Search

Monitoring and evaluation (Monev) are critical to determining whether the plan has been implemented and learning for future policies and planning. In education, the information obtained from monitoring and evaluation results is beneficial and will help improve existing processes sustainably. Implementation of monitoring and evaluation using printed manual documents requires time in processing the monitoring and evaluation results, giving rise to a tendency to spend much time in the implementation process. At the same time, there are essential things to do next, namely, evaluation and follow-up of the monitoring and evaluation process. An integrated solution is needed to implement monitoring, evaluation, and reporting so that the monitoring and evaluation process can be emphasized on assessment and follow-up, not monitoring. This research aims to design a prototype e-monev application using a web platform. This system is intended to be used to monitor and evaluate lectures. E-Monev was developed using an Agile and Collaborative Model Driven Development (AC-MDD). AC-MDD helps teams identify and manage interactions between business processes, domains, software, and creative design in Web engineering projects. UML was chosen in the E-Monev system design modeling. UML was expected to assist the team in communicating, designing, and validating software architectural designs. Agile Modeling with UML can be modeling the E-Monev system by adopting changes that may arise due to policy or rule changes.

Short-range, wireless communications in the vicinity of, or inside, a human body (but not limited to humans) are specified in this standard. It uses existing industrial scientific medical (ISM) bands as well as frequency bands approved by national medical and/or regulatory authorities. These sensors provide accurate and reliable information about the situation or activity occurring at any time. This high responsiveness of these sensors has made lives easy and safe. This article will perform an investigation on the WBAN's application for motion detection based on android smartwatch. The main problem is how to the sensors that attached on the human body can send of data via Bluetooth and read the motion and orientation of the body and display in the graph form. However, if the sensors do not match, the result of output display inappropriate. This article proposed method by using accelerometer and gyroscope sensors which are integrated with smartwatch to overcome the main problem. This application will display results in the form of numeric values and then convert in graph form. These results have proven that WBAN's application for motion sensing can be used for detection of motion and orientation via Bluetooth based on android smartwatch.