Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Knowledge Engineering and Data Science Jurnal Informatika Progres
Yuningsih, Nia
Unknown Affiliation
Computer Science & IT Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Stacked LSTM-GRU Long-Term Forecasting Model for Indonesian Islamic Banks Sujatna, Yayat; Karno, Adhitio Satyo Bayangkari; Hastomo, Widi; Yuningsih, Nia; Arif, Dody; Handayani, Sri Setya; Kardian, Aqwam Rosadi; Wardhani, Ire Puspa; Rere, L.M Rasdi
Knowledge Engineering and Data Science Vol 6, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v6i22023p215-250

Abstract

The development of the Islamic banking industry in Indonesia has become a significant concern in recent years, with rapid growth in the number of banks operating based on Sharia principles. To face emerging challenges and opportunities, a deep understanding of the long-term financial behavior of Islamic banks is becoming increasingly important. This study aims to predict the share price of PT Bank Syariah Indonesia Tbk, over 28 days using the LSTM-GRU stack. The observation stage includes importing the dataset, data separation, model variations, the training process, output, and evaluation. Observations were conducted using 10 model variations from 4 stacks of LSTM and GRU. Each model performs the training process in four epochs (200, 500, 750, and 1000). The results of observations in this study show that long-term predictions (28 days ahead) using four stacks of LSTM-GRU and daily training accumulation techniques produce better accuracy than the general method (using multiple outputs). From the observations we have made for predictions for the next 28 days, the model with the LGLG stack arrangement (LSTM-GRU-LSTM-GRU) produces the best accuracy at epoch 750 with an MSE LSTM-GRU 63.43762863. This study will undoubtedly continue in order to achieve even better precision, either by utilizing a new design or by further improving the technology we are now employing.
PENERAPAN METODE PROTOTYPE DALAM PENGEMBANGAN WEBSITE KONVERSI GAMBAR VEKTOR KE MODEL 3D Yuningsih, Nia; Rachman, Zaidan Ramadhan; Prananingrum, Lely
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.538

Abstract

This research aims to design and build a static website capable of automatically converting SVG vector images into 3D objects. The main problem addressed is the lack of user-friendly and efficient web-based tools for converting SVG files into 3D models, which are important for 3D designers and 3D printing. The development applies the Prototype method, allowing initial prototypes to be tested and refined based on user feedback. The website is developed using JavaScript with the Three.js library for 3D object processing and visualization, and Vite as a modern development tool to ensure responsiveness. Users are able to upload SVG files, adjust object thickness, preview the conversion in real-time, and export the 3D model in STL format. The results show that this website provides a practical and interactive solution for users who require fast conversion from SVG images to 3D objects through a web platform, accessible at https://sv3dkonversi.xyz. User Acceptance Testing was conducted and achieved a score of 82.2%, indicating that users can operate the website effectively in terms of layout, interface, system, and ease of use. This demonstrates the potential of the website to support 3D designers in digital manufacturing and 3D printing workflows.
Co-Authors Arif, Dody Bayangkari Karno, Adhitio Satyo Handayani, Sri Setya Ire Puspa Wardhani Kardian, Aqwam Rosadi Lely Prananingrum Rachman, Zaidan Ramadhan Rere, L.M Rasdi Widi Hastomo Yayat Sujatna, Yayat