Greetings and Thanks from the General Chair Foreword from Head of Department of Electrical Engineering,

  TABLE OF CONTENTS

KEYNOTE SPEAKERS

I-1 Multi-User MIMO Wireless System -From Theory to Chip Design

  1 Prof. Hiroshi Ochi I-2

  11 Prof. Dr. Trio Adiono I-3

  13 Adi Rahman Adiwoso

CIRCUITS AND SYSTEMS

  CC1

  14

Ahmed LutfiElgreatly, Ahmed AhmedShaaban, El-Sayed M. El-Rabaie

  CC2

  19

Aditya Ferry Ardyanto, Idham Hafizh, Septian Gilang Permana Putra, Trio

Adiono

  CC3

  24

Sidiq Syamsul Hidayat, TotokPrasetyo, Amin Suharjono, Kurnianingsih,

Muhammad Anif

  CC4

  28

B. Supriyo, S.S.Hidayat, A. Suharjono, M.Anif, Sorja Koesuma

  CC5

  33 Hugo Adeodatus Hendarto, Munadi, Joga Dharma Setiawan CC7

  44 Julian Ilham, Wan-Young Chung

  CC8

  50 Bambang Sugiarto, ElanDjaelani

  CC9

  56 Kevin Eka Pramudita, F. Budi Setiawan, Siswanto CC10

  61 Ahmad A. Daoud, Ahmed A. Shaaban, Sherif M. Abuelenin CC11

  66 Muhammad Faris, Adha Imam Cahyadi, Hanung Adi Nugroho

  CC12

  72 Devi Munandar, Djohar Syamsi

  CC13

  77

Ngurah Ayu Ketut Umiati, Siti Nurrahmi, Kuwat Triyana, Kamsul Abraha

  CC14

  81 Vipin Gemini CC15

  87 Nia Maharani Raharja ,Iswanto, Muhammad Faris, Adha Imam Cahyadi.

CC16 METHODOLOGY OF FUZZY LOGIC WITH MAMDANI FUZZI MODELS

  91 Indra Sakti

  CC17

  97

Arkham Zahri Rakhman, Lukito Edi Nugroho, Widyawan, Kurnianingsih

  

CC18 103

Huda Ubaya, Afdhal Akrom

  

CC19 109

Gunawan Wibisono, Tierta Syafraditya

  

CC20 113

  Imam Santoso, Thomas Sri Widodo, Adhi Susanto, Maesadjie Tjokronagoro

IMAGE PROCESSING AND MULTIMEDIA

  

IP2 122

Prati Hutari Gani, Maman Abdurohman

  

IP3 127

Rahmat Sholeh, Fahrul Agus, and Heliza Rahmania Hatta

  

IP4 131

Kazuyo IWAMOTO, Hitoshi TOKUNAGA, Toshimitsu OKANE

  

IP5 137

Laurentius Kuncoro Probo Saputra, Hanung Adi Nugroho, Meirista Wulandari

  

IP6 142

Mat Syai’in, M.F. Adiatmoko, Isa Rachman, L. Subiyanto, Koko Hutoro,

Ontoseno Penangsang, Adi Soeprijanto

  

IP7 Stanley Suryono Wibisono, Florentinus Budi Setiawan

  

IP8 153

Bagas Sakamulia Prakoso, Ivanna K. Timotius, Iwan Setyawan

  

IP9 158

Muhamad Iradat Achmad, Hanung Adinugroho, Adhi Susanto

  

IP10 165

Ignatia Dhian Estu Karisma Ratri, Hanung Adi Nugroho, Teguh Bharata

Adji

  

IP11 170

S. R. Sulistiyanti, M. Komarudin, L. Hakim, A. Yudamson

  

IP12 175

Wahyul Amien Syafei, Masayuki Kurosaki, and Hiroshi Ochi

  

IP13 181

R. Rizal Isnanto

INFORMATION AND COMPUTER TECHNOLOGIES

  ICT1 187

   Dania Eridani, Paulus Insap Santosa

  

ICT2 192

  

ICT3 198

Christiono Utomo, Yani Rahmawati

  

ICT4 202

Oky Dwi Nurhayati, Kurniawan Teguh M

  

ICT5 207

Mohammed Alotaibi

  ICT6

  

Supeno Djanali, FX Arunanto, Baskoro Adi Pratomo, Abdurrazak Baihaqi,

Hudan Studiawan, Ary Mazharuddin Shiddiqi

  

