FOREWORD - portal.kopertis3.or.idportal.kopertis3.or.id/bitstream/123456789/1345/1/VISUALIZATION...International Conference on Telecommunication 2009 WELCOMING SPEECH ICTel2009 is

International Conference on Telecommunication 2009

FOREWORD ICTEL 2009

International Conference on Telecommunication (ICTel) is an annual event hosted by IT Telkom since the year of 2005. Thus today ICTel is its fifth, highlighting on the theme of “ICT Development for the Knowledge Based Society”. This theme is chosen as a response from our institution in seeing the current trend where ICT already enters various areas of human life. Those areas include education, health, banking and finance, mining, national defense, and many others. Most of business activities in those areas have been using ICT as their main assisting device. Therefore we can conveniently say that ‘ICT for life’ has become ‘a jargon comes to life’, in which lots of ICT applications are everyday phenomena.

Responding to that existing trend, ITTelkom as one educational institution is taking on active participation to link communication among people and communities in ICT development. The vast development in ICT has given more and more rooms to ideas and creative minds. This is exactly where ICTel is expected to facilitate communications and information exchanges, allowing faster and more integrated expansion of ICT knowledge. All ICTel participants coming from diverse background: academics, research and development, industry, and engineering are given widest opportunity to openly discuss the best solution for ICT for the society growing on pillars of knowledge.

Last but not least, since ICT development is not something to be built overnight, and that it needs continuous and sustainable communication, we hope that the discussions taken place in this event can be followed by real efforts to improve the quality of life of society. To all the participants, writers, committees, and all the contributing parties, we extend our sincere gratitude and appreciation. We hope that ICTel 2009 can give meaningful contribution to ICT development for society.

Yours, Director of Academic Support Suwandi

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WELCOMING SPEECH

ICTel2009 is an annual international conference especially for researchers and academicians in the field of telecommunication to share and publish their works. ICTel2009 consists of plenary session featuring various presenters to expose their research and read condition of telecommunication world. The theme “ICT Development for the Knowledge Based Society” is chosen because, as a matter of fact, the role of ICT nowadays it expected to be more evolved for the development of sophisticated and advanced society. Moreover, ICT will also enable this society to have better information access to close the economical and social gap. Thus, eventually prosperity shall be achieved by their society. Mainly, the plenary session of ICTel2009 consists of presentations covering the topic of telecommunication industry, optic, radar, computer, communication system, artificial intelligence, and many others. There are 78 abstracts and papers sent to the committee and only 53 papers are accepted and to be presented. These include 4 international presenters, 16 national presenters, and 33 presenters from the IT Telkom. Participants and presenters of ICTel 2009 come from German, Malaysia, Korea, and Indonesia. Good luck to all people involved in ICTel 2009. I hope that all of you will enjoy and gain invaluable benefits from all agenda of ICTel 2009. Bandung, November 2009 Chair of Organizing Committee Iswahyudi Hidayat

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ICTel 2009 COMMITTEE

ORGANIZER

Directorate of Academic Support, Institut Teknologi Telkom Bandung

TECHNICAL PROGRAM COMMITTEE

Josaphat Tetuko Sri Sumantyo (Chiba University) Joel Joseph Sacro Marciano (IEEE Phillipine Section Chair)

Toni Anwar (TGGS, Thailand) Marzuki Khalid (University Technology of Malaysia)

Heiko Schroder (Royal Melbourne Institute of Technology) Andrian Bayu Suksmono (Institut Teknologi Bandung)

Sugihartono (Institut Teknologi Bandung) Suhartono Tjondronegoro (Institut Teknologi Bandung)

Aly Muayyadi (Institut Teknologi Telkom) Deni Saepudin (Institut Teknologi Telkom) Rendy Munadi (Institut Teknologi Telkom) Rina Puji Astuti (Institut Teknologi Telkom) Ary M. Barmawi (Institut Teknologi Telkom) Heroe Wijanto (Institut Teknologi Telkom) Dharu Arseno (Institut Teknologi Telkom) Iwan Iwut TA (Institut Teknologi Telkom)

ORGANIZING COMMITTEE

Iswahyudi Hidayat Yuliant Sibaroni

Erwin Budi Setiawan Kinkin Kindawati

Leanna Vidya Yovita Shaufiah Adiwijaya

Iman Hedi Santoso Indra Chandra Deny Saepudin

Koredianto Usman Rian Febrian Umbara Florita Diana Sari

Istikmal Hetti Hidayati Heri Iman N.

