Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Gilang Ramadhan
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis Performa State Snapshot Transfers (SST) Tipe Blocking (Rsync) dan Non Blocking (Xtrabackup-V2) pada MariaDB Galera Cluster Gilang Ramadhan; Mahendra Data; Kasyful Amron
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1125.575 KB)

Abstract

Reliability and availability of database server becomes the crucial things of application system. There are so many researches that have been done in order to increase the reliabilty and availability of database server. The example is using database replication mechanism. MariaDB is one of DBMS that has a replication mechanism through MariaDB Galera Cluster application. MariaDB Galera Cluster has several methods called State Snapshot transfer (SST) which is used for replication process, namely Rsync, Xtrabackup, Xtrabackup-v2, and Mysqldump. This study focused to compare the performance of Rsync method and Xtrabackup-v2 method. The experimental results show that both methods have a similar performance. Number of nodes in a cluster can affect the performance of cluster. Cluster with two nodes would be more vulnerable to become an error if one of the node becomes has failed. Therefore, the minimum number of nodes on a cluster is three on condition that there is just one node that failed. This experiment also results another conclusion that SST method that used and number of nodes can affect the replication times. Rsync method has a shorter duration of replication compared to the Xtrabackup-v2.
Optimasi Peramalan Jumlah Kasus Penyakit Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Dengan Algoritma Genetika Gilang Ramadhan; Budi Darma Setiawan; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (967.91 KB)

Abstract

The number of disease cases has increased and decreased every month. This has an impact on the unbalanced of medicine availability such as, lack of supply of medicine, waste of medicine, medicine that are not on target, damaged medicine and so on. Therefore forecasting on number of disease cases is needed to determine the number of disease cases within a certain time. One of forecasting method that can be used is backpropagation neural network method. This method can be optimized using genetic algorithm to produce optimal results. The optimized parameters are weight and bias which will be used in backpropagation algorithm. The purpose of this study is to forecast the number of disease cases at Puskesmas Rogotrunan, Lumajang using backpropagation method optimized by genetic algorithm. From this study the optimal parameters of genetic algorithm are population=180, combination of cr and mr respectively 0,4 and 0,6, generation=100. The optimal parameters of backpropagation algorithm are total data=16, input neuron=6, iteration=1000, alfa=0,1. Accuray obtained with MSE=87,2 with data test of the number of disease cases in january to desember 2016. From the value of MSE obtained using backpropagation method optimized by genetic algorithm can be used to forecast the number of disease cases.
Co-Authors Budi Darma Setiawan Kasyful Amron Mahendra Data Marji Marji