ICT7 216

Ika Widiastuti, Nurul Zainal Fanani

  

ICT8 221

Eduard Royce, Iwan Setyawan, Ivanna K. Timotius

  

ICT9 225

Siti Mardiana

  

ICT10 232

Gian Gautama, Imanuel Widjaja, Michael Aditya Sutiono, Jovan Anggara,

Hugeng

  

ICT11 Daniar Fahmi, Abdillah F. I., IGN Satriyadi Hernanda, Dimas Anton Asfani

  

ICT12 244

Putra Wanda, Selo, Bimo Sunafri Hantono

  

ICT13 249

Indah Soesanti

  

ICT14 254

Albaar Rubhasy, A.A.G. Yudhi Paramartha, Indra Budi, Zainal A.

  Hasibuan

  

ICT15 259

Agus Fahrul, Sumaryono, Subagyo Lambang, Ruchaemi Afif

  

ICT16 265

Istiadi, Emma Budi Sulistiarini ,Guntur Dharma Putra

  

ICT17 271

  

ICT18 275

Hermawan Prasetyo, Ayu Purwarianti

  

ICT19 280

Evi Triandini, Daniel Siahaan, Arif Djunaidy

  

ICT20 285

Istiadi, Lukito Edi Nugroho, Paulus Insap Santosa

  

ICT21 290

F.X. Satriyo D. Nugroho, Teguh Bharata Adji, Silmi Fauziati

  

ICT22 296

Meta Lara Pandini, Zainal Arifin and Dyna Marisa Khairina

  

ICT23 302

Agung B. Prasetijo, Sami S. Alwakeel and Hesham A. Altwaijry

  

ICT24 308

Falahah, Defrin Karisia Ayuningtias

  

ICT25 314

Ajub Ajulian Zahra Macrina and Achmad Hidayatno

  ICT26 318

   Priyogi B., Nan Cenka B. A., Paramartha A.A.G.Y. &Rubhasy A.

POWER SYSTEMS

  

PS1 323

Ahmad Musa, Leonardus H. Pratomo, Felix Y. Setiono

  

PS2 327

Ms. Alamuru Vani, Dr. Pessapaty Sree Rama Chandra Murthy

  

PS3 333

M. Usman Aslam, Muhammad Usman Cheema, Muhammad Samran, Muhammad Bilal Cheema

  

PS4 338

M. Usman Aslam, Muhammad Usman Cheema, Muhammad Samran,

  

PS5 345

Suyanto, Soedibyo, Aji Akbar Firdaus

  

PS6 350

Slamet Riyadi

  

PS7 355

  

PS8 360

Hanny H. Tumbelaka

  

PS9 365

  

I.G.N Satriyadi Hernanda, Evril N. Kartinisari, Dimas Anton Asfani, Daniar

Fahmi

PS10 370

   Imam Abadi, Adi Soeprijanto, Ali Musyafa’

  

PS11 375

Antonius Rajagukguk, Mochamad Ashari, Dedet Candra Riawan

  

PS12 381

Yusri Syam Akil, Syafaruddin, Tajuddin Waris, A. A. Halik Lateko

  

PS13 386

Ramadoni Syahputra, Imam Robandi, Mochamad Ashari

  

PS14 392

Soedibyo, Ciptian Weried Priananda, Muhammad Agil Haikal

  

PS15 398

Idreis Abdualgader , Eflita Yohana, Mochammad Facta

  

PS16 402

Soedibyo, Mochamad Ashari, Ramadoni Syahputra

  

PS17 407

Mochammad Facta, Hermawan, Karnoto,Zainal Salam, Zolkafle Buntat

  

PS18 411

  

PS19 417

Imam Wahyudi F., Wisnu Kuntjoro Adi, Ardyono Priyadi, Margo Pujiantara, Mauridhi Hery P TELECOMUNICATIONS

  

TE1 422

  

TE2 427

Eva Yovita Dwi Utami, Deddy Susilo, Budihardja Murtianta

  

TE3 432

Muhammad Suryanegara, Naufan Raharya

  

TE4 436

Rizadi Sasmita Darwis, Suwadi, Wirawan, Endroyono, Titiek Suryani, Prasetiyono Hari Mukti

  

TE5 441

Florentinus Budi Setiawan

  

