Reducing maternal mortality rate is a key concern of health promotion in developing countries or city face. The investigated and survey for maternal mortality had been done in Dairy City. There are 149 samples got from the survey directly in this area for 2017. In this study, we use a machine learning approach to train and test the data of maternal mortality. The aim of this study to classification maternal mortality in health promotion for reducing the maternal mortality rate in Dairi. The result of this study indicated the decision tree and Naïve Bayes are available to train and test the dataset. The accuracy of the decision tree of maternal mortality is 100 % and the Naïve Bayes model indicates 97.37 % of maternal mortality.

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Objective: This study explores the impact of social media on family who live with mentally disordered members in rural areas of Ponorogo, East Java Province. Various efforts have been made to determine whether or not social media can help families in rural areas deal with serious stress because of living with their mentally disordered members. Method: This study involves 160 members with mental disorder and their family. Stress is measured based on Lazarus and Folkman theory. Data are analyzed using the Sperman test with SPSS software. Results: Using Beck criteria, it was found that 60% (N = 160) of families feel stressed. Interestingly, there was a significance difference of stress experienced by the social media users and non-social media users (p value= 0.002). There are 31.3% of social media users who are less stressed while 68.7% non-social media users felt more stressed. Conclusion: This study verifies the stress experienced by familes who live with mentally disordered members. It can be concluded that the families who use social media are less stressed even though they live with mentally disordered members. It means social media can prevent stress. In addition, it is recommended that counseling and psychological training should be designed by considering participants’ gender and level of education.

Aim: This study aims to determine the effect of health services on coping mechanisms of families with schizophrenia. Methode: The sample consisted of 260 family carers of individuals with schizophrenia in Ponorogo, East Java, Indonesia. Caregivers of families completed filling in the service factor questionnaire and coping mechanism questionnaire. Results: Community Value for Service Factor 0.662 and Family Coping 0.670 which means valid and strong. Community Value for Service Factor 0.853 and Family Coping 0.800 means Reliability. T-Statistics value of 0.205, which means there is an influence between service factors on family coping. Conclusiaon: Research on improving health services for coping mechanisms in family members of individuals with schizophrenia will help design interventions to improve coping mechanisms.