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All Journal CHAIN: Journal of Computer Technology, Computer Engineering and Informatics TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Dwi Handoko
Politeknik Negeri Lampung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Rancang Bangun Sistem Booking Online Wedding Organizer Berbasis Mobile Dwi Handoko
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 2 No. 4 (2024): Volume 2 Number 4 October 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v2i4.152

Abstract

Rancang bangun sistem booking online wedding organizer bertujuan untuk mempermudah pasangan pengantin dalam merencanakan pernikahan dengan menyediakan platform yang efisien dan terorganisir. Melalui sistem booking online, pasangan pengantin dapat mengakses informasi mengenai layanan yang tersedia, memilih paket yang sesuai dengan anggaran dan preferensi, serta melakukan pemesanan tanpa perlu bertatap muka langsung dengan pihak wedding organizer. Penelitian ini bertujuan untuk merancang dan membangun sebuah sistem booking online wedding organizer berbasis mobile yang dapat mempermudah pasangan pengantin dalam merencanakan dan mengelola acara pernikahan mereka dengan lebih efisien. Hasil pengujian sistem menggunakan metode Blackbox Testing, aplikasi booking online wedding organizer berbasis mobile memperoleh nilai 100%, yang menunjukkan bahwa seluruh fitur utama berfungsi dengan baik sesuai dengan harapan. Setiap skenario pengujian, mulai dari registrasi pengguna, pencarian paket, pemesanan, pembayaran, hingga pengelolaan pemesanan oleh admin, berhasil dieksekusi tanpa kendala. Aplikasi juga mampu menangani input yang valid dan tidak valid dengan tepat, serta memberikan umpan balik yang sesuai kepada pengguna. Pengujian ini membuktikan bahwa aplikasi siap untuk diluncurkan dengan performa optimal, memberikan pengalaman pengguna yang lancar dan memuaskan.
Enhancing rice plant disease detection through transfer learning and image segmentation with YOLOv11 Muhammad Reza Redo I Islami; Sylvia; Atika Arpan; Rizka Permata; Dwi Handoko; Rima Maulini; Dwirgo Sahlinal
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1754

Abstract

Rice is a staple food globally, yet its productivity is often threatened by diseases such as blast and brown spot. Traditional diagnostic methods relying on human observation are prone to delays and inaccuracies. This study introduces an automated detection system that utilizes YOLOv11-seg to improve the accuracy and efficiency of rice disease identification. The model integrates object detection and instance segmentation, is trained on over 6,000 annotated images covering six categories (five disease types and healthy leaves), and leverages transfer learning from COCO weights. Experimental results show that the model achieved a bounding box mAP@50 of 0.607 and a segmentation mAP@50 of 0.564, with F1-scores of 0.62 and 0.59, respectively. The highest detection accuracy was recorded for healthy leaves (86%), while segmentation performance declined on visually similar classes such as Brown Spot and Sheath Blight. Overfitting was observed during training, with a 15–20% gap between training and validation metrics. These findings demonstrate the model's potential for real-time field application in precision agriculture. Future improvements should focus on enhancing spatial accuracy and robustness through synthetic data generation and architectural optimization.
Co-Authors Atika Arpan Dwirgo Sahlinal Muhammad Reza Redo I Islami Rima Maulini Sylvia