TE6 445

Prasetiyono Hari Mukti, Eko Setijadi, Nancy Ardelina

  TE7 449

   Yoga Krismawardana, Yuli Christyono, Munawar A. Riyadi

  

TE8 455

Savitri Galih, Marc Hoffmann, Thomas Kaiser

  

TE9 459

Andrian Andaya Lestari,Oktanto Dedi Winarko, Herlinda Serliningtyas, Deni Yulian

  

Enhancing Online Expert System Consultation

Service with Short Message Service Interface

Istiadi

  Abstract— Short message service (SMS) that has been widely used in various fields could potentially utilized for problem- solving consulting services that are based on expert system, so it takes a kind of application platform to implement this service. This paper proposes an expansion of online expert system services (web and wap based) by adding an application use SMS interface. Knowledge base of the expert system, which employs a decision tree approach, is expressed in the form of a database that can be accessed by the application interfaces, including SMS interface. According to the experiment results, the decision tree has been able to play a role directing the consultation mechanism from an initial question to reach a conclusion interactively. Thus, a problem-solving case that can be expressed in the decision tree allows the implementation of this system.

  An ES is basically a form of computing application, which works based on facts any rules accommodated on a knowledge base. The knowledge base mainly acts for representing knowledge extracted from experts and allows particular computer to do reasoning process in a particular problem domain [10].

  ELATED W ORK

  II. R

  This paper proposes the development of SMS interface application that refers to a particular ES’ knowledge base, which is represented in a database system in the previous work [2]. This service development is based on application interaction concept that employs question and answer (as request-response mechanism in client-server system) in an ES, which refers to a particular knowledge base. The SMS application software will be developed for handling message processing and replaying user’s request automatically.

  Development efforts of expert system using SMS has been carried out, such as cases of fish disease in [12] and field of crops in [13]. However, the system was developed for specific purposes. The breadth of potential use of SMS as consulting services should be an available platform that is more general to accommodate for resolving problems with an interactive mechanism.

  Expert System (ES) is a particular media that provides problem-solving service within a specific problem domain [10]. When problem domain involves people’s need, then this ES is supposed to be capable to extensively reach wider targeted users. The ES that have been developed utilizing web interface has been successfully giving several service access [11], however the existence of SMS feature in common mobile phone to be another potential alternative for ES implementation. for handling the textual data processing and giving information back to users as an auto reply system. This condition allows this media to be the interaction process. Thus, the mechanism is possible to be implemented in an ES as consulting system.

  I NTRODUCTION SMS is basically a text-exchanging feature between mobile subscribers with a limited amount of characters [1]. Although the message is limited, SMS has been a communication media of public service, especially in developing countries, such as the disease prevention services [2], m-banking services [3,5,4,6], and the field of agriculture [7,8,9]. Compatibility of SMS service to various types device of mobile phones which continues to grow, making this service as one of more accessible communication media. Advantages of these services can be used for consulting services regarding the problems in the community which aided by computing technologies such as expert systems.

  Keywords— expert system; database; SMS; decision tree I.

  Yogyakarta, Indonesia e-mail: guntur.dharma@mail.ugm.ac.id

  1 , Emma Budi Sulistiarini

  Technology Universitas Gadjah Mada

  3 Department of Electrical Engineering & Information

  3

  Guntur Dharma Putra

  Widyagama University of Malang Malang, Indonesia e-mail: {istiadi,emma_budi}@widyagama.ac.id

  2 Department of Industrial Engineering

  1 Department of Electrical Engineering

  2

  Evolving communication technology allows a particular computer system to work from a local scale network to an Internet, which is highly potential for implementing ES. Like an online ES, for instance, web usage that allows an ES to be accessible by more users. However, this system costs more complex development [14]. An ES as online consultation media has to pay attention to the interaction aspects. The systems are supposed to be capable for dynamically generating interface for the users, including from consultation process until inference process [15]. 2014 1st International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE) knowledge base is accommodated by using a database that will be accessed by web and WAP applications. This approach is

  Root node

  likely to be carried out as this implements server side method, which is suitable for SMS.

  A SMS based ES has been developed in [12] and [13], although those works are only specified for specific cases. In [12], expert system applications using SMS for fish disease cases with a case-based reasoning approach. While in [13], SMS based expert system use fuzzy approach to case of crops field. Both of these applications require particular design for the implementation because it uses some parameters that need to be considered analytically. While at the other cases it may take more general representation such as with decision tree approach. So the chances of its use will be more flexible.

