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RANCANG BANGUN SISTEM INFORMASI BATAM DIRECTORY MENGGUNAKAN METODE BACKWARD CHAINING BERBASIS MOBILE Hamsir hamsir; Gunadi W Nurcahyo; Sarjon Defit
Elektron : Jurnal Ilmiah Vol 4 No 2 (2012): Elektron Jurnal Ilmiah
Publisher : Teknik Elektro Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1004.268 KB) | DOI: 10.30630/eji.4.2.30

Abstract

This article is designed for an information system in the form of expert system applications to present information on Batam Directory. The purpose of this system is to help provide information about the city of Batam as a whole to the residents of Batam city in particular and thelocal and foreign tourists as well as prospective investors in general. The system presents information in the form of public service to the residents of Batam city government and other newcomers as well as products and services are made ​​and offered by the business and government. The analysis was done by determining the first goal, then do these arching to obtain the desired information. The design system uses backward chaining inference method to the implementation ofthe system using My-SQL database systems and programming languages​​ of PHP and JQuery. The system is based on mobile, so it can be accessed using a mobile device.
SELECTION OF DEFUZZIFICATION METHOD TO OBTAIN CRISP VALUES FOR REPRESENTING UNCERTAIN DATA IN A MODIFIED SWEEP ALGORITHM Gunadi W Nurcahyo
Elektron : Jurnal Ilmiah Vol 5 No 2 (2013): Elektron Jurnal Ilmiah
Publisher : Teknik Elektro Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.524 KB) | DOI: 10.30630/eji.5.2.50

Abstract

A study of using fuzzy-based parameters for solving public bus routing problem with uncertain demand is presented. The fuzzy-based parameters are designed to provide data required by the route selection procedure. The uncertain data are represented as linguistic values which are fully dependent on the user’s preference. Fuzzy inference rules are assigned to relate the fuzzy parameters to the crisp values which are concerned in the route selection process. This paper focuses on the selection of the Defuzzification method to discover the most appropriate method for obtaining crisp values which represent uncertain data. We also present a step by step evaluation showing that the fuzzy-based parameters are capable to represent uncertain data replacing the use of exact data which common route selection algorithms usually use.