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All Journal Journal of Computer System and Informatics (JoSYC) ABDIMAS
Sutjiningtyas, Sri
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Industrial & Manufacturing Engineering Physics Other

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Pengenalan dan Penerapan Ekonomi Digital dan E-Government Pada Masyarakat Desa Pananjung Phety, Debora Tri Oktarina; Sutjiningtyas, Sri; Barliansah, Beni; Gea, Firmanto; Fauziah, Nurlaela; Sadewo, Bayu Rachmad
Jurnal Pengabdian Kepada Masyarakat (ABDIMAS) Vol. 2 No. 2 (2024): JURNAL PENGABDIAN KEPADA MASYARAKAT (ABDIMAS) VOL.2 NO.2 JUNI 2024
Publisher : LPPM Universitas Nurtanio Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56244/abdimas.v2i2.851

Abstract

Kegiatan pengabdian kepada masyarakat ini dilakukan untuk memperkenalkan dan menerapkan ekonomi digital dan e government di Desa Pananjung yang dilakukan pada bidang pemerintah, bidang kemasyarakatan dan bidang pembangunan. Dengan melakukan sosialisasi mengenai ekonomi digital, pemasaran produk UMKM semakin meluas dan semakin meningkatkan perekonomian desa. Sosialisasi E Government dilakukan dengan melakukan penyuluhan update Sistem Informasi Desa (SID) dengan kolaborasi dosen pembimbing, perangkat desa, dan mahasiswa. Setelah melakukan sosialisasi, tim melakukan implementasi terhadap produk yang dimiliki oleh UMKM melalui pemasaran media online, penggunaan aplikasi photoshop dan melakukan packing barang. Implementasi E Government dilakukan dengan membantu perangkat desa menginput data penduduk non permanen sehingga akan mempercepat pelayanan desa kepada masyarakat, memperbaharui profil desa secara digital yang akan meningkatkan informasi Desa Pananjung terhadap masyarakat luas dan memperluas potensi desa.
Implementasi Pengenalan Ekspresi Wajah dengan Menggunakan Metode Convolutional Neural Network dan OpenCV Berbasis Webcam Melatisudra, Raifvaldhy Jounias Luppus; Utomo, Suharjanto; Sutjiningtyas, Sri; Hernawati, Hernawati
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6114

Abstract

Facial expressions play an important role as a non-verbal language rich in emotional information, especially in psychological contexts. The main challenge in this research is to understand and analyse complex facial expressions, which are often difficult for psychologists to interpret. The implementation of webcam-based facial expression recognition leverages the computer's ability to visually recognise human emotions, supported by artificial intelligence and machine learning. Convolutional Neural Network (CNN) and OpenCV methods are used to detect and classify facial expressions directly. The CNN model is trained using a dataset with six expression classes (happy, sad, angry, surprised, neutral, afraid), with four convolution layers for multi-class classification. The implementation of facial expression recognition is successful, the system captures facial images from a webcam, detects faces in the frame, and classifies facial expressions directly on the screen window. The performance of training data against the trained model measured using Classification Accuracy shows an accuracy of 72.34% in training accuracy and 60.54% in validation accuracy. While the performance of the facial expression recognition system calculated using Confusion Matrix resulted in an accuracy of 70.55%. The calculation results show that the model is at the Fair Classification parameter level or able to classify facial expressions in humans with a fairly good level of accuracy, this research has great potential for application development in the field of psychology. However, further optimisation is needed by involving experts to ensure its effectiveness.
Co-Authors Barliansah, Beni Fauziah, Nurlaela Gea, Firmanto Hernawati Hernawati Melatisudra, Raifvaldhy Jounias Luppus Phety, Debora Tri Oktarina Sadewo, Bayu Rachmad Utomo, Suharjanto