  As SMS offers a wide range for implementation, a SMS based ES is also applicable to be implemented for other particular cases. This paper proposes a general ES model, thus Fig. 1. Example of a decision tree [16]. this model is applicable for any particular cases that are able to be represented using decision tree approach.

  Representing knowledge base by using decision tree approach basically requires several definition processes.

YSTEM ESIGN

  D

III. S Firstly, defining a problem domain will be the main concern.

  Secondly, defining facts or symptoms that are probably appear The system design is designed based on our previous work in identification process as a decision node. Thirdly, defining in [11], that was developing a web-based ES with web and inference as the diagnosis result of several facts or symptoms WAP application for consultation application. The system was that appears as a leaf node. Fourthly, defining basic rule utilizing an arbitrary database for holding knowledge base elements that are illustrate the relation between nodes as a representation. Therefore the system is accessible through web decision tree representation. and WAP interfaces. The usage of the database also allows experts or knowledge engineers to carry out data entry or

  Database model illustrated in relational diagram (Fig. 2.) is editing process through web interface. An expansion for SMS developed to represent above-mentioned knowledge base. The based consulting application is done by adding a software that Database design consists of Case Table, Symptom Table, will act as SMS server and gateway. Furthermore, explanations Diagnose Table, and Rule Table. regarding system design will be divided into knowledge base representation and system architecture, which is expanded using SMS, based consulting application.

A. Database of Knowledge Base Representation

  This ES will employ decision tree approach in knowledge base representation [11]. The decision tree approach itself is basically a collection of nodes that are connected each other. These nodes are categorized as root node, decision node, and leaf node. The root node represents first fact that will be an initial point where seeking process for identifying emerging symptoms is started. This identification will provide options to walk through other branches into other nodes, either decision node or leaf node. The decision node owns identical purposes with root node, but it is not located in the initial position. Leaf node is particularly a node that marks the ending position of a tree. This leaf node must be a decision that points to a Fig. 2. Database design to store knowledge base representation. particular solution. Fig. 3. An expanded Web and WAP based Expert System architecture using SMS consulting application.

  Case table acts to keep problem domain definition data, Web interface. Furthermore, consulting application can utilize which consists of Case Title fields and its explanation. the stored knowledge representation, based on access media Symptom Table is used for storing fact definitions as an type, to provide consultation services to the users. Each type of identified symptom. This Symptom table holds question field consulting application is supposed to own similar interpretation for symptom identification and description field for the to the knowledge base representation. Fig. 4 illustrates the descriptions. Diagnose Table will act to store leaf node decision tree seeking algorithm as a knowledge base representations. That table will also store conclusion representation in flowchart diagram. definitions or diagnosis results and suggestions data.

  Begin The decision tree structure representation will be stored in

  Rule Table. Several fields that are accommodated by Rule Table covers IsRootNode field as first stage initial

  Select a case identification data (to find out the existence of root or decision nodes), Identification_Question field as a storage for questions data regarding Symptom table, Answer_Description field to store options label data, Answer_Link field to store the link to Start with query to root node of the selected case an answer, either a link to next question or a link to a decision (diagnosis result), and IsANswerLeafNode field to store answer indication data, whether leaf node will stop or no. Show multiple choice question which nodes linked

B. Design of System Architecture

  System architecture design (shown in Fig. 3.), which Get a node as link of the answer previously consisted of knowledge representation databases, development application, and consulting application for Web and WAP interfaces, will be expanded by using SMS

  No application. This SMS application will provide a proper access Is leaf node? to the data stored in database, accordingly SMS based consultation is possible to be built. The SMS application

  Yes utilizes request-response communication concept in order to provide consulting application based on the knowledge base

  Show Conclusion of the selected leaf node stored in database. Thus, this SMS application would be a particular interface for an ES consultation service.

ESULT AND

  This SMS application is developed by using PHP language as the server side application. This application employs Gammu software as the SMS gateway that provides send- receive interface for text messages to the clients. The SMS gateway device will provide communication media to the mobile network that will be forwarded to the mobile subscriber.

  Fig. 6. is basically an application form to facilitate rule base construction using decision tree approach. Based on that approach, a symptom identification process is initially began with first question that represents root node. Every identification phase (question) will provide an alternative answer with a label as a particular branch. The answer branch can be aimed to further symptoms identification or a specific conclusion. Furthermore, appropriate answer link is supposed

  Fig. 6. Interface form for rule defining.

