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All Journal Jurnal Statistika dan Matematika (Statmat) JOURNAL OF ICT APLICATIONS AND SYSTEM Journal Of Indonesian Social Society RJOCS (Riau Journal of Computer Science)
Fauzi Erwis
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : JOURNAL OF ICT APLICATIONS AND SYSTEM

 1 
Classification of Capsicum Varieties Using Color Analysis with Convolutional Neural Network Azzahra, Tantia; Riski Rahmadan; Fernanda Abi Maulana; Ismi Asmita; Efendi Rahayu; Fauzi Erwis
Journal of ICT Applications System Vol 3 No 2 (2024): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jictas.v3i2.394

Abstract

Paprika (Capsicum annuum L.) is a high-value horticultural commodity widely consumed for its nutritional content and vibrant color variations. In the agricultural industry, classifying paprika varieties based on color is crucial for ensuring product quality and optimizing sorting processes. This study developed an automated classification system for three main paprika varieties—red, green, and yellow—using the Convolutional Neural Network (CNN) method. The dataset consisted of 1,820 images sourced from Kaggle, with data split into 60% for training and 40% for validation. Preprocessing steps included resizing images, normalizing pixel values to the range [0,1], and data augmentation techniques such as rotation, flipping, and brightness adjustments to enhance dataset diversity and reduce the risk of overfitting. The CNN model was designed with key layers, including convolutional, pooling, and fully connected layers, optimized using the Adam algorithm and categorical cross-entropy loss function. The training results showed an accuracy of 99.9% on the training data and 92% on the testing data, with an average processing time of 64 seconds per image and a maximum of 78 seconds, demonstrating the model's efficiency for real-time applications. The k-fold cross-validation technique was also employed to ensure the model's generalization ability to new data. This study demonstrated that CNN is an effective method for classifying paprika varieties based on color analysis, offering an accurate, fast, and scalable solution for automating sorting and grading processes in the agricultural sector, reducing human errors, and improving operational efficiency.
Visualization of Sales Danalyser Data in Dashboard Form Google Data Studio Agung Surya Maulana; yanto, Budi Yanto; Fauzi Erwis
Journal of ICT Applications System Vol 2 No 2 (2023): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jictas.v2i2.270

Abstract

In the business sector, the use of information technology is used as a means of supporting company performance. Data visualization is the answer to simplifying complex data into a graphical format so that it is easier to understand the business. Managing sales data is an important process that must be carried out by companies. With good data management, companies get more value. This added value includes information supporting decision making, in order to increase the efficiency and effectiveness of company operations. This research uses data on sales of goods obtained from the internet, namely 69 data. The research was carried out with the help of Google Data Studio tools for creating dashboards. The results obtained are that there are several elements that help make it easier to read information, namely scorecard elements, Pie Chart elements, bar chart elements, geographic diagram elements, and table elements. The Scorecard element displays total income, average price of goods, total items sold, and total buyers. In the Pie Chart, the product insight is displayed in percent, the items that sell best are P010. The bar chart element displays total sales for each month, the highest sales were in August 2021. The geographic diagram element displays the distribution of sales to various countries. The table element displays insight information on price cuts or discounts.
Co-Authors Agung Setiawan AGUNG SETIAWAN Agung Surya Maulana Ambiyar, Ambiyar Azzahra, Tantia Efendi Rahayu Fernanda Abi Maulana Firman Santosa Hafiz Maulana Hariyen Ulfa Ismi Asmita Jufri Luth Fimawahib Riski Rahmadan Rohima Safrudin Sri Wahyudi Syahril Syahril yanto, Budi Yanto YULIANI