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Proceeding of the Electrical Engineering Computer Science and Informatics

EECSI
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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 140 Documents

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Search results for , issue "Vol 4: EECSI 2017" : 140 Documents clear

Conceptual Framework for Public Policymaking based on System Dynamics and Big Data Feldiansyah Bin Bakri Nasution; Dr. Nor Erne Nazira Bazin; Dr. Hasanuddin Hasanuddin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Public policy is the critical key of the welfare programs. It is also a powerful instrument to achieve a feasible national competitiveness. Unfortunately, many public policy making processes does not utilize an appropriate data and tool in holistic and systematical approach. This research will focus on creating a comprehensive conceptual framework for public policymaking based on data and system approach. In connection with information technology, there are at least two approaches that will be considered for obtaining a more comprehensive public policy. First is utilization of Big Data to extract information. It is believed that if more accurate data are collected and analyzed, then more comprehensive public policy is created. Utilization of data mining will be intensively used to obtain knowledge. The second approach is the system dynamics. The knowledge created in the first approach is useful in modeling the system. The model will be used to simulate the future possibilities of several scenarios. The scenario with the best outcome is selected as an input for public policymaking. At the end of this research, a conceptual framework for public policy making will be created by incorporating Big Data and system dynamics.

Discovering Process Model from Event Logs by Considering Overlapping Rules Yutika Amelia Effendi; Riyanarto Sarno
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Process Mining is a technique to automatically discover and analyze business processes from event logs. Discovering concurrent activities often uses process mining since there are many of them contained in business processes. Since researchers and practitioners are giving attention to the process discovery (one of process mining techniques), then the best result of the discovered process models is a must. Nowadays, using process execution data in the past, process models with rules underlying decisions in processes can be enriched, called decision mining. Rules defined over process data specify choices between multiple activities. One out of multiple activities is allowed to be executed in existing decision mining methods or it is known as mutually-exclusive rules. Not only mutually-exclusive rules, but also fully deterministic because all factors which influence decisions are recorded. However, because of non-determinism or incomplete information, there are some cases that are overlapping in process model. Moreover, the rules which are generated from existing method are not suitable with the recorded data. In this paper, a discovery technique for process model with data by considering the overlapping rules from event logs is presented. Discovering overlapping rules uses decision tree learning techniques, which fit the recorded data better than the existing method. Process model discovery from event logs is generated using Modified Time-Based Heuristics Miner Algorithm. Last, online book store management process model is presented in High-level BPMN Process Model.

CHMM for Discovering Intentional Process Model From Event Logs by Considering Sequence of Activities Kelly R. Sungkono; Riyanarto Sarno
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

An intentional process model is known to analyze processes deeply and provide recommendations for the upcoming processes. Nevertheless, the discovery of intentions is a difficult task because the intentions are not recorded in the event log, but they encourage the executable activities in the event log. Map Miner is the latest algorithm to depict the intentional process model. A disadvantage of this algorithm is the inability to determine strategies that contain same activities with the different sequence with other strategies. This disadvantage leads failure on the intentional process model. This research proposes an algorithm for discovering an intentional process model by considering the sequence of activities and CHMM (Coupled Hidden Markov Model). The probabilities and states of CHMM are utilized for the formation of the intentional process model. The experiment shows that the proposed algorithm with considering the sequence of activities gets an appropriate intentional process model. It also demonstrates that an obtained intentional process model using proposed algorithm gets the better validity than an intentional process model using Map Miner Method.

Sosio-Technical Factors of E-Government Implementation Darmawan Napitupulu; Dana Indra Sensuse; Yudho Giri Sucahyo
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

The failure of e-Government in a number of sector units happened because the implementation of e-Government is not easy. The old paradigm assume that e-Government is simply by installing a computer makes the implementation of e-Government failure. In fact, the success of e-Government is influenced by various factors called Critical Success Factors (CSFs). This study aims to map CSFs that influenced implementation of e-Government into two term of both technology and non-technology factors. The results showed a 67 CSFs of e-Government implementation identified was successfully mapped into seven dimensions ITPOSMO (Information, Technology, Process, Objective, Staffing & Skill, Management and Other Resource).

Prediction of Rupiah Against US Dollar by Using ARIMA Adiba Qonita; Annas Gading Pertiwi; Triyanna Widiyaningtyas
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

The currency exchanges rate is one of the most important things in the economy. The currency exchange rate is needed in the business word for example, investment and profit assessment. Prediction of rupiah rate is done to get the price of the rupiah against US dollar in the future to be used as consideration in decision-making, thereby reducing the risk of loss. Therefore, we need a method that can help in making business decisions about when to make the right trades with a high degree of accuracy. This study aims to predict the value of rupiah against US dollar by using ARIMA (Autoregressive Integrated Moving Average). This study uses four stages, including (1) the preparation of the dataset, (2) preprocessing of data, (3) the use of ARIMA models, (4) test accuracy. The data used for the test is the data rate from January 4th 2010 until June 24th 2016. The result showed that ARIMA method has an accuracy rate of 98.74%. Based on the result, it can be concluded that the development of the predictive value of the rupiah against the US dollar using ARIMA method was accurate to use.

