Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal Julia Jurnal
andri triyono
unan
Computer Science & IT

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

Found 2 Documents
Search

 1 
EARLY DETECTION OF DIABETES MELLITUS USING RANDOM FOREST ALGORITHM andri triyono; Rahmawan Bagus Trianto; Dhika Malita Puspita Arum
Julia: Jurnal Ilmu Komputer An Nuur Vol. 1 No. 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Diabetes mellitus is a deadly disease. Patients with this disease often do not realize that they are improving their diabetes mellitus. It is necessary to do early prevention in order to reduce the sudden death rate of people with diabetes mellitus. In addition, during the COVID-19 pandemic, which increases the risk of death for people with comorbid diabetes mellitus. A system model for the prediction of diabetes mellitus is needed for early diagnosis of this disease. By using machine learning techniques using the Random Forest algorithm and Information Gain can be used to predict diabetes mellitus. This model has a fairly high level of accuracy, which is 98.27%, precision is 97.69% and recall is 98%.   Keywords: Diabetes Mellitus; Random Forest; Information Gain; Machine Learning
PENGGUNAAN ALGORITMA FP-GROWTH UNTUK MENENTUKAN PAKET PENJUALAN PADA TOKO PERLENGKAPAN KONVEKSI SRI BUSANA andri triyono; Rahmawan Bagus Trianto; Dhika Malita
Julia: Jurnal Ilmu Komputer An Nuur Vol. 2 No. 02 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Consumers of the Sri Busana convection shop are mostly tailors, both home and convection tailors, which are pretty large, especially in Grobogan district. The increasing number of fashion businesses or tailors in Grobogan district makes data on goods and sales at the sri busana convection shop increase because the sri busana convection shop always strives to meet the needs of tailors or home convection. In overcoming the problem of finding more efficient consumer patterns, an analysis of buying patterns is carried out. Consumer buying patterns were analyzed using Association rules and FP-Growth methods. With this algorithm, the process of determining consumer purchasing patterns consists of 2 product combinations with a support value of 50% and a confidence value of 100%. 3 product combinations with a support value of 40% and a confidence value of 80%. 4 product combinations with a support value of 40% and a confidence value of 80%.
Co-Authors Arum, Dhika Malita Puspita Dhika Malita Rahmawan Bagus Trianto