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All Journal Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Prosiding Semnastek REKAYASA Journal of Information Systems Engineering and Business Intelligence JOIV : International Journal on Informatics Visualization Network Engineering Research Operation [NERO] JURNAL INSTEK (Informatika Sains dan Teknologi) Berdikari: Jurnal Pengabdian Masyarakat Indonesia Jurnal Sistem Cerdas JATI (Jurnal Mahasiswa Teknik Informatika) Teknika Innovative: Journal Of Social Science Research Journal of Information Technology and Cyber Security
Budi Dwi Satoto
Universitas Trunojoyo Madura
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Physics Public Health Other

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Analisis Kualitas Layanan Website Terhadap Kepuasan Pelanggan Menggunakan Metode E-Govqual, Importance Performance Analysis dan Potential Gain in Customer Value (Studi Kasus : Dinas Penanaman Modal & Pelayanan Terpadu Satu Pintu Kabupaten Bangkalan) Hadiri, Machsus; Yusuf, Muhammad; Satoto, Budi Dwi
Innovative: Journal Of Social Science Research Vol. 4 No. 4 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i4.13636

Abstract

Kualitas layanan merupakan kemampuan sebuah perusahaan dalam memenuhi harapan pelanggan dengan memberikan layanan kepada pelanggan pada saat berinteraksi dengan pelanggan. Penggunaan website merupakan langkah yang tepat dalam penerapan E-Government karena informasi yang terkandung di dalamnya lebih mudah diakses bagi pengguna informasi. Penggunaan website di organisasi publik berperan penting dalam hal peningkatan transparansi, akuntabilitas dan partisipasi publik dengan menyediakan pengungkapan yang lebih efektif dan efisien mengenai proses, struktur dan produk pemerintah. Pemerintah Kabupaten Bangkalan melalui Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu (DPMPTSP) Kabupaten Bangkalan menerapkan konsep E-Government dengan cara membangun website DPMPTSP yang berisi tentang informasi pelayanan. Untuk mengetahui kualitas suatu layanan website E-Government maka dilakukan analisis kualitas layanan dengan menggunakan metode E-Govqual, Importance Performance Analysis (IPA) dan Potential Gain In Customer Value (PGCV).
Classification of Rice Disease Using Deep Learning Object Detection Yolov8 Dwi Satoto, Budi; Rosa Anamisa, Devie; Yusuf, Muhammad; Kautsar Sophan, Mohammad; Kembang Hapsari, Rinci; Irmawati, Budi; Arrova Dewi, Deshinta
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.3578

Abstract

Rice plant pests and diseases are among the primary threats to agricultural production, particularly in rice-growing regions, which can result in a significant decrease in crop yields and food production. Therefore, technology is essential for accurately detecting and classifying pests and diseases. In this research, the author proposes using deep learning-based object detection for moving objects. This is because observations are made on relatively large land areas. Images are captured by drone cameras as videos, which are then used to create ground-truth markers and identification targets during training. YOLO v8 is the latest object detection model on moving media. This model offers advantages in speed and accuracy, making it well-suited for applications that require precise results on agricultural land. The dataset comprises videos of rice plants infested with pests and diseases. After completing labeling and training, the YOLO v8 model can detect and classify pests and diseases in real time using markers in the form of frames with identification labels. Farmers can identify pest and disease attacks earlier by implementing this system, enabling more effective, timely pest control measures. The study's results showed that the training accuracy was 91.5%. The F1-Confidence measurement value obtained was 0.84, the Precision-Recall Curve was 0.891, and the Recall Confidence Curve was 0.97. The trial results, based on experimental data, achieved confidence accuracy of 80% to 95%.
Co-Authors Abidin, Mochammad Syahrul Achmad Yasid Amillia Kartika Sari Amin Abdillah Angkoso, Cucun Very Ari Kusumaningsih Arrova Dewi, Deshinta Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Budi Irmawati Efendi, Moch Rizal Eko Budi Khoendori Eza Rahmanita Faisal Dzikri, Mohammad Fika Hastarita Rachman, Fika Hastarita Firli Irhamni Firmansyah, Muhammad Iqbal Hadiri, Machsus Imam Utoyo Iswati Iswati Iswati Iswati, Iswati Jannah, Maughfirotul Javier, Najamuddin Kautsar Sophan, Mohammad Kembang Hapsari, Rinci Khotimah, Bain Khusnul Khotimah, Bain Khusnul Laili, Moh Linda Rimala Dewi Moh Laili Muhammad Yusuf Mukhamad Khoironi Novi Prastiti, Novi Putra, Wahyu Zainur Rima Tri Wahyuningrum Riries Rulaningtyas Rosa Anamisa, Devie Sensusiati, Anggraini Dwi Soesilo, Budi Thrisna, Mochamad Adrian Nuradha Yeni Kustiyahningsih Yudha Dwi Putra Negara, Yudha