Forming Heterogeneous Group in Cooperative Learning Process using Partitioning Around Medoids (PAM) and Equitable Distribution Imam Much Ibnu Subrotto; Badieah Badieah; Wardianto Eko Saputra
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Selection of methods will greatly impact in learning process. One of the methods commonly applied are Cooperative learning. Cooperative learning is one of many learning techniques to improve the performance of students in the academic literature. Moreover, the heterogeneity in study group’s academics can improve performance, but only partially implementing cooperative learning in a group of heterogeneous formations. The problem faced in this type is the process of forming group of students into a heterogeneous group and inter-group quality is relatively equal or balanced. In this study, the authors aimed to provide intelligent solutions in the distribution group based on the value (The value of achievement on related subjects) and personality traits of each student in the determination of the performance of students are using the algorithm clustering Partitioning Around Medoids (PAM) in consideration of the value of measurement Euclidean Distance (ED) and the equitable distribution to form heterogeneous groups based on their level of heterogeneity in Measured with Goodness of Heterogeneity in Group (GH) and the rate of coefficient variation (CV) in same group or between groups with groups and equitable distributions on college campuses.

Encoding of Passive Anticollision Radio Frequency Identification Surface Acoustic Waves Tags Alexander Sorokin; Alexander Shepeta; Maurits Wattimena
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This paper describes the encoding of anticollision radio-frequency identification tags based on surface acoustic waves. The study is based on the tag model with specific topology, which allows us to receive a response signal with time–frequency information. This research considers the collision case for several passive tags. Therefore, the proposal is to analyze the possibility of using several distinctive signs like frequency and time. We consider the model of passive surface acoustic wave tag, which contains piezoelectric substrate, interdigital transducer, and consecutive orthogonal-frequency-coded structures, which are placed in time slots. Similar topology makes possible the reliability of increasing tag identification in the collision case.

Compact Fractal Patch Microstrip Antenna Fed by Coplanar Waveguide for Long Term Evolution Communications Indra Surjati; Yuli Kurnia Ningsih; Syah Alam
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This paper proposes a new design of compact fractal patch microstrip antenna fed by coplanar waveguide to reduce the antenna dimension and to increase its bandwidth for Long Term Evolution application purposes. The results shown return loss of -23.45 dB and VSWR 1.144 can be achieved by controlling the height and the width of the fractal patch dimension. Bandwidth of the proposed antenna is 375 MHz which is equal to an increase of 200% compared to the conventional rectangular patch antenna and also the dimension of fractal patch antenna can be reduced until 66%.

Graphical Approach for RF Amplifier Specification in Radio over Fiber System: Maximum Power Issues Teguh Prakoso; Munawar Agus Riyadi; Razali Ngah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Radio-over-fiber (RoF) technologies address wireless communication’s need for high data rate, protocol- transparency, and flexibility. One of challenge in RoF access point design is RF amplifier requirement that match to microwave-photonic link chosen and service range needed. This paper proposes a graphical approach as systematic method to solve the challenge. The method identifies two regions, i.e. (a) scalable region where amplifiers’ output 1-dB compression point (OP1dB) improvement can enhance system’s maximum input and output power, and (b) saturation region where any improvement on amplifiers’ OP1dB cannot improve AP’s maximum input and output power. The methods have been verified by system simulations. The errors at scalable and saturation regions are less than 1 dB and the standard deviation is no more than 0.6 dB. The error values around the breakpoint between scalable and saturation regions are around 1 dB. Therefore, the proposed graphical approach can be used in the specification tradeoff between RoF access point input and output power, amplifier’s gain and OP1dB.

FEM Modeling of Squeeze Film Damping Effect in RF-MEMS Switches Syed Turab Haider; Muhammad Mubasher Saleem; Mashhood Ahmad
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

A very important aspect in the design of RF- MEMS switches, is to obtain low switching time. The switching time not only depends on the device geometric parameters but also on the operating conditions. This paper presents the squeeze film damping effect on the dynamic response of the RF-MEMS switches. The squeeze film damping effect, with and without perforations, on the switching time is analyzed using finite element method (FEM) simulations. The effect of temperature and humidity on the squeeze film damping and switching time is also investigated.

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