Mediana Mayang Kencana Ani Yuliani Warsino

Aris Hartaman Yanuar Firdaus AW

Chandra Purna Darmawan

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International Conferece on Telecommunication 2009

LIST OF PARTICIPANT PAPERS A. Social and Technical aspect of Computer Network

Performance Comparison Of Scheduling Algorithm: Round Robin (RR), Weighted Round Robin

(WRR) and Deficit Round Robin (DRR) on WIMAX Network With NS-2 Simulator ................................... 1

Analysis Performance Congestion Control Algorithm on Mobile Adhoc Network (MANET) .................... 11

Performance Evaluation of Multi-Radio AOVD in Hybrid Wireless Mesh Networks Based on

Manhattan Mobility Model ............................................................................................................................ 20

Analysis of Delay Bound in IEEE 802.11g WLAN Over Fiber Networks .................................................... 27

Mobile Banking: Safe, at Least for Now ....................................................................................................... 31

Design and Implementation of SMS Gateway as a Learning Support Tool .................................................. 35

Eastern Cyberlaw Exposed : The Port Scanning Way ................................................................................... 39

Optimize QOS of Metro Ethernet Network with Packet Scheduller Using Weight Round Roubin

Algorithm (WRR) .......................................................................................................................................... 45

Performance Analysis of H.264/AVC Video Streaming Over Wireless LAN with IEEE 802.11e

Enhanced Distributed Channel Access QOS Support ................................................................................... 49

Content Provider Server for Wireless Mobile Device ................................................................................... 56

Improved Flooding Protocol with Gravity Analogy in Wireless Sensor Network ........................................ 62

An Application to Support TDM-to-Softswitch-Based NGN Migration on OPNET IT Guru®

Network Planner ............................................................................................................................................ 69

A Comparison Between FUSC and PUSC Sub-channelization Techniques for Downlink Mobile

WiMAX IEEE 802.16e Performance ............................................................................................................ 73

Analysis Performance of Bandwidth Request-Grant Mechanisms in WiMAX Networks ............................ 80

Design on Information Technology Strategic Planning Framework by Activity Values Identification ........ 86

B. Computer Sience and Intelligent System Particle Swarm Optimization Algorithm to Optimize Project Resource Scheduling .................................. 100

Visualization Comparison Self Organizing Mapping (SOM) Analysis to Linearity Correlation Based

on Region Power Transmission Path in JMB .............................................................................................. 105

Reconstruction of Phylogenetic Tree Using Ant Colony Optimization ....................................................... 110

Corporate Information Factory Planning in Telecommunication Operator ................................................. 115

Design and Implementation of Communication Between Virtual World and Real World Based on

Croquet in 3D Virtual World ....................................................................................................................... 119

Performance Test of Statistical Translation Machine at Translating English to Indonesian Language ....... 126

Development of Social Security Card Case on Monitoring Malnutrition Patients in NTT Area ................. 130

Analysis of Indonesian News Document Classification Using Centroid Based Classifier Method ............ 133

Similarity Measurement in Digital Music File Base on Chroma-Based Representation ............................. 138

Design and Software Implementation for Wireless Automation in PLC Based Using Java Platform ......... 143

Caricari Game Design and Implementation as a Web Based Mini Game ................................................... 152

Hardware Description Language Comparison Systemc to Verilog Case Study: Least Common

Multiple ....................................................................................................................................................... 155

C. Communication System, Optics, Radar, and Applied Physics Hanle Eeffect Modeling on Silicon Based Spintronic Semiconductor Devices .......................................... 160

PON Extender: Controlling System for GPON with optional EDFA .......................................................... 164

