Application of The K-Nearest Neighbor Ensemble Method in Predicting The Human Development Index and Its Relationship with The Unemployment Rate in Central Sulawesi Province

Unemployment has an impact on economic development and also community welfare. One of the indicators to measure the level of development is the Human Development Index (HDI). Therefore, the purpose of this research is to obtain the results of HDI prediction and the relationship with the unemployment rate. The method used in this study is the K-NN Ensemble method. This research was conducted using HDI data consisting of data on school life expectancy, per capita expenditure, average school duration, and life expectancy as well as unemployment rate data. The results of the HDI prediction in Central Sulawesi Province are with an average of 69.03 with a MAPE value of 1.45%. Based on the correlation test, it was found that the relationship between HDI and the unemployment rate with a significant value below 0.05 was 0.001. The resulting correlation value is 0.803 which shows that the closeness is very strong and has a negative correlation coefficient property.

Authors

Institutions

Publication Details

Journal
˜The œjournal of academic science.
Published
2024-12-18
DOI
https://doi.org/10.59613/w1ebc495
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

Application of The K-Nearest Neighbor Ensemble Method in Predicting The Human Development Index and Its Relationship with The Unemployment Rate in Central Sulawesi Province

Selvy Musdalifah, Andri Andri, Saputra Hardiansyah
˜The œjournal of academic science.
Data Mining and Machine Learning Applications
article

Application of The K-Nearest Neighbor Ensemble Method in Predicting The Human Development Index and Its Relationship with The Unemployment Rate in Central Sulawesi Province

Selvy Musdalifah, Andri Andri, Saputra Hardiansyah
article en

Abstract

Unemployment has an impact on economic development and also community welfare. One of the indicators to measure the level of development is the Human Development Index (HDI). Therefore, the purpose of this research is to obtain the results of HDI prediction and the relationship with the unemployment rate. The method used in this study is the K-NN Ensemble method. This research was conducted using HDI data consisting of data on school life expectancy, per capita expenditure, average school duration, and life expectancy as well as unemployment rate data. The results of the HDI prediction in Central Sulawesi Province are with an average of 69.03 with a MAPE value of 1.45%. Based on the correlation test, it was found that the relationship between HDI and the unemployment rate with a significant value below 0.05 was 0.001. The resulting correlation value is 0.803 which shows that the closeness is very strong and has a negative correlation coefficient property.

˜The œjournal of academic science.Vol. 1(8)
Tadulako University (ID)
Openalex Percentile: Top 56%
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.

Application of The K-Nearest Neighbor Ensemble Method in Predicting The Human Development Index and Its Relationship with The Unemployment Rate in Central Sulawesi Province — Selvy Musdalifah, Andri Andri, et al. · ˜The œjournal of academic science. (2024) | TGRS Research Map | TGRS