Early detection of radicalism, extremism, and terrorism is still not optimal. The reason is because of the limitations of the task force and prevention forums in involving the community. Several studies show that community participation is needed in the early detection. Strengthening community participation will be better by empowering organizations that are close to the community such as RT and RW. Therefore, this paper discusses the role of RT and RW in the early detection of radicalism, extremism, and terrorism including identifying the efforts that need to be made to optimize them. The method applied in this paper is library research with data and information sources from several books, journals, documentation, and legal products. The author analyzes data and information by reducing data, classifying data and processing data qualitatively. The results of the study show that RT and RW have an important role in the early detection of radicalism, extremism, and terrorism. Optimizing the empowerment of RT and RW in increasing early detection of radicalism, extremism, and terrorism is much more effective and efficient than prevention forums or task forces which are all temporary. Optimization of empowerment is achieved by improving the quality of several factors which include facilities and infrastructure, budget, human resources, and more productive work mechanisms.
Background: The prevalence of low birth weight (LBW) in the world (20%) and in Indonesia is still high (12.4%). The importance of efforts to reduce the incidence of LBW is written in the global nutrition targets for 2025. Methods: The study design in this study was quantitative using the data set 'Indonesian Demographic and Health Survey (IDHS) of 2017. The samples included in the research process were 13,269 samples with probability proportional to size (PPS) sampling technique. The research instrument was based on a modified DHS VII questionnaire. Data were analyzed by chi-square test, binary logistic regression, and Receiver Operating Characteristics (ROC). Results: The prevalence of LBW in Indonesia is 7% [95% CI: 6.6, 7.5]. The final model for determining low birth weight after controlling for confounding was gemelli P<0.001 [OR: 22,428; 95% CI: 14,145, 35,561], history of pregnancy complications P<0.001 [OR: 1,906; 95% CI: 1.569, 2.315], education level P=0.002 [OR: 1.581; 95% CI: 1.180, 2.117], economic status P<0.001 [OR: 1.509; 95% CI: 1.225, 1.859], and gestational interval P=0.016 [OR: 1.401; 95% CI: 1,066, 1,842]. The minimum probability of the prediction model is 2.8%-80.5% [AUC = 0.638; Sensitivity = 0.074; Specificity = 0.996]. Conclusion: Diagnostic performance with ROC evaluation on a predictive model of LBW determinant has very high specificity power. Mothers with gemelli status need to be the focus to reduce the risk of low birth weight.
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