scholarly journals Determination of Microbiological Quality of Fermented Sausage Samples by Fuzzy Logic Approach

Author(s):  
Özlem ERTEKİN ◽  
Sema KAYAPINAR KAYA
2019 ◽  
Vol 2 (2) ◽  
pp. 80-91
Author(s):  
Agus Pamuji

The quality of software production is considered important when testing which is involves several IT Staff such as IT development, operation, end-user. One of the issue was having today is a bug processing where it almost all platforms too difficult to avoid from the bugs and even might be full of the risks. In the main of Our focus is on how to measure and attempt to reduce the number were indicated as bugs from low up to critical levels. Furthermore, we were propose with a method already known as a fuzzy logic approach to measure the severity of the presence of bugs during the testing process. there are 20 thousand even more bugs have been reported and be supposed removed with the fuzzy logic approach with various levels. As The end result is that we have found a gradual 20% reduction in various criteria in the testing process as experimentally. Therefore, fuzzy logic is considered as  effective enough to be able to improve existing methods and support to reduce bugs significantly.


Tibuana ◽  
2019 ◽  
Vol 2 (01) ◽  
pp. 58-65
Author(s):  
Prihono Prihono

Determination of poor families in the poverty database is still less than perfect. There is still no multi criteria decision making (MCDM) technique in the grouping of poor families, making the results of the criteria in grouping poor families still far from expectations. So, this article discusses the use of the multi criteria decision making (MCDM) technique for grouping poor families in the poverty database in the Malang district. Fuzzy logic is one technique of MCDM which is commonly used for affirmation of decisions. In a random sampling of 35 families taken from the Malang District poverty database, the classification that was originally obtained was only obtained by 2 (two) classifications of poor families, namely: very poor families and poor families. But after it was calculated using the Fuzzy Logic method, it was found 3 (three) classifications of poor families, namely very poor families, poor families, and almost poor families. The magnitude of the distribution of the poor family classification is: 17 (seventeen) very poor families which previously were 14 (fourteen), 17 (seventeen) families were categorized as poor families that were previously 21 (twenty one), and 1 (one) family in the category of near-poor families that were not previously found. With these results, it can be concluded that the Fuzzy Logic method can and is able to provide better and more diverse results in determining poor families in the Malang District poverty database.


Author(s):  
Nur Syuhada Muhammat Pazil ◽  
Norwaziah Mahmud ◽  
Siti Hafawati Jamaluddin ◽  
Umi Hanim Mazlan ◽  
Afiqah Abdul Rahman

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