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All Journal Jurnal Tunas Majalah Ilmiah UPI YPTK Jurnal Komtekinfo Jurnal Pengabdian Pada Masyarakat METHABDI
Syahrian, Achmad
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Digital Image Processing Education for Detection and Knowledge Information Hidden in Images Negoro, Wahyu Sapta; Azhar, Asbon Hendra; Destari, Ratih Adinda; Syahrian, Achmad
Jurnal TUNAS Vol 6, No 1 (2024): Edisi November
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jtunas.v6i1.117

Abstract

AbstractDigital Image Processing, known as Digital Image Processing, is a scientific discipline related to techniques for processing an image using a computer. There are several types of images, namely color images (RGB), grayscale images (grayscale), binary images (monochrome) (Akhmad Fadjeri et al, 2023). In the world of medicine, image segmentation is used to detect an object in a medical image or analyze the nature of a disease such as eye disease (keratitis) (Kon et al, 2023).Image is a representation or can also be said to be a picture, imitation, imitation, or similarity, of a particular object. Images, when grouped based on the type of data that makes up the image, are divided into 2 types, namely analog images and digital images (Yao et al, 2022). Analog Images and Digital Images Analog images are produced using analog tools, such as analog video cameras, CT scans, analog photo cameras, x-ray sensors for thorax photos, cams, short wave sensors in radar systems, ultrasound sensors in ultrasound systems, and others. -other (Tarpley et al., 2021).
Implementasi Teknologi Informasi untuk Meningkatkan Strategi Penjualan pada UKM Driply Coffee Berbasis Online Wahyuni, Linda; Hardianto, Hardianto; Rosnelly, Rika; Syahrian, Achmad; Rahmadi, Diky
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 1 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Small and medium enterprises (SMEs) are similar to the category of Small and medium enterprises (SMEs), but are usually used to refer to small and medium enterprises only, without including micro businesses. Community service carried out at UKM Driply Coffee, which provides types of drinks in the form of coffee and several other types of drinks besides, also providing food that can accompany customers when they come and sit down to relax either alone, with friends, colleagues, or with family. The research conducted looked at the process of its marketing system, which uses social media such as Facebook, Instagram, and also WhatsApp. The system is indeed seen by many customers, only the process for ordering and selecting menus and the payment process cannot all be seen in the display due to the limitations of the image display, from the presentation of these conditions this research was conducted for approximately 3 months, and will be designed and implemented an online-based application that uses a web program and a MySQL database. Customers can access remotely and can also make payments online, and delivery of drinks or food will be carried out according to the intended location. The convenience felt is not only for customers, but partners will also get convenience and be able to compete in the world of small and medium enterprises (UKM).
Implementasi Teknologi Informasi untuk Meningkatkan Strategi Penjualan pada UKM Driply Coffee Berbasis Online Wahyuni, Linda; Hardianto, Hardianto; Rosnelly, Rika; Syahrian, Achmad; Rahmadi, Diky
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 1 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methabdi.Vol5No1.pp7-12

Abstract

Small and medium enterprises (SMEs) are similar to the category of Small and medium enterprises (SMEs), but are usually used to refer to small and medium enterprises only, without including micro businesses. Community service carried out at UKM Driply Coffee, which provides types of drinks in the form of coffee and several other types of drinks besides, also providing food that can accompany customers when they come and sit down to relax either alone, with friends, colleagues, or with family. The research conducted looked at the process of its marketing system, which uses social media such as Facebook, Instagram, and also WhatsApp. The system is indeed seen by many customers, only the process for ordering and selecting menus and the payment process cannot all be seen in the display due to the limitations of the image display, from the presentation of these conditions this research was conducted for approximately 3 months, and will be designed and implemented an online-based application that uses a web program and a MySQL database. Customers can access remotely and can also make payments online, and delivery of drinks or food will be carried out according to the intended location. The convenience felt is not only for customers, but partners will also get convenience and be able to compete in the world of small and medium enterprises (UKM).
Computer Vision Technology Innovation Education to Support Early Warning Systems for Rice Diseases Saptha Negoro, Wahyu; Adinda Destari, Ratih; Hendra Azhar, Asbon; Syahrian, Achmad
Majalah Ilmiah UPI YPTK Vol. 32 (2025) No. 2
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jmi.v32i2.199

Abstract

Rice plant diseases are one of the main factors causing decreased productivity and threatening national food security. Farmers' limited knowledge in recognizing early symptoms of disease often leads to delays in treatment. The results of this research are educated in community service with the aim of developing and implementing Computer Vision-based technological innovation education to support an early warning system for rice diseases. The methods used include collecting rice leaf images in the field, digital image processing, and applying Computer Vision models to recognize visual patterns of disease symptoms. Educational activities with students are carried out through training and mentoring for farmers and agricultural extension workers regarding the use of this technology as an early detection tool. The expected results of this service are increased understanding and ability of users or partners in identifying rice diseases more quickly and accurately, so that they can support appropriate decision-making in disease control and increase rice agricultural productivity in a sustainable manner.
Combination of Active Contour and CNN-based Segmentation Methods to Improve Accuracy in Detecting Rice Diseases Saptha Negoro, Wahyu; Adinda Destari, Ratih; Hendra Azhar, Asbon; Syahrian, Achmad
Jurnal KomtekInfo Vol. 12 No. 4 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i4.671

Abstract

Rice diseases are one of the main factors causing decreased productivity and threatening national food security. The main problem in controlling rice diseases is the delay and inaccuracy of symptom identification in the field. This study aims to develop an artificial intelligence-based rice disease detection system through a combination of Active Contour and Convolutional Neural Network (CNN) methods. The research object is rice leaf images taken from rice fields in Pulau Sejuk Village, Batubara Medan, with a dataset of 600 images consisting of healthy leaves and 3 types of rice diseases. The Active Contour method is used in the segmentation stage to extract leaf areas precisely, while CNN is applied for the disease classification process. The results show that this combination of methods can significantly improve the accuracy of rice disease detection. The developed system is expected to assist farmers and stakeholders in the early detection of rice diseases, thereby supporting food innovation and increasing sustainable agricultural productivity.
Co-Authors Adinda Destari, Ratih Azhar, Asbon Hendra HARDIANTO - Hendra Azhar, Asbon Mochammad Imron Awalludin Negoro, Wahyu Sapta Rahmadi, Diky Ratih Adinda Destari, Ratih Adinda Rika Rosnelly, Rika Saptha Negoro, Wahyu Wahyuni, Linda