Mekanisme Load Balancing Server Menggunakan Metode Naive Bayes dengan Agen Psutils pada Software Defined Network - Aris Adi Utomo; Primantara Hari Trisnawan; Rakhmadhani Primananda (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2020)
The performance of the server is heavily influenced by the resources of those servers both include memory, disk and CPU. Server can experience overload when at one time get load traffic that exceeds its capability. To handle it can use the Load Balancing system using the Resource usage parameters of the server. This research will implement Load Balancing using the Naive Bayes algorithm with parameters including memory, disk and cpu. The built-in system will be applied to the Software Defined Network architecture by using the Fuzzy algorithm as a comparator. Testing was conducted using two Low text and text High test scenarios and three rates in each of the 25, 50 and 100 rate. The test parameters used include traffic distribution, throughput, response time, memory usage and CPU usage. From the test results obtained by Naive Bayes algorithm in all scenarios and test rates on Throughput, Response time, CPU Usage and Memory Usage parameters showed better results when compared to the Fuzzy algorithm. Average rating for CPU Usage testing for Low text and High text and Memory Usage for Low text and High text is 77.6% and 80% and 26.9% and 50.3%.