Diagnosa Tingkat Kolesterol Pada Remaja Menggunakan Metode Dempster Shafer

Teenagers are the age group from 10 years to before the age of 23 years. Adolescent health efforts aim to prepare adolescents to become healthy, intelligent, qualified and productive adults who play a role in maintaining, maintaining and improving their own health. In its grouping, cholesterol is included in the steroid group, which is a type of lipid that is not connected and is a fatty substance that has the property of not dissolving in the blood, which in the transportation process requires the help of protein to form particles which are usually called lipoproteins. Lipoprotein itself has several types, including LDL (low density lipoprotein), HDL (high density lipoprotein), triglycerides and total cholesterol. Dempster Shafer is the Dempster Shafer Method, also known as belief function theory. This method uses Belief, which is a measure of the strength of evidence in supporting a set of propositions. If the value is 0 (zero), it indicates that there is no evidence, and if the value is 1, it indicates that there is certainty. Based on the weight values ​​given by experts for each data on symptoms of cholesterol disease in adolescents, from the results of the analysis carried out in the previous chapter, the results of the diagnosis of cholesterol disease in adolescents were obtained, namely Low Density Lipoprotein (LDL) disease with a density value of 73.81%.

Authors

Institutions

Publication Details

Journal
JURNAL PENELITIAN SISTEM INFORMASI (JPSI)
Published
2024-09-20
DOI
https://doi.org/10.54066/jpsi.v2i4.2452
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnosa Tingkat Kolesterol Pada Remaja Menggunakan Metode Dempster Shafer

Magdalena Simanjuntak, Siswan Syahputra, Pujiani Pujiani
JURNAL PENELITIAN SISTEM INFORMASI (JPSI)
Data Mining and Machine Learning Applications
article

Diagnosa Tingkat Kolesterol Pada Remaja Menggunakan Metode Dempster Shafer

Magdalena Simanjuntak, Siswan Syahputra, Pujiani Pujiani
article en

Abstract

Teenagers are the age group from 10 years to before the age of 23 years. Adolescent health efforts aim to prepare adolescents to become healthy, intelligent, qualified and productive adults who play a role in maintaining, maintaining and improving their own health. In its grouping, cholesterol is included in the steroid group, which is a type of lipid that is not connected and is a fatty substance that has the property of not dissolving in the blood, which in the transportation process requires the help of protein to form particles which are usually called lipoproteins. Lipoprotein itself has several types, including LDL (low density lipoprotein), HDL (high density lipoprotein), triglycerides and total cholesterol. Dempster Shafer is the Dempster Shafer Method, also known as belief function theory. This method uses Belief, which is a measure of the strength of evidence in supporting a set of propositions. If the value is 0 (zero), it indicates that there is no evidence, and if the value is 1, it indicates that there is certainty. Based on the weight values ​​given by experts for each data on symptoms of cholesterol disease in adolescents, from the results of the analysis carried out in the previous chapter, the results of the diagnosis of cholesterol disease in adolescents were obtained, namely Low Density Lipoprotein (LDL) disease with a density value of 73.81%.

JURNAL PENELITIAN SISTEM INFORMASI (JPSI)Vol. 2(4)
Kootenay Association for Science & Technology (CA)
Openalex Percentile: Top 67%
Data Mining and Machine Learning Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.