Perancangan Sistem Alarm Dan Monitoring Mahasiswa Selama Kelas Virtual Berbasis Ekspresi Wajah Dan Arah Pandangan Mata Menggunakan Jaringan Syaraf Tiruan

Nabila, Ratna Dian (2023) Perancangan Sistem Alarm Dan Monitoring Mahasiswa Selama Kelas Virtual Berbasis Ekspresi Wajah Dan Arah Pandangan Mata Menggunakan Jaringan Syaraf Tiruan. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Saat ini, transformasi digital sangat berkembang pesat pada setiap sendi kehidupan. Salah satunya adalah transformasi digital pada bidang pendidikan. Mobile Learning memudahkan mahasiswa untuk dapat mengakses materi pembelajaran kapan saja dan dimana saja. Mobile learning juga menawarkan adanya transformasi pelaksanaan pembelajaran konvensional di kelas menjadi pembelajaran virtual melalui platform video konferensi. Pelaksanaan kelas virtual tentunya memiliki beberapa kekurangan yaitu kurangnya self-disciplen para mahasiswa serta para pengajar yang terkendala dalam monitoring kondisi mahasiswa. Penelitian Tugas Akhir ini mengadopsi algorima model jaringan syaraf tiruan berupa Convolutional Neural Network dalam melakukan monitoring kondisi mahasiswa berbasis pengenalan dan klasifikasi ekspresi wajah dan arah pandangan mata mahasiswa selama menjalani kelas virtual. Model jaringan syaraf tiruan CNN yang dirancang memiliki tingkat akurasi training maupun testing melebihi angka 80%. Sistem juga dapat mengeluarkan bunyi alarm apabila beberapa mahasiswa sedang mengalami ekspresi bosan, bingung, maupun frustasi. Hasil penelitian menunjukkan bahwa ada keterkaitan erat antara kondisi mahasiswa dengan mengacu pada ekspresi wajah terhadap hasil akademik pasca pelaksanaan kelas virtual. Semakin positif ekspresi wajah mahasiswa maka semakin baik hasil akademik yang dicapai. Persepsi engagement mahasiswa juga ditunjukkan berdasarkan materi pembelajaran apabila materi pembelajaran menarik dan mudah dipahami maka ekspresi mahasiswa menunjukkan ekspresi fokus. ================================================================================================================================
Currently, digital transformation is growing rapidly in every aspect of life. One of them is digital transformation in the field of education. Mobile Learning makes it easy for students to be able to access learning materials anytime and anywhere. Mobile learning also offers a transformation of the implementation of conventional learning in class into virtual learning through a video conferencing platform. The implementation of virtual classes certainly has several drawbacks, namely the lack of self-discipline of students and teachers who are constrained in monitoring student conditions. This Final Project research adopts an artificial neural network model algorithm in the form of a Convolutional Neural Network in monitoring student conditions based on the recognition and classification of facial expressions and the direction of student eyes during virtual classes. The designed CNN neural network model has a training and testing accuracy rate exceeding 80%. The system can also sound an alarm when some students are experiencing expressions of boredom, confusion, or frustration. The results of the study show that there is a close relationship between the condition of students with reference to facial expressions and academic results after implementing virtual classes. The more positive the student's facial expressions, the better the academic results achieved. Perceptions of student engagement are also shown based on learning material if the learning material is interesting and easy to understand then student expressions show focused expressions.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	mobile learning, ekspresi wajah, arah pandangan mata, JST, CNN, mobile learning, facial expression, eye gaze, CNN, JST
Subjects:	L Education > L Education (General) T Technology > T Technology (General)
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	RATNA DIAN NABILA
Date Deposited:	04 Aug 2023 02:49
Last Modified:	04 Aug 2023 02:49
URI:	http://repository.its.ac.id/id/eprint/98873

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