Last modified: 2018-07-07
Abstract
Human Immunodeficiency Virus (HIV) is a virus that attacks the human immune and then causes ability of the body vulnerable to infection. Treatment of the HIV-AIDS disease has not been able to be completely cures this disease. Several factors assumed to affect a patient's clinical picture of HIV-AIDS are predisposing factors, enabling factors and strengthening factors. This study involved many variables and indicators collected from the population with various characteristics, thus making the data become heterogeneity. Some literature suggests that PATHMOX produces a segmentation tree that has a similar structure to a binary decision tree. The purpose of the research is to investigate segmentation variables of the structural equation of the patient’s clinical picture of HIV-AIDS by using PATHMOX-PLS (Path Modeling Segmentation Partial Least Square). Secondary data were gathered and derived from the medical records of 150 patients with HIV-AIDS at the health centers of the Pasuruan Regency in 2017. Due to the free assumption and more flexible for any scale data, the PATHMOX-PLS was applied in explaining the relationship between variables and in grouping that variables.
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Figure 1. PATHMOX Tree Clinical HIV-AIDS
The results showed that the predisposing factors, enabling factors and strengthening factors influenced the clinical picture of HIV/AIDS patients. Based on the grouping analysis using PATHMOX-PLS, the clinical picture of the HIV/AIDS patient was grouped by the segmentation variables i.e. gender (male and female) and patient’s education levels. First split the resulting significant with p-value segmentation used 0.0032 and second split the resulting significant with p-value segmentation used 0.0006. Therefore, those two variables generated heterogeneity in the clinical picture of HIV/AIDS patients at the Pasuruan regency. So it can be conclude the clinical picture of HIV/AIDS patients can be modeled using PATHMOX-PLS and it easier to take a large patient base into smaller, more specific segments according to their similarities. We recommend to the government to pay attention for the factors that have effect on the clinical picture of the HIV/AIDS' patient.