Article Per Year (5 Year)
p-Index From 2021 - 2026
0.817
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Komputer dan Informatika
Rochmawati, Dwi Robiul
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
DETEKSI WAJAH DENGAN METODE HAAR CASCADE MENGGUNAKAN OPENCV (FACE DETECTION WITH HAAR CASCADE METHOD USING OPENCV) Rochmawati, Dwi Robiul
Jurnal Teknologi Komputer dan Informatika Vol 3 No 1 (2024): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i1.293

Abstract

Abstract Face detection is one of the most researched topics in the field of computer vision and digital image processing. The Haar Cascade method is one method that is often used to detect faces in an image or video. This method uses Haar features to identify faces by comparing them with existing faces in the database. This research aims to implement the Haar Cascade method to detect faces using the OpenCV library. The stages include image acquisition, image processing, face detection using Haar Cascade, and evaluation of detection results. The results show that the Haar Cascade method can detect faces quite well in various lighting conditions and viewing angles. Keywords: Face Detection; Haar Cascade; OpenCV
KLASIFIKASI EMOSI MENGGUNAKAN COMPUTER VISION DAN CONVOLUTIONAL NEURAL NETWORKS Nurdiyansah , Andri; Rochmawati, Dwi Robiul
Jurnal Teknologi Komputer dan Informatika Vol 3 No 2 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i2.411

Abstract

This research focuses on the development of an emotion classification system utilizing computer vision and Convolutional Neural Networks (CNN). This model was trained on the FER2013 dataset, which contains 35,809 facial images categorized into seven emotions. Metode seperti augmentasi data dan normalisasi piksel diterapkan untuk meningkatkan ketahanan model. The CNN architecture achieved an accuracy of 85%, demonstrating its effectiveness in recognizing emotions such as happiness and anger. This research highlights the potential integration of emotion-aware systems into applications such as human-computer interaction and personalized services, emphasizing technical innovation in AI-based solutions. Keywords: Emotion Classification; Computer Vision; CNN; FER2013; Deep Learning
PREDIKSI CUACA DENGAN JARINGAN SYARAF TIRUAN MENGGUNAKAN PYTHON Rochmawati, Dwi Robiul
Jurnal Teknologi Komputer dan Informatika Vol 2 No 2 (2024): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v2i2.228

Abstract

Weather prediction is one of the growing challenges in meteorological science. Accurate prediction methods can provide invaluable information for various sectors, including agriculture, transport, and natural disaster mitigation. One approach used in predicting weather is using artificial neural network (ANN) techniques. JST is a computational model inspired by the structure and function of human biological neural networks. This research aims to implement and evaluate the performance of JST in weather prediction. The data used is historical weather data that includes parameters such as air temperature, humidity, air pressure, and wind direction. The training process is carried out using a suitable learning algorithm to adjust the weights in the JST to produce accurate weather predictions. The results of this study show that a single hidden layer with only two nodes performs slightly better than more complex architectures. In addition, it requires a much shorter training time. In terms of accuracy and efficiency despite using a simpler architecture, the small network almost achieved the same accuracy (around 89%) as the original network. In addition, its training time is also more efficient. So based on these findings, it was decided to continue with the optimized network layout (one hidden layer with 2 nodes) due to the good balance between accuracy and efficiency. This research not only improves the accuracy of weather prediction but also highlights the importance of neural network architecture optimization according to the specific dataset and task.
MANFAAT KECERDASAN BUATAN UNTUK PENDIDIKAN Rochmawati, Dwi Robiul; Arya , Ivan; Zakariyya, Azka
Jurnal Teknologi Komputer dan Informatika Vol 2 No 1 (2023): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v2i1.163

Abstract

Pemanfaatan kecerdasan buatan (AI) dalam pendidikan telah menjadi subjek yang menarik perhatian akademisi dan praktisi pendidikan. Dalam konteks ini, penelitian ini bertujuan untuk mengeksplorasi manfaat AI dalam pembelajaran, pengembangan metode pengajaran, serta peningkatan efektivitas secara keseluruhan. Melalui metode penelitian deskriptif dan analisis komprehensif, penelitian ini mengidentifikasi manfaat AI dalam personalisasi pembelajaran, pengajaran adaptif, analisis data pendidikan, serta peningkatan akses global terhadap pendidikan. Namun, penerapan AI juga menimbulkan sejumlah tantangan dan kekhawatiran etika, seperti bias algoritma, privasi dan keamanan data, ketergantungan teknologi, dan kurangnya pelatihan guru. Oleh karena itu, penelitian ini memberikan saran-saran untuk mengelola tantangan tersebut secara bijaksana, termasuk pengelolaan bias algoritma, perlindungan privasi data, keterlibatan manusia yang cukup, transparansi algoritma, pelatihan guru yang memadai, dan pertimbangan etika dalam pengambilan keputusan karier. Dengan pendekatan yang hati-hati terhadap tantangan dan saran-saran ini, integrasi AI dalam pendidikan dapat memberikan manfaat maksimal sambil menjaga keadilan, privasi, dan keterlibatan manusia yang penting dalam proses pendidikan.
Co-Authors Arya , Ivan Nurdiyansah , Andri Zakariyya, Azka