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All Journal Jurnal Khatulistiwa Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING NUSANTARA: Jurnal Pengabdian Kepada Masyarakat CKI On Spot
Dwi yuni Utami
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Computer Science & IT Engineering Social Sciences

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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

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Implementasi Load Balancing Per address connection ECMP Algoritma Round Roubin Mikrotik Router Ahmad Fauzi; Dwi Yuni Utami
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.6319

Abstract

Internet access is a basic need that must be owned by both individuals and companies because of how important internet access is so that a company can work, in the current digital era, when internet access for a company or individual is experiencing problems, due to the ISP (Internet Service Provider). If the network is down or disconnected, it can be said that all activities will be inefficient, hampered, cannot open email, cannot connect to the central server, even entrepreneurs with orders via online cannot sell, for that when internet access becomes a vital object for companies, it is necessary an internet access or more than one ISP can use two or more ISPs where many methods are used to combine two or more internet accesses into one network that is connected by a local network but a very good method is used to maximize the two or more ISPs a is to use the Load Balancing method using the ECMP round roubin algorithm on the Mikrotik router device so it is hoped that internet access will continue even though one of the ISPs is down or network disturbances.
Attribute Selection in Naive Bayes Algorithm Using Genetic Algorithms and Bagging for Prediction of Liver Disease Dwi Yuni Utami; Elah Nurlelah; Noer Hikmah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 4, No 1 (2020): ---> EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (294.093 KB) | DOI: 10.31289/jite.v4i1.3793

Abstract

Liver disease is an inflammatory disease of the liver and can cause the liver to be unable to function as usual and even cause death. According to WHO (World Health Organization) data, almost 1.2 million people per year, especially in Southeast Asia and Africa, have died from liver disease. The problem that usually occurs is the difficulty of recognizing liver disease early on, even when the disease has spread. This study aims to compare and evaluate Naive Bayes algorithm as a selected algorithm and Naive Bayes algorithm based on Genetic Algorithm (GA) and Bagging to find out which algorithm has a higher accuracy in predicting liver disease by processing a dataset taken from the UCI Machine Learning Repository database (GA). University of California Invene). From the results of testing by evaluating both the confusion matrix and the ROC curve, it was proven that the testing carried out by the Naive Bayes Optimization algorithm using Algortima Genetics and Bagging has a higher accuracy value than only using the Naive Bayes algorithm. The accuracy value for the Naive Bayes algorithm model is 66.66% and the accuracy value for the Naive Bayes model with attribute selection using Genetic Algorithms and Bagging is 72.02%. Based on this value, the difference in accuracy is 5.36%.Keywords: Liver Disease, Naïve Bayes, Genetic Agorithms, Bagging.
Co-Authors Ahmad Fauzi Elah Nurlelah Fani Nurona Cahya Minda Septiani Noer Hikmah Nurmalasari Nurmalasari Sischa Rahmawati Tri Agus Setiawan