REDUKSI ATRIBUT BERDASAR MATRIK DISCERNIBILITY TEORI ROUGH SET DALAM SIMULASI BENCANA KEBAKARAN

Herdiyatmoko, Hendrik Fery (2017) REDUKSI ATRIBUT BERDASAR MATRIK DISCERNIBILITY TEORI ROUGH SET DALAM SIMULASI BENCANA KEBAKARAN. Jurnal Simeteris, 8 (1). pp. 145-154. ISSN 2252-4983

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Abstract

Fire disaster can occur anywhere, anytime, can occur in the area of residence, in mines and in the woods. There is an important issue in the automatic fire detection, which on fire parameter data. Parameters of these fires can be temperature, humidity, fuel fires, fires, etc. In this study fires parameter data collected by the sensor network wireless networks are positioned specifically on the location in the building. However, not all parameters of fires will be used, because the more parameters used fires will cause computational load increases, so the data is the most important parameters that will be used. One way to extract the most important component is the use of parameter selection attribute based on attribute reduction with Rough Set Theory. The purpose of this study is to reduce the parameters or attributes of fires that produce lower complexity in the data analysis of fires.The output of attribute reduction is used as the basis for an evacuation route search catastrophic fires.

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