Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Komatika: Jurnal Pengabdian Kepada Masyarakat
Ahmad Wahyu Rosyadi, Ahmad Wahyu
Institut Teknologi Sepuluh Nopember
Humanities Computer Science & IT Dentistry Education Engineering Library & Information Science Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Pelatihan Pembuatan Media Pembelajaran Berbasis Android Bagi Guru Untuk Meningkatkan Mutu Pembelajaran di Madrasah Tsanawiyah Manbaul Ulum Rohman, Taufiqur; Assani, Saffana; Rosyadi, Ahmad Wahyu; Aini, M. Anwar; Faqihatin; Hildani, Muhammad Rizqi; Mahmudah, Adilla; Mahera, Ahmad Firmansyah; Adelliyah, Nur Aini; Indawati, Ajeng Sri; Nidhom, Mohammad Syahrun; Effindi, Muhamad Afif
Komatika: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2024): Mei 2024
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat, Institut Informatika Indonesia Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/komatika.v4i1.795

Abstract

Media pembelajaran berbasis elektronik atau digital bertujuan untuk menambah minat belajar siswa yang berdampak pada prestasi belajar siswa yang lebih baik, media pembelajaran digital juga lebih memudahkan siswa mengakses materi pembelajaran. Madrasah Tsanawiyah (MTs) Manbaul Ulum merupakan sekolah lanjutan pertama (SLTP) yang berada di Desa Mojopuro Gede Kecamatan Bungah Kabupaten Gresik Porvinsi Jawa Timur. Dalam pelaksanaan pembelajaran di MTs Manbaul Ulum perlu adanya pengembangan media belajar yang inovatif untuk meningkatkan minat belajar siswa. Pelaksanaan kegiatan pengabdian kepada masyarkat ini bertujuan untuk membantu meningkatkan kompetensi guru di sekolah mitra dalam mengembangankan media pembelajaran berbasis android. Tahap pelaksanaan kegiatan pengabdian ini terbagi dalam tahap persiapan dan tahap pelaksanaan, tahap persiapan terdiri dari studi literatur dan observasi lapangan di sekolah mitra untuk mendapatkan rumusan permasalahan dan penentuan solusi untuk sekolah mitra serta pembuatan modul yang sesuai kebutuhan. Pelaksanaan pelatihan dilakukan dengan ceramah oleh pemateri dan praktik oleh peserta. Peserta diminta untuk membuat media pembelajaran berbasis android sesuai dengan arahan dari pemateri. Pelatihan ini menghasilkan mendia pembelajaran berbasis android yang dibuat oleh peserta pelatihan yang dapat dijadikan modal oleh peserta dalam mengembangkan media pembelajaran berbasis andorid.
Median Filter For Transition Region Refinement In Image Segmentation Rosyadi, Ahmad Wahyu; Suciati, Nanik
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 16, No. 2, Juli 2018
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v16i2.a750

Abstract

Transition region based image segmentation is one of the simple and effective image segmentation methods. This method is capable to segment image contains single or multiple objects. However, this method depends on the background. It may produce a bad segmentation result if the gray level variance is high or the background is textured. So a method to repair the transition region is needed. In this study, a new method to repair the transition region with median filter based on the percentage of the adjacent transitional pixels is proposed. Transition region is extracted from the grayscale image. Transition region refinement is conducted based on the percentage of the adjacent transitional pixels. Then, several morphological operations and the edge linking process are conducted to the transition region. Afterward, region filling is used to get the foreground area. Finally, image of segmentation result is obtained by showing the pixels of grayscale image that are located in the foreground area. The value of misclassification error (ME), false negative rate (FNR), and false positive rate (FPR) of the segmentation result are calculated to measure the proposed method performance. Performance of the proposed method is compared with the other method. The experimental results show that the proposed method has average value of ME, FPR, and FNR: 0.0297, 0.0209, and 0.0828 respectively. It defines that the proposed method has better performance than the other methods. Furthermore, the proposed method works well on the image with a variety of background, especially on image with textured background.
Ingredients Identification Through Label Scanning Using PaddleOCR and ChatGPT for Information Retrieval Rosyadi, Ahmad Wahyu; Siti Ma’shumah; Muhammad Qomaruz Zaman; Moh. Rizki Fajar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 6 (2024): December 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i6.6119

Abstract

Human health depends on choosing food ingredients that align with dietary needs and avoid allergens. However, consumers often encounter unfamiliar ingredients that require additional information. Traditionally, they search online by typing in the ingredient's name which can be time-consuming and may not yield relevant results. Therefore, a system to identify and display ingredient information is necessary. This study proposes a new system that identifies ingredients by scanning the composition label on packaging using PaddleOCR and retrieving information through ChatGPT on a smartphone. The process begins with capturing an image of the composition label. Then PaddleOCR is employed to extract text from the scanned label, enabling identification of the listed ingredients. Subsequently, ChatGPT retrieves detailed information about the desired ingredients and displays it, allowing users to easily understand the ingredients. The system's effectiveness in text recognition is assessed using the character error rate (CER). The results show robust performance by achieving an average CER of 0.14, with flat packaging reaching an impressive CER of 0.05. Additionally, the system's usability was assessed through pilot testing which received significant positive user feedback achieving 4.37 satisfaction level on Likert scale, particularly regarding the clarity and relevance of the ingredient information provided.
Co-Authors Adelliyah, Nur Aini Assani, Saffana Faqihatin Hildani, Muhammad Rizqi Indawati, Ajeng Sri M. Anwar Aini Mahera, Ahmad Firmansyah Mahmudah, Adilla Moh. Rizki Fajar Muhamad Afif Effindi, Muhamad Afif MUHAMMAD QOMARUZ ZAMAN Nanik Suciati Nidhom, Mohammad Syahrun Siti Ma’shumah Taufiqur Rohman