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All Journal Journal of Informatics, Electrical and Electronics Engineering Bulletin of Artificial Intelligence
Manik, Lastri
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Implementasi Metode MAUT Dalam Pemilihan Aplikasi Pembuatan Media Pembelajaran Dimasa Pandemi Covid 19 Pradana, Ari; Manik, Lastri; Syahrizal, Muhammad
Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 1 (2023): September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v3i1.1609

Abstract

Corona Virus disiase 2019 (covid 19) is an infectious disease caused by SARS-CoV-2 a type of Corona virus. This virus is transmitted through physical contact and causes symptoms of respiratory problems, colds, fever, dry cough, and attacks the human physical immunity. covid 19 has disrupted the activities of daily human life, including in the field of education. To prevent the spread of covid 19 the government proposes that during the covid 19 pandemic the teaching and learning process takes place online or online. In the online learning process so that students are more active, creative and enthusiastic, a system is needed decision support that can determine and choose the application of learning media during the covid 19 pandemic, a decision support system that can solve the problem using the MAUT (Multi Attribute Utility Theory) method and produce an appropriate decision based on the results of the data obtained such as alternatives and the criteria so as to produce a decision, namely the application of the best learning media in the era of covid 19, namely the Sony Vegas Pro application with a score of 0.9025.
Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit Otitis Eksterna Manik, Lastri; Saragi, Naomi Labora; Utomo, Dito Putro
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.138

Abstract

Otitis externa is a common ear problem that often requires an accurate diagnosis for effective treatment. The Certainty Factor Method is an artificial intelligence approach used to support the diagnostic process. This research aims to apply the Certainty Factor Method in diagnosing otitis externa. Patient data, including symptoms, medical history, and examination results, are used to build a knowledge base that is then utilized in the diagnostic process. This method allows for improved accuracy in determining diagnoses by considering the confidence level associated with each symptom and examination result. Experimental results show that the application of the Certainty Factor Method can assist doctors in diagnosing otitis externa with higher accuracy compared to conventional methods. With this approach, diagnoses are made with higher confidence levels, which can aid in providing accurate and prompt treatment for patients suffering from otitis externa. The Certainty Factor Method has the potential for use in other medical contexts and can make a positive contribution to problem-solving in the healthcare field. This research underscores the importance of technology in supporting ear disease diagnosis and providing more reliable solutions for managing otitis externa. By leveraging the Certainty Factor approach, doctors can be more efficient and effective in responding to patients' conditions, thus reducing the risk of complications and enhancing healthcare quality. Therefore, this study offers a valuable contribution to the fields of medicine and computer science in improving the diagnosis of ear diseases, such as otitis externa, so that patients can receive better and faster care.
Co-Authors Muhammad Syahrizal Pradana, Ari Saragi, Naomi Labora