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Data Mining Predicts the Need for Immunization Vaccines Using the Naive Bayes Method R Arri Widyanto; Meidar Hadi Avizenna; Nugroho Agung Prabowo; Kemal Alfata; Agus Ismanto
Journal of Applied Data Sciences Vol 2, No 3: SEPTEMBER 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i3.39

Abstract

In December 2019, SARS-CoV-2 caused the coronavirus disease (COVID-19) to spread to all countries, infecting thousands of people and causing death. COVID-19 causes mild illness in most cases, although it can make some people seriously ill. Therefore, vaccines are in various phases of clinical progress, and some of them have been approved for national use. The current state of affairs reveals that there is a critical need for a quick and timely solution to the need for a Covid-19 vaccine. Non-clinical methods such as data mining and machine learning techniques can help to do this. This study will focus on US COVID-19 Vaccination Advances using Machine learning classification algorithms and Using Geospatial analysis to visualize the results. The paper's findings indicate which algorithm is better for a given data set. Naive Bayes algorithm is used to run tests on real world data, and is used to analyze and draw conclusions. Period of Accuracy and performance, and it was found that Naive Bayes is very superior in terms of time and accuracy.
Applying the Apriori Algorithm to Analyze and Optimize Medical Device Inventory Management Meidar Hadi Avizenna
Journal of Applied Data Sciences Vol 3, No 4: DECEMBER 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i4.33

Abstract

Extracting data or an effort to retrieve valuable knowledge and information in a large database is called data mining or Knowledge Discovery in Database or usually shortened as KDD . One of the most popular algorithm in data mining technic is Apriori Algorithm, while the discovery of “relational combination pattern among itemset used Association Rules”. Data mining has been implemented into the various fields like : business or trade, education and telecommunication. In business for instance, the implementation result of data mining use ‘algorithm Apriori which can give a hand to help the Businessmen make decision on supplies. For example, the necessity of supplies system in a drugstore as one of the medical stuff supplier, and to determine which product as the priority should be supplied to anticipate out of stock of supplies availability in the store, as the results will also affect to the consumer service and daily income. Medical tools are essential unit should be supplied and being and essential factor which will impact to the consumer trust to a hospital or another medical service. That is why the availability of medical tools in drugstores is completely needed to support the success of distribution to the consumers, so the activity of medical service to consumers run thoroughly. In this case, data mining is seen as able to built intelligent business environment as solution for competing increated competition among the drugstores in future.