Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Medula Journal of Computer, Electronic, and Telecommunication (COMPLETE)
Muhammad Rifki Pratama
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Medicine & Pharmacology Neuroscience Public Health

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Hubungan Tahap Pengobatan dengan Kualitas Hidup Pasien Multidrug-resistant Tuberculosis di RSUD Dr. H. Abdul Moeloek Provinsi Lampung Muhammad Rifki Pratama; Asep Sukohar; Khairun Nisa Berawi
Medula Vol 10 No 1 (2020): Medula
Publisher : CV. Jasa Sukses Abadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53089/medula.v10i1.48

Abstract

Tuberculosis (TB) is the number one infectious disease in the world as the most frequent cause of death. TB infects 10 million people each year and becomes the 10th highest cause of death in the world.Multidrug-resistant Tuberculosis (MDR-TB) is a type of TB germ resistance against at least two first-line anti-tuberculosis (OAT) drugs. MDR-TB treatment certainly takes longer than 18 months. This very long treatment can affect the quality of life of MDR-TB patients. This study is to determine the correlation between the treatment phases with the quality of life of patients with Multidrug-resistant Tuberculosis in Dr. H. Abdul Moeloek Hospital Lampung Province. This study used 68 respondents who had been diagnosed with MDR-TB by pulmonary specialists. Primary data was taken using SF-36 questionnaire to measure the quality of life of MDR-TB patients, then secondary data based on the treatment phases using the medical record of the patient who had filled out the questionnaire. The data is processed and analyzed by the program in the computer. Data were tested by chi-square test and the results were obtained from 30 respondents in the initial treatment phases, 22 people (73.3%) quality of life was poor and 8 people had good quality of life (26.7%), while from 38 respondents at the continued treatment phases, as many as 12 people (31.6%) quality of life is bad and 26 people have good quality of life (68.4%). The result of bivariate analysis showed the variable had a correlation with p-value=0,001. There is a correlation between the treatment phases with the quality of life of patients with Multidrug-resistant Tuberculosis in RSUD Dr. H. Abdul Moeloek.
Pengenalan Gestur Jari Tangan Sebagai Media Pembelajaran Berhitung Bagi PAUD Berbasis Visi Komputer dan Deep Learning: Pengenalan Gestur Jari Tangan BerbasisVis i Komputer Dan Deep Learning Heri Pratikno; Muhammad Rifki Pratama; Yosefine Triwidyastuti; Musayyanah
Journal of Computer, Electronic, and Telecommunication (COMPLETE) Vol. 4 No. 1 (2023): July
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v4i1.355

Abstract

Pendidikan anak usia dini (PAUD) merupakan periode perkembangan yang penting dalam kehidupan anak, salah satu pertumbuhan yang penting adalah aspek kognitif. Berhitung termasuk dalam kemampuan kognitif yang meliputi kemampuan menghafal, memahami, mengaplikasi, menganalisis, mensintesis, dan kemampuan mengevaluasi. Guna meningkatkan kemampuan berhitung bagi anak-anak maka harus diketahui bagaimana cara mengaplikasikan hitungan tersebut dalam dunia nyata. Pada penelitian ini memberikan solusi bagaimana cara belajar berhitung yang menyenangkan serta tidak membosankan bagi anak-anak menggunakan media pembelajaran berhitung yang interaktif melalui pengenalan bentuk gestur jari-jari kedua tangan berbasis visi komputer dan deep learning secara realtime. Adapun visi komputer pada penelitian ini menggunakan framework MediaPipe, sedangkan metode deep learning yang digunakan adalah arsitektur Convolutional Neural Network (CNN). Hasil pengujian yang telah dilakukan pada penelitian ini, akurasi deteksi kesepuluh jari tangan untuk proses berhitung dari metode MediaPipe sebesar 89,9% dengan frame per second-nya antara 20-25 FPS. Metode CNN persentase akurasi deteksinya 20% dengan nilai FPS-nya antara 10-12 FPS, manfaat dari hasil penelitian ini bisa memberikan pengalaman belajar yang menyenangkan, menstimulasi, dan mendukung perkembangan anak secara holistik.
Co-Authors Asep Sukohar Heri Pratikno Khairun Nisa Musayyanah Yosefine Triwidyastuti