The Use of Modern Technology

Oct 13, 2025 by pynkocean.com 34 views

Android-based Application for Classification of Batak Ulos Fabrics using the R-CNN Faster Algorithm

Introduction

Ulos cloth is a rich cultural symbol of the Batak tribe living in Indonesia. This fabric not only functions as a traditional clothing but also has a deep meaning in various traditional ceremonies, such as marriage, and can be used in everyday life as a body warmer. Over time, ulos cloth is increasingly known throughout the world. However, many people only know Ulos as a traditional cloth without knowing their rich origin, because the Batak tribe consists of various sub-tribes with different fabric characteristics.

The Importance of Ulos Fabric Classification

In recent years, the Batak tribe has been working to preserve their cultural heritage, including their traditional fabrics. However, the lack of knowledge about the different types of ulos fabrics and their origin has made it difficult for the community to promote and preserve their cultural heritage. This is where the development of an Android-based application for classification of Batak ulos fabrics using the R-CNN Faster algorithm comes in.

What is the R-CNN Faster Algorithm?

The R-CNN Faster algorithm is a deep learning algorithm used for object detection in images. It is a type of convolutional neural network (CNN) that is designed to detect objects in images with high accuracy and speed. The algorithm works by first generating region proposals, which are potential locations where objects may be present in the image. These region proposals are then classified using a neural network to determine whether they contain an object or not.

Benefits of Ulos Fabric Classification Application

The development of an Android-based application for classification of Batak ulos fabrics using the R-CNN Faster algorithm has several benefits, including:

Cultural Education

This application can increase public awareness about the diversity of ulos fabrics and the importance of preserving Batak culture. With a clear classification, users can understand more about each type of fabric and its function in tradition.

The Use of Modern Technology

Society is now increasingly accustomed to technology. With the presence of this application, users can easily identify and classify ulos fabrics just by scanning images through their smartphones.

Ulos Fabric Promotion

With clear information about the origin and type of ulos fabric, the potential of this fabric to be marketed to the global market will also increase. This can have a positive impact on the economy of the Batak community.

Preservation of Cultural Heritage

In this way, knowledge about traditional fabrics can be passed on to future generations.

How the Application Works

The application works by using the R-CNN Faster algorithm to classify ulos fabrics based on their images. The user simply needs to upload an image of the ulos fabric, and the application will automatically classify it based on its characteristics.

Conclusion

The development of an Android-based application for classification of Batak ulos fabrics using the R-CNN Faster algorithm is an innovative step that can have a positive impact on the community. In addition to facilitating fabric identification, this application also serves to preserve culture, increase public awareness, and encourage promotion of ulos cloth at the international level. That way, ulos fabric will not only be known as a traditional cloth, but also as a valuable cultural heritage of the Batak tribe.

Future Directions

The development of this application is just the beginning. Future directions for this project include:

Improving the Accuracy of the Algorithm: The accuracy of the R-CNN Faster algorithm can be improved by training it on a larger dataset of ulos fabrics.
Expanding the Application to Other Types of Fabrics: The application can be expanded to classify other types of fabrics, such as batik or songket.
Developing a Web-Based Version of the Application: A web-based version of the application can be developed to make it more accessible to a wider audience.

Conclusion

In conclusion, the development of an Android-based application for classification of Batak ulos fabrics using the R-CNN Faster algorithm is a significant step towards preserving the cultural heritage of the Batak tribe. The application has several benefits, including cultural education, the use of modern technology, ulos fabric promotion, and preservation of cultural heritage. Future directions for this project include improving the accuracy of the algorithm, expanding the application to other types of fabrics, and developing a web-based version of the application.
Frequently Asked Questions (FAQs) about Android-based Application for Classification of Batak Ulos Fabrics using the R-CNN Faster Algorithm

Q: What is the purpose of the Android-based application for classification of Batak ulos fabrics using the R-CNN Faster algorithm?

A: The purpose of the application is to classify and identify Batak ulos fabrics using the R-CNN Faster algorithm, which is a deep learning algorithm used for object detection in images. This application aims to help the general public better recognize and understand various types of ulos fabrics and their origin.

Q: How does the R-CNN Faster algorithm work?

A: The R-CNN Faster algorithm works by first generating region proposals, which are potential locations where objects may be present in the image. These region proposals are then classified using a neural network to determine whether they contain an object or not.

Q: What are the benefits of using the R-CNN Faster algorithm for ulos fabric classification?

A: The benefits of using the R-CNN Faster algorithm for ulos fabric classification include:

High accuracy in detecting objects in images
Good speed in processing images
Ability to detect objects with complex shapes and textures

Q: How does the application classify ulos fabrics?

A: The application classifies ulos fabrics based on their images. The user simply needs to upload an image of the ulos fabric, and the application will automatically classify it based on its characteristics.

Q: What types of ulos fabrics can be classified using the application?

A: The application can classify various types of ulos fabrics, including:

Traditional ulos fabrics
Modern ulos fabrics
Ulos fabrics with unique patterns and designs

Q: Can the application be used for other types of fabrics besides ulos?

A: Yes, the application can be expanded to classify other types of fabrics, such as batik or songket.

Q: Is the application available for download?

A: Yes, the application is available for download on the Google Play Store.

Q: What are the system requirements for running the application?

A: The system requirements for running the application include:

Android 5.0 or later
2GB of RAM or more
1GB of storage space or more

Q: Can I use the application offline?

A: Yes, the application can be used offline. However, the application requires an internet connection to download the R-CNN Faster algorithm and to access the database of ulos fabrics.

Q: How can I provide feedback or report issues with the application?

A: You can provide feedback or report issues with the application by contacting the developer through the application's contact page or by sending an email to the developer's email address.

Q: Is the application free to use?

A: Yes, the application is free to use. However, the application may display ads to support its development and maintenance.

Q: Can I use the application for commercial purposes?

A: Yes, you can use the application for commercial purposes. However, you must obtain permission from the developer before using the application for commercial purposes.

Q: How can I contribute to the development of the application?

A: You can contribute to the development of the application by providing feedback, reporting issues, or by contributing code to the application's open-source repository.