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All Journal Jurnal Teknologi Terpadu Prosiding National Conference for Community Service Project
Patrick Pratama Hendri
Universitas Internasional Batam
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering

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Pengembangan aplikasi ujian berbasis web pada SMK Maitreyawira Patrick Pratama Hendri; Haeruddin Haeruddin
National Conference for Community Service Project (NaCosPro) Vol 4 No 1 (2022): The 4th National Conference of Community Service Project 2022
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/nacospro.v4i1.7131

Abstract

SMK Maitreyawira Batam sudah melakukan proses pembelajaran secara daring selama masa pandemi covid-19 ini. Oleh karena itu dibutuhkan sebuah aplikasi yang dapat mengakomodasi seluruh kebutuhan ujian siswa secara daring. Dalam pengembangan aplikasi ujian online dilakukan dengan metode WSDM, dimana perancangan aplikasi tersebut dapat memenuhi seluruh kebutuhan yang diminta oleh SMK Maitreyawira. Dengan adanya aplikai ujian online ini, SMK Maitreyawira bisa mengurangi pekerjaan dan waktu yang dibutuhkan relatif lebih sedikit sehingga lebih efisien dan efektif.
Pengembangan Aplikasi Emoticon Recognition dan Facial Recognition menggunakan Algoritma Local Binary Pattern Histogram (LBPH) dan Convolutional Neural Network (CNN) Haeruddin Haeruddin; Herman Herman; Patrick Pratama Hendri
Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i1.613

Abstract

In the current modern era facial recognition technology can be found inside of everyday life, but said technology still has a big problem which is deepfake, where in which a deepfake can bypass security systems created with facial recognition as its base, one facial aspect that a deepfake cannot replicate perfectly is the emotion that can be observed from expression, which is why an emotion can be used as a tool to detect a deepfake, which is why an application that can detect both face and emotion at the same time is needed to add security to facial recognition technology, writer has succeeded in creating an application that can do both emotion recognition and facial recognition at the same time using LBPH (Local Binary Pattern Histogram) algorithm and purposive sampling technique for the facial recognition aspect with 67.5% accuracy and CNN (Convolutional Neural Network) algorithm using FER2013 (Facial emotion Recognition 2013) dataset for the emotion recognition aspect with 58.4% accuracy, with CRISP-DM method that can achieve the average accuracy rate of 63%, because currently not many research combine facial recognition using LBPH (Local Binary Pattern Histogram) algorithm and emotion recognition using CNN (Convolutional Neural Network) algorithm at the same time.
Co-Authors Haeruddin haeruddin Herman Herman