Bidirectional Optical Add/Drop Multiplexer (OADM) For CWDM PON System ..................................... 166

Building a Radar From The Scratch: ISRA LIPI Radar Experience ........................................................... 171

Simulation Of Sequentila Fast ADC For Ground Penetrating Radar (GPR) Applications .......................... 181

Performance Analysis of MIMO-STBC System in HSDPA Over Fading Rayleigh Channel ..................... 186

The Performance Analysis of Combined Mud Decorrelator and PIC in DS-CDMA .................................. 194

Design of Yagi Antenna on Wireless Local Area Network 2,4 GHz .......................................................... 199

Analyzing Influence of Earth Station Antenna Pointing to Receiving Signal Parameter at Down Link

Power Budget .............................................................................................................................................. 203

Cooperative Signal Detection With Different Channel Fading ................................................................... 209

Design of Dispersion Shifted Fiber (DSF) to Increase The Performance of Optical Fiber

Communication System ............................................................................................................................... 214

Design and Realization Pulse Generator for Ground Penetrating Radar Application Using Timing

Switched Method ......................................................................................................................................... 221

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International Conferece on Telecommunication 2009

D. Data Mining, Applied Mathematics, Image Processing and ICT Contens of Gold and Silver Estimation Using Ordinary Kriging Method (Case Study : PT Aneka

Tambang) ..................................................................................................................................................... 227

Scheduling Replacement of Hydraulic Pump Component Software Using Weibull Distribution (Case

Study : PT Inco, Tbk) .................................................................................................................................. 233

Space-Time Analysis of Product−Sum Semivariogram Model (Case Study : Oil Product) ........................ 238

Churn Prediction of Cellular Telecommunication Customer with Cost-Sensitive Learning Approach ...... 247

The Analysis and Application of Classification Methods for Software Development Non-Tulis

University Student Enrollment System (Case Study at IT Telkom) ............................................................ 252

3D Reconstruction Extraction and Equation of Calibration Parameters Using Simple Sckewed

Chessboard Pattern on Stereo Vision........................................................................................................... 258

Training Set with Enhancement TSVQ Method for Medical Image Based Super-Resolution .................... 264

Building an Indonesian Digital Forensic Laboratory ................................................................................... 268

The Effects of VAK Learning Style on Learning Outcomes in Powerpoint-Based Teaching ..................... 274

Cybercrime from Islamic Shariah Law Point of View ................................................................................ 281

Implementation of Particle System Using Smoothed Particle Hydrodynamics (SPH) for Simulating

Lava Flow .................................................................................................................................................... 284

Analysis and Design of E-procurement PT. Adhi Jaya ............................................................................... 290

Analysis of Propagation Channel Using Walfisch-Ikegami Model On Mobile Wimax System ................. 296

Performance Analysis Of Zigbee Protocol On Wireless Personal Area Network (WPAN) ........................ 304


VISUALIZATION COMPARISON SELF ORGANIZING MAPPING (SOM) ANALYSIS TO LINEARITY CORRELATION BASED ON REGION POWER

TRANSMISSION PATH IN JMB

Iriansyah BM Sangadji 1, Subanar 2 , Retantyo Wardoyo 3, Sri Hartati 4

1 Informatics, STT PLN 2,3,4, Natural Science and Mathematics Faculty, Gadjah Mada University

[email protected] , [email protected], [email protected]

Abstract Electricity transmission path function is connecting numbers of power plant in the large covering area. Its mean the system needs handling when the power plant must active or not. Decision is taking by consider analytic behavior and relation between power plant in each region. Knowledge about relation pattern and behavior of power need are important. Neural network (SOM) and scatterplot methods can use in this paper. Comparison of form graph between scatter plot and SOM visualization mean will be investigated. Results of this paper will showing and explain behavior relationships pattern between region 1 to region 4. Comparison method between 2 approaches will showed.

Keywords: Self Organizing Map(SOM), Linear Correlation , Region, JMB electricity transmission path. 1. Introduction

In operation electricity power handling system

that the power plants , transmission path is

connected in a big electricity complex system. The

area of this system covering increase will correlate

with integrated new numbers kind of power plants.

