Measurement of student motivation in learning mathematics using a human face expression detector
Suprih Widodo- Erna Suwangsih- Srie Mulyani- Hudzaifi Syah Tsalits Taufiqi

Universitas Pendidikan Indonesia

Abstract

Motivation will have an impact on student learning outcomes, either directly or indirectly. Every student has a goal in his activity, so he will have a strong motivation to achieve it. The purpose of this study is to find out students^ learning motivation in photovoices for learning mathematics ^funtastic^ using a human face expression detector and to find out the accuracy of measuring motivation shown by students in photovoices for learning mathematics ^funtastic^ using a human face expression detector. The results of the research show that it produces a series of processes that start from collecting frames in the form of images, which then go through a careful selection process, filtering until the remaining 412 relevant photos are left. After that, the next step involves using the FaceAnalyzer app to identify facial expressions in each photo. The collected data is then processed using the Microsoft Excel application, where the process of recapitulation and analysis is carried out. From this analysis, the average facial expression is calculated in each frame recorded in the photographs. students tend to show neutral expressions during learning activities and produce out of a total of 110 frames analyzed, only 5 frames show an inaccurate level of accuracy, while 105 other frames show accurate results. It is important to note that these results reflect the high quality of the FaceAnalyzer application used in this study. The 95,5% accuracy rate achieved by the application provides a strong indication of reliable and reliable performance in detecting and measuring student facial expressions

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Topic: Mathematic Education