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APLIKASI PEMBELAJARAN DASAR BAHASA INGGRIS UNTUK ANAK DENGAN METODE PQRST BERBASIS MULTIMEDIA MOBILE Yus Jayusman; Faiqunisa Faiqunisa; Reni Triastuti
JURTIK:Jurnal Penelitian dan Pengembangan Teknologi Informasi dan Komunikasi Vol 8 No 1 (2019): JURTIK : Jurnal Teknologi Informasi dan Komunikasi
Publisher : LPPM STMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (370.641 KB) | DOI: 10.58761/jurtikstmikbandung.v8i1.132

Abstract

English was introduced early on because the children have learned the so-called golden age of brilliant, which allows children at an early age learn languages quickly. Found those things need to be built upon an application which is expected to be used by parents and children, the method used to build these applications is the PQRST IE Preview, Question, Read, Summarize, pronunciation of vocabulary Test in the form of pictures and voice, learning and practice.
KLASIFIKASI RAS KUCING MENGGUNAKAN METADATA DATASET KAGGLE DENGAN FRAMEWORK YOLO v5 Mina Ismu Rahayu; faiqunisa Faiqunisa
JURTIK:Jurnal Penelitian dan Pengembangan Teknologi Informasi dan Komunikasi Vol 12 No 1 (2023): JURTIK: Jurnal Teknologi Informasi dan Komunikasi
Publisher : LPPM STMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58761/jurtikstmikbandung.v12i1.179

Abstract

At this time cats have a variety of different breeds around the world including the Persian, Maine Coon, Siamese, Ragdoll, Sphynx and others. To find out, each cat breed can be seen from the pattern, coat color, and there are some faces that are different from other cats, but not completely the pattern, coat color and face can distinguish each cat breed. With the development of the times and increasing technology in the field of Computer Vision where the Artificial Intelligence system that is trained is used as a tool to classify types of cat breeds based on their faces using a computer. This study aims to be able to recognize and classify cat breeds based on their faces using YOLOv5. The evaluation parameters used are Confusion Matrix, Mean Average Precision, Precision and Recall. The experimental results show that the best model is achieved in the 60th epoch scenario in the 16th batch size with precision 0.9844, Recall of 1.0, mAP 0.5 of 0.9933 and mAP 0.5 : 0.95 of 0.9144.