Wahyu Sapto Adhi, - (2022) RANCANG BANGUN APLIKASI DETEKSI MASKER BERBASIS ARTIFICIAL INTELLEGENCE SEBAGAI MEDIA PENERAPAN PROTOKOL KESEHATAN PEMBELAJARAN TATAP MUKA DI SEKOLAH. S1 thesis, Universitas Pendidikan Indonesia.
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Abstract
Pandemi covid di Indonesia menyebabkan kegiatan belajar mengajar di sekolah dihentikan sementara untuk mencegah terjadinya penyebaran kasus positif di klaster sekolah. Sejak awal tahun 2022, pandemi mulai mereda dan sekolah diperbolehkan untuk melaksanakan kembali kegiatan tatap muka dengan tetap memperhatikan pelaksanaan protokol kesehatan terutama memakai masker. Untuk meningkatkan kedisiplinan serta mengawasi pemakaian masker di lingkungan sekolah, Peneliti membuat sebuah program deteksi masker menggunakaan metode Convolutional Neural Network (CNN) yang akan diimplementasikan selama pembelajaran tatap muka. Penelitian ini menggunakan model SDLC model waterfall yang terdiri dari 5 tahap yaitu, (1) Requirements Analysis and Definition, (2) System and Software Design, (3) Implementation and Unit Testing, (4) Integration and System Testing, dan (5) Operation and Maintenance. Analisis akurasi program menggunakan rumus confusion matrix. Penelitian menggunakan 4 variabel dalam menentukan akurasi program yaitu true positive (tp), false positive (fp), true negative (tn), dan false negative (fn). Proses pembuatan program menggunakan bahasa pemrograman python dengan bantuan library Tensorflow dan OpenCV. Program dibuat pada aplikasi code editor sublime text.Hasil tingkat akurasi program setelah dilaksanakan uji coba di kelas X AMM 2 selama 3 jam adalah sebesar 68,46%. Berdasarkan penilaian produk multimedia menggunakan rating scale, program termasuk dalam kategori layak. Program dapat diterapkan yang memberikan informasi pemakaian masker dan dapat dibaca oleh sistem. Dari hasil penelitian didapat tingkat pemakaian masker di kelas X AMM 2 adalah sebesar 68,26%. -------- The Covid pandemic in Indonesia has caused teaching and learning activities in schools to be temporarily suspended to prevent the spread of positive cases in school classes. Since the beginning of 2022, the pandemic has begun to subside and schools are allowed to carry out face-to-face activities while still paying attention to the implementation of health protocols, especially wearing masks. To improve discipline and monitor masks in the school environment, the researcher created a mask detection program using the Convolutional Neural Network (CNN) method which will be implemented during face-to-face learning. This study uses the waterfall model SDLC model which consists of 5 stages, namely, (1) Requirements Analysis and Definition, (2) System and Software Design, (3) Implementation and Unit Testing, (4) System Integration and Testing, and (5 ) Operation and Maintenance. Analysis of program accuracy using the confusion matrix formula. This study uses 4 variables in program accuracy, namely true positive (tp), false positive (fp), true negative (tn), and false negative (fn). The process of making the program using the python programming language with the help of the Tensorflow and OpenCV libraries. The program is made in the sublime text code editor application. The results of the program's accuracy level after the test in class X AMM 2 for 3 hours is 68.46%. Based on the assessment of multimedia products using a rating scale, the program is included in the feasible category. Programs can be implemented that provide information on the use of masks and can be read by the system. From the results of the study, it was found that the level of wearing masks in class X AMM 2 was 68.26%.
| Item Type: | Thesis (S1) |
|---|---|
| Uncontrolled Keywords: | Deteksi Masker, Convolutional Neural Network, Confusion Matrix, Artificial Intellegence. Pembelajaran Tatap Muka |
| Subjects: | L Education > L Education (General) L Education > LB Theory and practice of education L Education > LB Theory and practice of education > LB1603 Secondary Education. High schools T Technology > T Technology (General) |
| Divisions: | UPI Kampus cibiru > S1 Pendidikan Multimedia |
| Depositing User: | Wahyu Sapto Adhi |
| Date Deposited: | 16 Sep 2022 06:29 |
| Last Modified: | 07 Feb 2023 02:29 |
| URI: | http://repository.upi.edu/id/eprint/81021 |
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