Roles of addition or develop its system have

feedback in positive or negative values to system.

To constitute a new power plants have to

consider much aspects from the handling system

itself to social and environment impacts. Now the

question is how to make interactive between power

plants unit in harmony of transmission balancing

system. Balancing system has a few conditions. One

condition is have to know behavioral active power

from power plant and consumption in customer .

JMB (Jawa, Madura Bali) electricity

transmission system is the one of complex network

handling system. Its constitute from four convergent

regions division power. Operating power JMB

system have to based on region1 to region 4.

Figure 1. JMB electricity Transmission System

Modeling and mapping behavioral power per

region areas will explain behavioral of dynamic

region power.

There are many approaches and models to

identify, recognize behavior pattern of electricity

consume in region1 to region4. Statistically method

is the most popular in using today.

This paper tray to explain compare about

correlation linearity from statistically with scatter

plot and neural network methods. Self Organizing

Map is the one of Neural network approach. Results

will show visualization of linearity as graph. Reason

of linearity behavioral found is to modeling the next

purpose in controllability study. It’s a part of

handling system

1.1 Self Organizing Map

The SOM is an unsupervised neural network,

based on competitive learning, that implements a

non linear smooth mapping of high dimensional

input space onto low dimensional output space. The

neurons of the SOM form a topologically ordered

low- dimensional lattice that is an outstanding

visualization tool to extract knowledge about the

nature of the input space data.

The SOM is widely used as a data mining and

visualization method for complex data sets.

Application areas include, for instance, image

processing and speech recognition, process control,

economical analysis, and diagnostics in industry and

in medicine.

The SOM algorithm implements its mapping in

two stages. First the best matching unit (BMU) of

the input vector is selected by means of a

competitive process.

c= arg mini || x – mi (t) || , i = 1, 2, ...,N (1)

Then a cooperative step is performed, where the

winning unit and its neighbors are adapted

mi(t+1) = mi(t) + (t) hci (t)[x(t) - mi (t)] (2)

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1.2 Scatter Plot

A scatterplot matrix is a matrix of scatterplots

where each column contains the same X axis and

each row the same Y axis. A scatterplot matrix is

useful for visualizing how a dataset is distributed

through multiple variables. all of the scatterplots in

the matrix the same way, you can see how the same

clusters of points change shape from one scatterplot

to another

2. Methodology

Figure 2. Analysis Methodology

2.1 Scatter Plot Vusualization

Data Prepocessing

Each regions consumption data will be correlating to

another except the region itself as figure above.

Table 1. Sample Behavior Power Region in October 2006

Sum Of Power Plants Region

I Region

II Region

3 Region

4

AVG AVG AVG AVG

4465 666 1969 4062

4840 678 2084 4834

4876 679 2285 4971

5101 678 2124 4954

5000 656 2318 4943

5122 655 2222 4855

5029 645 1862 4586

4993 689 1420 3948

5652 600 1894 4332

5463 560 2177 4646

5363 592 2192 4736

5359 593 2165 4702

5346 621 2022 4671

5226 612 1944 4328

5020 596 1736 3959

5553 583 2039 4417

5802 568 1644 4695

5668 576 1728 4714

5565 577 1787 4512

5340 582 1484 4370

5004 581 1237 3653

4563 595 1015 3201

4142 631 969 2827

3679 649 1000 2566

3886 640 1019 2503

3926 604 923 2957

3974 592 1034 3240

4224 590 976 3340

4472 600 1100 3138

5220 586 1341 3773

5408 608 1553 3948

Data prepared from daily operations sheet in

Pusat Pengatur dan Penyaluran Beban (P3B) PT

PLN (persero) from October 2006 – December

2006. Its repsenting regular days and few of holiday.

Region 1 Region 2

Region 3 Region 4

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R e g io n I

3 5 0 0

4 0 0 0

4 5 0 0

5 0 0 0

5 5 0 0

6 0 0 0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2

T a n g ga l

R e gio n 2

5 5 0

5 7 0

5 9 0

6 10

6 3 0

6 5 0

6 7 0

6 9 0

7 10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 2 2 1 2 2 2 2 2 2 2 2 3 3 1

