Seminar Nasional Teknologi Informasi Komunikasi dan Industri
2016: SNTIKI 8

Model Marcov Chains untuk Prediksi Perkembangan Usaha Perdagangan di Pekanbaru

Intan Suryani Sari (Laboratorium Data Mining Program Studi Sistem Informasi Fakultas Saisn dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau)
Mustakim Mustakim (Laboratorium Data Mining Program Studi Sistem Informasi Fakultas Saisn dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau)



Article Info

Publish Date
09 Nov 2016

Abstract

Enactment of Pekanbaru City as city services, the city of trade and industrial city make the rising growth of trade . It is certainly tighten the competition, to maintain and develop the business need for an effective strategy. Information trafficking business development next few years could be one of the basic reference for decision making to the business strategy . Markov Chains method is one method that can provide information on the probability of the future by analyzing data on the number of trading business several years earlier . The information generated in the form of trade development value 2 years. In this research predicted results obtained from business entities attributes, the value of capital, information capital, institutional, and business activities. The final results of the referenced decision-making with a percentage of 81.3% of the company's enterprises, 89.9% of capital range of> 100 million - 1 M, 73.9% with a description of a small capital, 79.2% institutional as suppliers, and 57, 4% of business activities for household needs. Keywords: Markov Chains, prediction, trading business

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Journal Info

Abbrev

SNTIKI

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

Description

SNTIKI adalah Seminar Nasional Teknologi Informasi, Komunikasi dan Industri yang diselenggarakan setiap tahun oleh Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau. ISSN 2579 7271 (Print) | ISSN 2579 5406 ...