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All Journal International Journal of Artificial Intelligence Research JPM (Jurnal Pemberdayaan Masyarakat) Jurnal Komtika (Komputasi dan Informatika) CARADDE: Jurnal Pengabdian Kepada Masyarakat GERVASI: Jurnal Pengabdian kepada Masyarakat Celebes Abdimas: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Building of Informatics, Technology and Science To Maega: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Kepada Masyarakat (Mediteg) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) IJIIS: International Journal of Informatics and Information Systems Madaniya Community Empowerment Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Prosiding University Research Colloquium Borobudur Informatics Review Jurnal Informatika: Jurnal Pengembangan IT Dedikasi Nusantara
R Arri Widyanto
Universitas Muhammadiyah Magelang, Indonesia
Religion Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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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.
Co-Authors Abdilah, Surya Abi Rafdi Ade Adams Ade Ragil Bintoro Adha, Amella Rayani Afri Listiyana Agus Ismanto Aisya, Ummatrisi Fadhia Alfata, Kemal Alfiantoro, Graha Alfina Khusni Rodiyatul Hidayati Amalia, Arina Amiroh, Jihan Andaresti, Zahsa Okna Andi Triyanto Andi Widiyanto Anstryani, Ditya Ardhin Primadewi Arif Nur Hidayat Ayun, Shafira Qurrota Azizah, Husna Nur Bambang Andrean Bambang Pujiarto Bambang Pujiarto Bambang Pujiarto Bambang Pujiarto Cahyaningtyas, Fadilah Hasti Cendani, Vabian Drana Dimas Sasongko Dimas Sasongko Ditya Anstryani Dwi Setya Rini Dyan Ihza Mahendra Eki Dewangga Emilya Ully Artha Endah Ratna Arumi Fadzan Fahrurrosak Faridh Fajar Nugroho Faris Afandi Ferdiansyah, Rizki Ghani, Mohd Khanapi Abd Graha Alfiantoro Grahadian, Muhammad Handika Satya Putra Hapsari, Farah Sanda Helmi Naufal Muzaki Ika Hermeining Normawati Imam Agus Faisal Wardani Jaya, Dito Ananda Kasih, Ginanjar Prianggoro Lina Wahyu Listiyana, Afri Lugman Ismail Mahfuzah, S.N Meidar Hadi Avizenna Muhammad Jidan Narizki Muhammad Rafly Muhammad Resa Arif Yudianto Muhammad Riyan Mukhtar Hanafi Mukhtar Hanafi Mukhtar Hanafi Na'im, Lailia Jannatun Nabila, Amandha Shafa Naufal Gufron Nayunda Gunawan Saputri Nugroho Agung Prabowo Nugroho Agung Prabowo Nugroho Agung Prabowo Nurudin, Anwar Nurul Huda Nurul Huda Nuryanto - Octaviani, Dwi Pindiarta, Bagus Radar Dwi Prabowo, N Agung Pratama, Teguh Adhi Puji Agustina Purwono Hendradi Purwono Hendradi Putra, Handika Satya Putri Nur Amalina Putri, Nugrahani Rafly, Muhammad Rahadyan, Rayhan Vibi Rahmat Bastian, Deka Ramadhan, Gilang Satria Putra Ramadhani, Balgis Riski Ramadhani, Muhammad Wildan Ridho Rayhan Vibi Rahadyan Rida Nurachman Rizal Panji Binangkit Rohmat Sigit Ribowo Rosadi, Dony Rosna Dewi Larasati Saifudin Setiawan, Agus Setiya Nugroho Subagio, Riki Sunarni Sunarni Sunarni Sunarni Tri Anggoro Istianto Tuessi Ari Purnomo Uky Yudatama, Uky Wahyu Febriyanto Wibowo, Aldino Lutfi Arif Wirawan, Dwi Kusuma Wiryani, Frida Yahya, Ali Affandi