journal is Scopus indexed, and we cannot find papers of evaluated URL (http://dujournal.eu.pn) in Scopus database. Also in Thomson Reuter's website we cannot find any link to website. By using a Whois databases, we detect that fake website is created in Jul 2007 by a hosting company and use ns1.freehostingeu.com as a name server, it means that website use free hosting service. Often Phisher and forgers use free hosting to be anonymous. Domain of the fake journal is a free domain too. In other words, forgers used free domain and hosting for fake journal. We can find similar hijacking technique for another hijacked journal that name "Ephemera Journal." Ephemera Journal is placed in this server and uses free hosting and domain such as DU journal. It is high probability that a person is a forger of these two journals. In fake DU journal, two volumes are accessible, and some issues only have one paper. It seems that forgers are creating a website or are searching for victims to publish their papers in these volumes. In contact section of the website, there are three email addresses; du.editor@swissmail.com, du.customer@swissmail.com and info@dujournal.eu.pn. Forgers used swissmail.com server as official email addresses to convince authors that journal is belonged to Switzerland, and journal is authenticated while swissmail.com server, is free email service such as Google, Yahoo and other free email services, that is created by mail.com and any people can create email account in it. In main page of the fake website, there is an image from a certificate, we searched this image and other images of this site in Google and found that these images are belonged to journal of Siberian federal university (http://journal.sfu-kras.ru/en). Hijackers used Siberian federal university Journal' website content and created faked DU journal. This type of hijacking is very similar to deceptive phishing attacks. In information security literature, phishing is a social engineering based attack where the attacker tries to steal victims' sensitive information by means of different techniques (4, 5). In deceptive phishing attacks, phisher use content of other websites and create the fake website then redirect victims to the fake website by using of social engineering techniques.

Facial Expression Recognition Using SVM Classifier

Abstract: Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field Computational facial expression analysis is a challenging research topic in computer vision It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels First, in the bottom level, facial feature tracking, which usually detects and tracks prominent landmarks surrounding facial components (ie, mouth, eyebrow, etc), captures the detailed face shape information; Second, facial actions recognition, ie, recognize facial action units (AUs) defined in FACS, try to recognize some meaningful facial activities (ie, lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize some meaningful facial activities (ie, lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize facial expressions that represent the human emotion states In this proposed algorithm initially detecting eye and mouth, features of eye and mouth are extracted using Gabor filter, (Local Binary Pattern) LBP and PCA is used to reduce the dimensions of the features Finally SVM is used to classification of expression and facial action units