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Journal : JAMBURA JOURNAL OF PROBABILITY AND STATISTICS

Implementasi Algoritma Random Forest dengan Forward Selection untuk Klasifikasi Indeks Pembangunan Manusia Posangi, Tiara; Yahya, Lailany; Wungguli, Djihad
Jambura Journal of Probability and Statistics Vol 4, No 2 (2023): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v4i2.18460

Abstract

Development is essentially a process of continuous change carried out to achieve better living condition. So that the benchmark for the success of a development is seen in its human development. 3 The basic dimensions that form human development are long and healthy life, knowledge, and a decent life. The indicators that represent the three dimensions are summarized in a single value, namely the Human Development Index (IPM). In 2021 the HDI figure in Indonesia is 72.29, which means it is high. However, due to the diverse geographical location of regions in Indonesia, this also influences the HDI rate in each region in Indonesia, so this study uses the Random Forest Algorithm to obtain accurate results from the HDI classification and uses Forward Selection to determine features that influence the classification. The results of the study show that the features that influence the classification are per capita spending, expected length of schooling, life expectancy, and average length of schooling, and get a final accuracy of 80%.
Model Regresi Multilevel Negative Binomial Pada Kasus Kronis Filariasis di Indonesia Usman, Rizal; Nasib, Salmun K.; Wungguli, Djihad; Abdussamad, Siti Nurmardia
Jambura Journal of Probability and Statistics Vol 6, No 2 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i2.31648

Abstract

Filariasis is a contagious disease caused by infection with the parasitic worm Filaria and transmitted through the bite of an infected mosquito. Analysis of the number of chronic filariasis cases in Indonesia often faces statistical problems in the form of overdispersion and excess zero. To overcome this, a Multilevel Negative Binomial Regression model is used which is able to handle data variance that is greater than the average as well as the number of zero values in the data. The results showed that the model was effective in overcoming overdispersion and excess zero problems. Based on the parameter significance test using the Wald test, environmental variables such as the presence of unprotected wells (X4) and household proximity to waste storage (X5) have a significant effect on the number of chronic filariasis cases. In contrast, socioeconomic variables such as percentage of male population (X1), productive age population (X2), proper sanitation (X3), percentage of poor population (X6), and Human Development Index (X7) did not show a significant effect. These findings confirm that environmental factors play an important role in the spread of chronic filariasis cases in Indonesia.