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All Journal Jurnal Informatika dan Teknik Elektro Terapan NERO (Networking Engineering Research Operation)
Jeri, Jeri
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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RANCANG BANGUN APLIKASI VIRTUAL TOUR 360o OBJEK WISATA AIR TERJUN ANDULAN DESA SITEBA KECAMATAN WALENRANG UTARA BERBASIS WEBSITE Jeri, Jeri; Muhallim, Muhlis; Paembonan, Solmin
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5404

Abstract

Rancang Bangun Aplikasi Virtual Tour 3600 Objek Wisata Air Terjun Andulan Desa Siteba Kecamatan Walenrang Utara Berbasis Website. Virtual tour atau biasa disebut dengan istilah tur 360derajat merupakan kumpulan gambar panorama 360 derajat yang digabungkan sehingga mendapatkan pengalaman seperti berada di tempat itu. Penelitian ini mengusulkan Rancang Bangun Aplikasi Virtual Tour 3600 Objek Wisata Air Terjun Andulan Desa Siteba Kecamatan Walenrang Utara Berbasis Website. Aplikasi ini dapat diakses melalui link yang dapat terhubung langsung dengan website untuk mengidentifikasi pengguna yang diperbolehkan masuk. Sistem ini terdiri dari beberapa komponen, termasuk wordpres.com untuk menampilkan halaman website, dan lapentor.com untuk menampilkan gambar virtual tour. Melalui pengujian dan evaluasi, sistem ini terbukti mampu menampilkan website dan gambar panorama virtual tour. Dengan demikian, solusi ini dapat meningkatkan daya tarik wisatawan dengan memanfaatkan teknologi yang sudah ada dan mudah diakses oleh masyarakat umum. Penelitian selanjutnya diharapkan dapat memperluas fungsionalitas dan meningkatkan virtual tour 3600 ini dalam berbagai skenario penggunaan.Keywords: Tourism, Virtual Tour, Waterfall
PENENTUAN UKURAN BATCH OPTIMAL UNTUK PELATIHAN YOLOV8 DALAM PENDETEKSIAN OBJEK PADA KENDARAAN OTONOM Jeri, Jeri; Syarif Hidayat, Zaid
Networking Engineering Research Operation Vol 9, No 1 (2024): Nero - April 2024
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v9i1.27462

Abstract

This study aims to determine the optimal batch size in training the YOLOv8 model for object detection in autonomous vehicles. With the increasing need for accurate and efficient object detection technology, this study explores the effect of batch size variation on the performance of the YOLOv8 model. The dataset used in this study is a traffic simulation dataset from CARLA, obtained from the Roboflow universe, consisting of 1719 images divided into training, validation, and testing data. The research methodology includes data collection, pre-processing, and data analysis using the YOLOv8 technique with different hyperparameter settings. The results showed that increasing the number of epochs and batch size contributed to the increase in the mean Average Precision (mAP) value of the model. The best training scheme was identified with the highest mAP value of 98.2%, using 100 epochs, batch size 32, and image resolution 640x640. These findings provide important insights for further development in object detection technology, as well as provide guidance for researchers who want to optimize training parameters for object detection models using YOLOv8 in the context of autonomous vehicles. This research is expected to serve as a reference for future studies in this field.Kata kunci: YOLOv8, object detection, autonomous vehicle, optimal batch size, CARLA dataset, mean Average Precision (mAP), hyperparameters, model training
Co-Authors Muhallim, Muhlis Paembonan, Solmin Syarif Hidayat, Zaid