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All Journal Edsence: Jurnal Pendidikan Multimedia EPSILON: Journal of Electrical Engineering and Information Technology
Nurmalasari, Rin Rin
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Other

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Face Recognition Based Attendance System Using Haar Cascade Algorithm with Histogram Equalization and Median Blur Filter Nurmalasari, Rin Rin; Nurhadhi, Rizky; Ramadhan, Rizky Mahesa; Katresnawati, Shabrina; Salsabila, Zalfa Humaira
Jurnal Pendidikan Multimedia (Edsence) Volume 5 No 2 (December 2023)
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/edsence.v5i2.65907

Abstract

The attendance system is one of the mandatory activities in teaching and learning activities in an educational environment. Unfortunately, many still use a manual attendance system, which is inefficient, and fraud often occurs by manipulating attendance data. In this research, a face recognition-based attendance system was created. The face detection and recognition system use the haar cascade method with image preprocessing, namely histogram equalization and median blur filter. This system can provide output in the form of CSV documents containing attendance data that has been done in real time so that attendance data recording becomes more efficient than before. There is a significant difference in face recognition without and with image preprocessing. Without image preprocessing, the average face recognition accuracy rate is 71.2%. In face recognition with image preprocessing, the face recognition accuracy rate is 91.5%. Therefore, the use of image preprocessing can improve image quality and significantly increase the accuracy of face recognition. In addition, the CSV document is successfully generated automatically after the attendance process is carried out, which is equipped with user data, attendance date, and time when the user makes attendance to avoid fraud in the form of manipulation of attendance data by users.
Hanacaraka Javanese Handwriting Detection Using Recurrent Neural Network (RNN) Yusuf, Ichsan Nur Rachmad; Nurmalasari, Rin Rin; Kamelia, Lia
Jurnal Pendidikan Multimedia (Edsence) Volume 6 No 1 (June 2024)
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/edsence.v6i1.74727

Abstract

Hanacaraka Javanese script is a valuable Indonesian cultural heritage, but its use has declined due to a lack of knowledge and ability to read and write the script. The main challenge in detecting and recognizing handwritten Javanese script is the variation of its shape and writing style. This research aims to train computers to recognize Javanese script. Prior to this research, there have been several similar studies with different recognition methods. In this research, the Recurrent Neural Network (RNN) method is used. The process of detection and recognition of Javanese script letters is divided into three parts: input image of script images used as a dataset of 500 images for training data and 8 pictures for prediction test data, the process of creating a Recurrent Neural Network model, and the output of this design is the performance of the Recurrent Neural Network model. The test results show that the model has an overall accuracy of 96%, with an average precision, recall, and F1 score of 96% each. Sentences such as "Dhahara", "Jawanagara", "Malaca", and "Ramayana" were successfully detected completely correctly, although some sentences such as "Jayabaya", "Nyala", and "Palawa" experienced prediction errors.
Rancang Bangun Prototipe Monitoring Dan Controlling Penggunaan Air Di Perumahan Berbasis IoT Ridwan, Azwar Mudzakkir; Arbian, Adlian Tsaltsa; Nurmalasari, Rin Rin
EPSILON: Journal of Electrical Engineering and Information Technology Vol 21 No 2 (2023): EPSILON: Journal of Electrical Engineering and Information Technology
Publisher : Department of Electrical Engineering, UNJANI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55893/epsilon.v21i2.107

Abstract

Sistem monitoring dan controlling penggunaan air pada saat ini masih menggunakan alat konvensional, dimana pengguna tidak dapat mengecek dan mengontrol air yang digunakan secara jarak jauh. Era teknologi yang berkembang semakin pesat menuntut manusia untuk melakukan berbagai inovasi yang bisa mempermudah suatu pekerjaan tanpa mengurangi keakurasian hasil. Penelitian ini telah membuat sistem yang dapat melakukan pengambilan data debit air dan total penggunaan air. Selain itu, sistem ini juga dapat melakukan control penggunaan air secara otomatis. Mikrokontroller yang digunakan adalah ESP32 karena dapat dikoneksikan ke internet. Platform IoT yang digunakan adalah Ubidots sebagai penampil pada sistem monitoring. Alat yang dibuat dapat berjalan dengan baik dengan hasil uji didapatkan Pada pengujian ini didapatkan hasil pada bukaan keran 10o didapatkan debit air sebesar 0,006 Liter/detik dan pada bukaan keran 80o didapatkan nilai 0,216 Liter/detik. Nilai pada bukaan keran ini sama dengan posisi 600 dan 700. alasan didapat nilai berikut karena pada bukaan 600 tekanan air yang mengalir sudah full sehingga Ketika diposisi 700 dan 800 masih memiliki debit yang sama. Selanjutnya pengujian dilakukan dengan membandingkan antara nilai yang dihasilkan oleh serial monitor dan hasil pengukuran manual menggunakan gelas ukur. Dari hasil pengujian ini didapatkan nilai selisih rata – rata pada 0,188 Liter. Selisih ini didapat dari adanya kebocoran pada selang yang masuk ke penampungan sehingga ikut terukur. Cloud ubidots mampu menampilkan data debit, volume total penggunaan dan grafik pemakaian.
Co-Authors Arbian, Adlian Tsaltsa Katresnawati, Shabrina lia kamelia Mudzakkir Ridwan, Azwar Nurhadhi, Rizky Ramadhan, Rizky Mahesa Salsabila, Zalfa Humaira Yusuf, Ichsan Nur Rachmad