Baby incubators are used for premature babies where babies are born prematurely. To ensure the accuracy of medical devices, periodic tests and controls need to be carried out aimed at reducing the risk of measurement. The baby incubator can be tested with a calibration device which is a device to calibrate temperature, noise, humidity, and airflow so that conditions remain stable and within normal limits. The purpose of this study was the development of a PC (Personal Computer) performing Incubator Analyzer with noise and airflow parameters. This type of research uses after only design. The standard incubator analyzer is not equipped with a PC and data processing via Excel, so the researchers created an Incubator Analyzer device that has four parameters to measure temperature, noise, humidity, and airflow. Using the Atmega328 Microcontroller as a data processor, equipped with sending data via Bluetooth HC-05 with data storage and output results will be displayed on a PC. Noise parameters using the Analog Sound Sensor V2 sensor and have the biggest error at 37oC setting temperature that is equal to 0.17%. While the airflow parameter uses an airflow sensor with type D6F-V3A01 and has the biggest error that is 0.5% at a temperature setting of 36oC and 37oC. The use of displays on personal computers and data processing using Excel, allows users to monitor calibration and data processing. The feasibility of this device is proven. Therefire, this design can be used for baby incubator calibration.

Purpose This study aimed to determine the effect of the implementation of the antenatal class toward exclusive breastfeeding.Methods The research was a case-control study with a quantitative approach. This research was also supported by a qualitative approach which aimed to complement and reinforce the results obtained from the quantitative data. Sample cases were 135 exclusive breastfeeding infants aged 6-12 months, and the control sample were 135 not exclusive breastfeeding infants aged 6-12 month. Data analysis used the McNemar and conditional logistic regression tests with significance level of p = <0.05 and 95% confidence interval.Results Bivariate analysis showed that antenatal class affected exclusive breastfeeding p = 0.026 and OR = 1.80 (95% CI: 1.03 to 3.24). In the results of multivariate analysis after controlling by including support of her husband and the ANC p = 0.03 and OR = 1.86 (95% CI: 1.05 to 3.30). Mothers who attended antenatal class have exclusive breastfeeding rate 1.86 times higher compared to mothers who did not attend the antenatal class.Conclusion The antenatal class can directly affect exclusive breastfeeding, in spite of controlling the support of her husband and the ANC.

Opening and closing an infant incubator during calibration can cause temperature leaks such as a decrease in the incubator temperature. The purpose of this study is to make the tool "Development Incubator Analyzer appear PC and Non-PC with Temperature and Humidity parameters" with Bluetooth HC05 delivery for Personal Computer display in the form of numbers and temperature graphs. Whereas for non-PCs displayed on a 20x4 LCD with SD Card storage. The contribution of this research is to be able to calibrate baby incubators without a decrease in temperature and monitoring data collection at a maximum distance of 10 meters. To avoid a decrease in temperature, the module is displayed on the Personal Computer and storage on the SD Card. Incubator Analyzer is designed to simplify and facilitate calibration with temperature parameters at 5 points using a DS18B20 sensor, mat temperature using a K type thermocouple and humidity using a DHT22 sensor. In the temperature setting of 34 C and 36 C, the average error result is -4.87% for DS18B20, -7.39% error for mattress temperature, and -24.80% for humidity sensor. Data generated from comparisons using the INCU II test conclude that the measurement results between modules and standard devices have large differences in values. The results of this study can be implemented on baby incubators to increase the appropriateness of the device.

The price of electrocardiograph (ECG) machine on the market is very high. Currently, the technology used is still very complicated and ineffective, and the ECG machine cannot be connected to other devices. A new development of a low-cost ECG machine with a customized design was needed to integrate the machine with other devices. Therefore, the purpose of this study is to develop a low-cost ECG machine which can be connected to other devices and equipped with sensitivity and paper speed setting. So that portable ECG machines can be produced and used at small clinics in the society. In this study, the main controller of the 12 channels ECG machines was supported by ATMEGA16 microcontroller, that is available on the market at low prices. The main part of the ECG amplifier is built using a high common mode rejection ratio (CMRR) instrumentation amplifier (AD620) and a bandpass filter which the cutoff frequency for highpass filter and lowpass filter are 0.05 Hz and 100 Hz, respectively. In order to complement the previous study, some features were introduced such as selectivity and motor speed option. In this study, 10 participants are involved for data acquisition,and an ECG phantom was used to calibrate the machine. The performance of the ECG machine was evaluated using standard measurement namely relative percentage error (% error) and uncertainty (UA). The result shows that %error from all of the feature is less than 2% and the UA is 0.0 which shows that the ECG machine is feasible for diagnostic purposes.

Body temperature and heart rate monitoring based on telemedicine is an electromedical device served to determine the condition of the heart rate per minute (BPM) and the patient’s body temperature in realtime remotely. The purpose of this study is to design the heart rate and body temperature monitor based on telemedicine uses the Internet of Things (IoT). The system allows unlimited distance monitoring by utilizing the internet as a medium for sending the data. The body temperature and heart rate monitoring system uses DS18B20, Arduino, and Raspberry Pi temperature sensors and finger sensors as data processing and transmission microprocessors, LCD Character displays the results of heart rate readings and body temperature per minute. The results of heart rate measurements and body temperature are sent to the database via microservice and displayed on a web page in the form of numerical data and responsive plot graphics on desktops and mobile phones. Based on the measurement and comparison to standard apparatus, the average error of BPM measurement is 0.72%, with a maximum permissible tolerance of ± 5%. While in the body temperature parameter the average difference is 0.3 ° C with a maximum permitted tolerance of ± 1 °C.