by Moh. Ladrang Pramushinto Paramanindhito and Co-authors. This article has been retracted at the request of the Editors as a result of (1) The authors are in the process of making changes to the study and awaiting final results.(2) The changes will be published later as different article, with justification for modification.

Birth weight serves as an indicator of a newborn’s health status. It is associated with mortality rate in the first year, developmental problems in childhood and risk of various diseases in adulthood. Even in modern era, it continues to be a health concern globally, especially in developing countries. In Indonesia, the prevalence of low birth weight has increased from 2013 to 2018, swaying further from the national target. Low birth weight is often caused by insufficient nutrients supplied by the mother to the fetus. In Indonesia, chronic energy deficiency status is diagnosed in the first antenatal care visit by measuring maternal middle-upper arm circumference with a cut-off point of 23.5cm. Meanwhile, iron level is measured via assessing hemoglobin level will be measured in the first antenatal care visit and in trimester III. This study aims to describe the factors that may influence neonatal birth weight. It is a quantitative study with a cross sectional approach conducted at Sidotopo Wetan Public Health Centre. 97 samples are collected from medical records and analysed using bivariate correlative test. Result shows that maternal age (0.20), chronic energy deficiency status (0.026) and antenatal care visit minimal of 4 times (0.49) increase the risk of low-birth-weight incidence. On the other hand, educational level, maternal parity and anemia status does not acts as risks. In conclusion, maternal age, energy status and visits to antenatal care acts as risk factors in causing low birth weight.

Introduction: Pandemic COVID-19 has led people to a new norm of spending most of their time at home. Regular direct physical social interactions become less common and replaced by interacting using social media. Method: This is study is a descriptive survey, describing society’s knowledge on the management of social media usage in COVID-19 Pandemic. 666 samples were gathered who met the inclusion and exclusion criteria. Google Form was spread amongst webinar participants, processed and distributed into tables, including average score based on age groups. Results: Majority of the participants (69.5%) achieved a score between 5-6 out of 7 questions that were given. Whilst, 0 participants received scores between 0 to 1. Results achieved by all age groups are almost similar, with age 36-40 appearing on top. Conclusion: Knowledge regarding social media usage management does not appear to be affected by the person’s age. This is because social media has been used by people of all ages, hence have almost similar knowledge regarding its usage.

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