T a n g ga l

R e g io n 3

900

1100

1300

1500

1700

1900

2100

2300

2500

1 2 3 4 5 6 7 8 9 10 11 12 13 1 4 15 16 17 18 19 20 21 22 23 24 25 26 27 28 2 9 30 31

T a n g g a l

R e g ion 4

2400

2900

3400

3900

4400

4900

5400

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 6 17 1 8 19 20 21 22 23 24 25 2 6 27 28 29 30 31

T a n g g a l Figure 3. Region Power behavior pattern

Region 1 ↔ Region 2

Figure 4. Scatter Plot Correlation Between Region 1 and Region 2

Figure 4 showing that there is no linear correlation

between region 1 and region 2 .


Figure 5 Scatter Plot Correlation Between Region 1 and Region 3

Figure 5 showing that there is a linear correlation

between region 1 and region 3






Figure 7. scatter plot correlation between Region

2 and Region 3




Figure 8. Scatter Plot Correlation Between Region 2 and Region 4







400

500

600

700

800

900

1000

1100

1200

1300

1400

3 5 0 0 3 6 0 0 3 7 0 0 3 8 0 0 3 9 0 0 4 0 0 0 4 10 0 4 2 0 0 4 3 0 0 4 4 0 0 4 5 0 0 4 6 0 0 4 7 0 0 4 8 0 0 4 9 0 0 5 0 0 0 5 10 0 5 2 0 0 5 3 0 0 5 4 0 0 5 5 0 0 5 6 0 0 5 7 0 0 5 8 0 0 5 9 0 0 6 0 0 0 6 10 0

900

1000

1100

1200

1300

1400

1500

1600

1700

1800

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2000

2100

2200

2300

2400

2500

2600

2700

3 5 0 0 3 6 0 0 3 7 0 0 3 8 0 0 3 9 0 0 4 0 0 0 4 10 0 4 2 0 0 4 3 0 0 4 4 0 0 4 5 0 0 4 6 0 0 4 7 0 0 4 8 0 0 4 9 0 0 5 0 0 0 5 10 0 5 2 0 0 5 3 0 0 5 4 0 0 5 5 0 0 5 6 0 0 5 7 0 0 5 8 0 0 5 9 0 0 6 0 0 0 6 10 0

2000

2100

2200

2300

2400

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5000

5100

5200

3 5 0 0 3 6 0 0 3 7 0 0 3 8 0 0 3 9 0 0 4 0 0 0 4 10 0 4 2 0 0 4 3 0 0 4 4 0 0 4 5 0 0 4 6 0 0 4 7 0 0 4 8 0 0 4 9 0 0 5 0 0 0 5 10 0 5 2 0 0 5 3 0 0 5 4 0 0 5 5 0 0 5 6 0 0 5 7 0 0 5 8 0 0 5 9 0 0 6 0 0 0 6 10

900

1000

1100

1200

1300

1400

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400 500 600 700 800 900 1000 1100 1200 1300 1400

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400 500 600 700 800 900 1000 1100 1200 1300 1400

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4800

4900

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5100

5200

900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700

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2.2 Self Organizing Map Visualizations


4.82

5.22

5.62

d

0.556

0.757

0.958

d

Color code

Figure 10. Correlation

Between Region 1 and Region 2


between region 1 and region 2 .


4.82

5.22

5.62

d

1.48

1.84

2.2

d

Figure 11. correlation between Region 1 and Region 3

Figure 11. Showing that There is a Linear Correlation Between Region 1 and Region 3


4.82

5.22

5.62

d

3.68

4.01

4.34

d

Figure 12. Correlation Between Region 1 and Region 4




0.556

0.757

0.958

d

1.48

1.84

2.2

d





0.556

0.757

0.958

d

3.68

4.01

4.34

d



between region 2 and region 4.


