Estimation curve of multivariate adaptive biresponse fuzzy clustering means regression splines approach to stunting and wasting cases in Southeast Sulawesi.

This article offers a new method of clustering data. This method is constructed by combining the multivariate adaptive regression spline biresponse continuous model (MARSBC) with the fuzzy clustering means (FCM) approach, called the multivariate adaptive biresponse fuzzy clustering means regression splines (MABFCMRS) model. This method uses patterns obtained from the MARSBC model to separate data into specific groups.

Predictors of stunting, wasting, and being underweight in Indonesia: A literature review.

Parents often perceive that stunting, wasting, and being underweight in their children are solely influenced by nutritional intake. In reality, various factors contribute to these outcomes. The objective of this study was to identify the factors associated with stunting, wasting, and being underweight in Indonesia.

Comparing Life Expectancy Determinants Between Indonesia and Oman from 1980 to 2020.

Life expectancy (LE) is a health indicator of a population's health and well-being. Modeling the trajectory of LE aligns with the objectives of Indonesia's Vision 2045 and Oman's Vision 2040. This study examines the influence of health status-resources (HSR), macroeconomic (ME), and sociodemographic (SD) factors on LE in Indonesia and Oman.

Segmentation of stunting, wasting, and underweight in Southeast Sulawesi using geographically weighted multivariate Poisson regression.

The health profile of Southeast Sulawesi Province in 2021 shows that the prevalence of stunting is 11.69 %, wasting 5.89 % and underweight 7.

Segmentation of toddler nutritional status using REBUS and FIMIX partial least square in Southeast Sulawesi.

Nutrition is one of the important factors that play a major role in the growth and development of children so that they can develop optimally. Child malnutrition, such as stunting, underweight, and wasting, is a significant problem in Indonesia. The World Health Organization (WHO) determined that the nutritional status of children under five in Indonesia is in the chronic category, one of which is in Southeast Sulawesi Province.

Determination of the best multivariate adaptive geographically weighted generalized Poisson regression splines model employing generalized cross-validation in dengue fever cases.

This article constructs a new model based on multivariate adaptive generalized Poisson regression splines (MAGPRS) and geographically weighted generalized Poisson regression (GWGPR), which is known as multivariate adaptive geographically weighted generalized Poisson regression splines (MAGWGPRS). The article elaborates the steps of weighted maximum likelihood estimation (weighted-MLE) to obtain the estimated values of its parameters. MAGWGPRS and MAGPRS were applied to the number of dengue hemorrhagic fever (DHF) cases in 119 districts or cities in Java, Indonesia, in 2020, to compare their performance.

Quality of life and subjective well-being modeling of pulmonary tuberculosis patients.

Unlabelled: psychosocial problems that cause stress, such as loss of hope, sleep disorders and interruption in period of rest. Therefore, this study aims to analyze the Quality of Life (QoL) and Subjective Well-Being (SWB) of pulmonary TB patients and the affecting factors.

Design And Methods: An analytical observational design with a cross sectional approach was used and a total of 73 respondents were randomly selected from 89 patients with pulmonary TB.

Corrigendum to "Propensity score stratification using bootstrap aggregating classification trees analysis" [Heliyon 6 (7) July 2020 e04288].

[This corrects the article DOI: 10.1016/j.heliyon.

Propensity score stratification using bootstrap aggregating classification trees analysis.

Introduction: Observational research in the field of health often does not conduct randomized controlled trials on research subjects. A non-random selection process on research subjects can result in a biased treatment effect due to an imbalance between the treatment and control groups.

Methods: The problem of bias effects can be dealt with by reducing the bias in the confounding variable using the propensity score method.