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All Journal Jurnal Komtika (Komputasi dan Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) IJIIS: International Journal of Informatics and Information Systems Madaniya Community Empowerment Journal of Applied Data Sciences Jurnal Komtika (Komputasi dan Informatika)
Meidar Hadi Avizenna
Universitas Muhammadiyah Magelang, Indonesia
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences

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Journal : Journal of Applied Data Sciences

 1 
Data Mining Predicts the Need for Immunization Vaccines Using the Naive Bayes Method Widyanto, R Arri; Avizenna, Meidar Hadi; Prabowo, Nugroho Agung; Alfata, Kemal; Ismanto, Agus
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.
Implementation of Apriori Data Mining Algorithm on Medical Device Inventory System Avizenna, Meidar Hadi; Widyanto, R Arri; Wirawan, Dwi Kusuma; Pratama, Teguh Adhi; Nabila, Amandha Shafa
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.v2i3.35

Abstract

The pattern of the need for drugs and medical devices in various hospitals has a tendency to be repeated and similar in a relatively long period of time, especially in one particular department, because the cases found are often similar or even similar. Ensuring the availability of stock in each departmental depot is very vital, because the procurement of medical devices must go through a certain process and time, so that cases of critical rheumatism often occur but the equipment needed at depositors does not meet the standards. need or run from inventory and must indent first. By calculating the trend of demand patterns and needs using an algorithm (Apriori Association) in the dataset, a rule is formed that in the pattern of dependence between itemsets that have supporting criteria in the form of 33.3% support and 85% Confidence, where the items that appear are items with frequency of occurrence and associations so that it can be taken into consideration to ensure the availability of drugs and medical devices.
Applying the Apriori Algorithm to Analyze and Optimize Medical Device Inventory Management Avizenna, Meidar Hadi
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.
Co-Authors Agus Ismanto Alfata, Kemal Andi Widiyanto Andi Widiyanto Ardhin Primadewi Bambang Pujiarto Bambang Pujiarto Bambang Pujiarto Bambang Pujiarto Eko Muh Widodo Maimunah, Maimunah Muhammad Resa Arif Yudianto Mukhtar Hanafi Mukhtar Hanafi Mukhtar Hanafi Nabila, Amandha Shafa Nugroho Agung Prabowo Nugroho Agung Prabowo Pratama, Teguh Adhi Purwono Hendradi R Arri Widyanto Shodiq, Umar Tuessi Ari Purnomo Wirawan, Dwi Kusuma