1.48

1.84

2.2

d

3.68

4.01

4.34

d




Figure 16. Mapping Between Region 1 - Region 4

0.258

0.71

1.16

U-matrix

November

November

Oktober

Oktober

November

Oktober

Oktober

Oktober

Desember

Desember

Desember

Desember

108


3. Result Region 1 and region 2 based on statistically or

SOM results show that power behavior have no

linear correlation. Its mean that each region have

independent relationships in power consume.

Region 1 and region3 based on above data

indicate that power behavior have a linear

correlation. Its mean that each region especially

region 1 needs power from region3.

Region 1 and region 4 show that region 1 need

more power from region 4 because there is a linear

correlations.

Region 2 and region 3 show there is no linear

correlation. Its mean that each area is independent

for power preparing.

Region 2 and region 4 show there is no linear

correlation.

Region 3 and region 4 show there is a linear

correlation and each area is dependent for power.

Figure 16 showing correlation each region to

others. Its mean that region 1 have using power a lot

in December. The other side region1 also have great

less power in last December. Region 2 in peak

power at October but not much than peak in region

1. Region 3 almost likely than region 2 in middle

October. Region 4 have most less power in

November.

4. Conclusion

Statistically(scatterplot) and neural networks

are the same method of visualization its showed

correlation linearity sets of data.

Neural networks have a colorfully visualization

than scatter plot. Its can be show details the

information needs.

Electricity power behavior at each region are

different in peak of power and region relationship.

Power plant interactive with transmission lines

path to achieve balance system with centralized

operator.

Relationship happen between region 1, 3 and

region

Based on data indicated that region 2 relative

independent in transmission system.

Analysis result can be use to make mapping

model in intelligence study area.

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Assessment”, Proceedings of INNS/EPRI

Summer workshop of Neural Network

Computing for the Electric Power Industry,

Stanford,CA, Aug 1992. [2] Bala. BK, “Principles of System Dynamics”,

www.albany.edu/cp/sds/sdcourse/ , 1999, Aug

2006.

[3] Blackburn, “Protective Relaying Principles and

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Operating Procedures for Transfer Limits”,

www.pserc.wisc.edu/ecow/get/publicatio/reports/2001reports/ , 2001, Agustus 2006.

[5] Bouthiba, “Fault Location in EHF Transmission

Lines Using Artificial Neural Network”,

www.doi.wiley.com/10.1002/etep.5/, Agustus

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Transction of Power Delivery, Vol 20 No 3, Juli

2005, p 1817. [8] El-Keib, Ma, “Aplication of Neural Network in

Voltage Stability Assessment”, IEEE

Transactions of Power System, Vol 10 No 4,

November 1995, p 1890 – 1896. [9] Fausett. Laurene, “Fundamentals of Neural

Network: Architecture algorithm and

Aplication”, Prentice Hall, 1994. [10] Haykin. Simon, “Neural Network A

Comprehensive Faundation”, Prentice Hall,

1994. [11] Han and Kamber, “Data Mining; Concepts and

Tecniques”, Morgan Kauffman Publisher, 2001. [12] He. H, Cheng.S, et al, “Home Network Power

Line Communication Signal Processing Based

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July 2005, p 1879 [13] Klir G, Yuan,Bo., 1995, “Fuzzy Set And Fuzzy

Logic Theory and Application”, Prentice Hall. [14] Kusumadewi,Sri et al, 2004, ” Aplikasi Logika

Fuzzy Untuk Pendukung Keputusan”, Graha

Ilmu, Jogjakarta. [15] Marsudi, Djiteng., 2005, “Operasi Sistem

Tenaga Listrik”, Graha Ilmu, Jogjakarta. [16] Sudibyo, 2005, “Operasi Sistem Tenaga Listrik

dan Perangkat pendukungnya”, Majalah

Teknologi dan Energi Vol 5 No 1 Januari 2005

Hal :77 – 91, STT PLN [17] Riza, 2005, “Otomatisasi Transmisi dan

Distribusi untuk Meningkatkan Kualitas

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Documents

FOREWORD - portal.kopertis3.or.idportal.kopertis3.or.id/bitstream/123456789/1345/1/VISUALIZATION...International Conference on Telecommunication 2009 WELCOMING SPEECH ICTel2009 is