  A particular case is defined to cover specified problem domain. Then, symptoms that are likely to occur and its diagnosis results are defined in that problem domain. Symptoms definition processes are followed by several questions to identify some facts that occur. Diagnosis result definition processes consist of conclusion statements and given solutions or suggestions. After symptoms and its possible diagnosis are defined, knowledge engineers are able to construct rule structure into a decision tree that consists of several linked nodes. Figure 6 illustrates an application form for constructing the rule base.

  Knowledge Base (KB) representation builder is a back-end control panel for the entire system. There, knowledge engineers are able to insert or edit existing KB remotely through a Web based application. Based on defined system design, some features are developed to insert case type data, symptoms, diagnosis types, and rule bases.

  A. A Web based Knowledge Base Representation Builder

  Based on common ES concept, this chapter is focused to the development of knowledge base representation builder and SMS based consultation application. Several explanations about the development of knowledge base representation builder is mainly focused to decision tree construction mechanism, while explanation about SMS based consultation application is mainly given by consultation process mechanism.

  ISCUSION

  D

  V. R

  Based on World Health Organization (WHO) agreement, the dengue fever levels of severities are classified into dengue without warning sign, dengue with warning sign, and severe dengue [9]. According to the classification, there are several symptoms and actions that are required to be performed. Based on that reference, this ES application is developed as a consultation application by identification process through question and answer regarding the possibly identified symptoms, so that a proper action can be easily determined.

  As seen in Fig. 4, the seeking process is started by choosing appropriate case as the problem domain. Then, identifying process is began from root node, which contains initial question. Each identification questions contains multiple choices with next node regarding to the selected answer. When the users answer a particular question, a node is obtained. If that is a leaf node, then the identifying process will reach a conclusion. Nevertheless, if the node is a decision node, then the identification process will continue by showing the next question. This identification process will take place step by step between decision node until the process reaches the leaf node. Based on this algorithm, each application can be developed by using its own programming language platform.

  1

  Dengue fever disease had been a serious worldwide concern as seen in Dengue Map

  ONSULTING

  C

  EVER

  F

  ENGUE

  : D

  XAMPLE

  E

  ASE

IV. C

  , an effort to keep monitoring these disease incidents globally. Beside preventive efforts to prevent the spread of this disease, an effort to take proper actions when the symptoms occur is also required to be carried out. A well-known and easily accessible communication service like SMS is expected to be an appropriate consultation media to detect initial detection of this disease. Therefore, this paper employs dengue fever as a case example for case study. by users. Consultation can be performed using available access Fig. 7. illustrates the decision tree of Dengue Fever media, either Web, WAP, or SMS interface. consultation process. The model possesses 13 questions and six decisions in total. In this scenario, the experiment will test

B. SMS based Consulting Application whether the developed system would give question and

  decision correctly according to the decision tree model. The This application provides a service for users to perform a desired path is Q1-Q3-Q4-Q6-Q7-Q8-Q9-Q10-D4. consultation using SMS communication. Consultation process will be performed using question and answer mechanism between the service application and users, right after the user has been registered.

  Users are able to continue to consultation process immediately after finished the registration process and replied according to the given instruction. This experiment is carried out based on the following decision tree shown in Fig. 7.

  Q1

  N Y

  Q3 Q2

  Y N N Y

  Q4 Q5

  D1 D2 N Y Y Fig. 8. Consultation phase toward a conclusion.

  N

  Q4’

  N Q5’ Consultation process will begin with initial question from Y root node (Q1) as shown in Fig. 8. Each question will always

  Y

  Q2’

  be followed by answer options to reply. Users are required to Y N simply reply the question by replying the message according

  N to the given instruction. Consultation process will continue

  Q2” Y

  with appropriate questions according to the constructed

  Q6

  N decision tree model. The process will end up in a leaf node

  N Y where a conclusion is drawn; in this case, the experiment

  Q7 reached D4 decision.

  N D3 Y

  ONCLUSION Q8

  VI. C N Knowledge base of the expert system with decision tree

  Y

  Q9

  approach is accommodated in a database that allows to be N Y accessed by an applications interface, including SMS interface

  Q10

  for consultation application. The consultation mechanism, by Y N means question and answer can work as an auto reply system.

