Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal SAGA: Journal of Technology and Information Systems
Ade Eviyanti
Department of Informatics, Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science

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

Found 3 Documents
Search

 1 
Android-based Programming Language to Natural Language Translator App Rosydah Rihadhatu Aisyiyah; Ade Eviyanti
SAGA: Journal of Technology and Information System Vol. 3 No. 1 (2025): February 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i1.476

Abstract

Translation between programming languages and natural languages is an important solution to improve the understanding of coding in informatics students who often have difficulty understanding the syntax rules of programming languages. This research develops a translator application that is integrated with OCR technology and uses GPT Chat API to automatically translate text. This application supports seven programming languages (Python, Kotlin, CSS, Dart, HTML, Javascript, and Java) and two natural languages (Indonesian and English). This research uses the Waterfall software development method, starting from requirements analysis, system design, implementation, to testing using the blackbox method. The results show that this application can help users understand coding more effectively and efficiently through translation features, interactive quizzes, and user activity history. Thus, this application has the potential to be an innovative learning media that improves the programming skills of informatics students.
Web-based Population Information System (Case Study of Ketapang Village Hall Office) Irene Elvariani Dewanti; Rohman Dijaya; Nuril Lutvi Azizah; Ade Eviyanti
SAGA: Journal of Technology and Information System Vol. 3 No. 1 (2025): February 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i1.477

Abstract

The development of information technology has brought significant changes in various aspects of life, including in the management of population data at the village level. Conventional population information systems that still use manual methods often have various problems such as data inconsistency, difficulty in finding information, and slow administrative service processes. Therefore, this research aims to develop a web-based village population information system that can overcome these problems. This web-based population information system is designed using a waterfall system development approach. Data collection methods were conducted through interviews, observations, and documentation studies. The system was built using PHP programming language and MySQL database. The results showed that this web-based population information system is able to present population data accurately, quickly, and easily accessible by the community and village officials. With this web-based population information system, it is expected to improve the efficiency and effectiveness of population data management at the village level, as well as provide convenience for the community in accessing information and obtaining population administration services.
Classification of Ceramic Roof Tiles Using the CNN Method Achmad Danu Zakaria; Ade Eviyanti; Metatia Intan Mauliana; Azmuri Wahyu Azinar
SAGA: Journal of Technology and Information System Vol. 3 No. 2 (2025): May 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i2.511

Abstract

The research on tile classification using Convolutional Neural Network (CNN) aims to improve and address issues in the sorting process within the tile manufacturing industry. The accuracy level in manual sorting processes is very low due to errors caused by visual limitations and physical fatigue. By leveraging the capabilities of Convolutional Neural Network (CNN), a model was developed to classify tiles. This research involved several processes, including literature review, dataset collection, dataset splitting, preprocessing, Convolutional Neural Network (CNN) design, training, testing, and result evaluation. The study used 69 tile images divided into three classes: KW 1, KW 2, and KW 3. The results of testing the Convolutional Neural Network (CNN) on tile classification using 100 epochs with a data split of 90% training and 10% validation yielded an accuracy rate of 100%.
Co-Authors Achmad Danu Zakaria Azmuri Wahyu Azinar Irene Elvariani Dewanti Metatia Intan Mauliana Nuril Lutvi Azizah Rohman Dijaya Rosydah Rihadhatu Aisyiyah