  The decision tree has been able to play a role to direct the consultation mechanism from an initial question on a root

  Q11 node until it finds a conclusion at a leaf node. Thus, this

  D4 system is also capable in implement any other problem

  N Y domains, if it can be expressed by a decision tree models.

  Q12 CKNOWLEDGMENT

  N A Y The authors of this research would like to express their

  Q13

  gratitude to Directorate General of Higher Education, Ministry Y N of Education and Culture of Indonesia for giving the research grant to support this work in 2014.

  D5 D6

  EFERENCES

  R

  [2] C. Déglise, L. S. Suggs, and P. Odermatt, “Short Message Service (SMS) Applications for Disease Prevention in Developing Countries,” Journal of Medical Internet Research, vol. 14, no. 1, p. e3, Jan. 2012.

  [3] Rahman, B. A., Azlina, N., Shajaratuddur Bt Harun, K., & Bt Yusof, Y., 2013, SMS banking transaction as an alternative for information, transfer and payment at merchant shops in Malaysia. In Information Technology and e-Services (ICITeS), 2013 3rd International Conference on (pp. 1-6). IEEE. [4] Thulani, D., Kosmas, N., Collins, M., & Lloyd, C. (2011). Adoption and use of sms/mobile banking services in zimbabwe: an exploratory study. Journal of Internet Banking and Commerce, 16(2), 149-167. [5] Mousumi, F., & Jamil, S. (2010). Push Pull Services Offering SMS Based m-Banking System in Context of Bangladesh. Int. Arab J. e-

  Technol., 1(3), 79-88. [6] Malik, G., & Gulati, K. (2013). An Exploratory Study on Adoption and Use of SMS/Mobile Banking in India with Special Reference to Public

  Sector Banks.Pacific Business Review International. Volume 5 Issue, 11. [7] Vishwakarma, R. G., & Choudhary, V. (2011, July). Wireless solution for irrigation in agriculture. In Signal Processing, Communication,

  Computing and Networking Technologies (ICSCCN), 2011 International Conference on (pp. 61-63). IEEE. [8] Ding, X., Xiong, G., Hu, B., Xie, L., & Zhou, S. (2013, July).

  Environment monitoring and early warning system of facility agriculture based on heterogeneous wireless networks. In Service Operations and Logistics, and Informatics (SOLI), 2013 IEEE International Conference on (pp. 307-310). IEEE. [9] Agrawal, R., Atray, M., & Sundari, S. K. (2013, December). KrishiEkta: integrated knowledge and information distribution system for Indian agriculture. In Proceedings of the 4th Annual Symposium on Computing for Development(p. 19). ACM. [10] Turban, E. and Aronson, JE., 1998, Decision Support System and

  Intelligent Systems, Prentice-Hall International Inc., New Jersey [11] Istiadi and Sulistiarini, E. B., Representing Knowledge Base into Database for WAP and Web-based Expert System , International

  Conference on Information Systems for Business Competitiveness (ICISBC 2013) , 2013 [12] Wang, Guirong, and Daoliang Li. “A Fish Disease Diagnosis Expert System Using Short Message Service.” In WRI International Conference on Communications and Mobile Computing, 2009. CMC ’09, 3:299– 303, 2009. doi:10.1109/CMC.2009.262.

  [13] Mao, Cheng, Yuan Hongbo, Shi Junwei, and Cheng Man. “The Research of Crop Expert System Based on GSM.” In Second International Conference on Intelligent Computation Technology and Automation, 2009. ICICTA ’09, 4:705–7, 2009. doi:10.1109/ICICTA.2009.884. [14] Duan, Y., Edwards, J.S., Xu, M.X. , 2005, Web-based expert systems: benefits and challenges, Information & Management Volume 42, Issue 6, September 2005, Pages 799–811 [15] Escribano, J.J, Murciano, R., Gervas, P., 2001, From Client’s dreams to Achievable Projects : An expert system for determining web site feasibility, Proceeding ICEIS 2001

  [16] Gamberger, D. & Šmuc, T. , 2001, Data Mining Server [http://dms.irb.hr/]. Zagreb, Croatia: Rudjer Boskovic Institute, Laboratory for Information Systems. [17] W. H. O. " Dengue Guidelines for diagnosis, treatment, prevention and control."Geneva: World Health Organization (2009).