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Pengantar Analisis Citra Dokumen Teks Anastasia Rita Widiarti
Dinamik Vol 9 No 2 (2004)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v9i2.631

Abstract

Analisis citra dokumen teks merupakan ilmu yang membahas tentang algoritma-algoritma dan teknik-teknik yang diterapkan pada citra dokumen teks untuk menghasilkan deskripsi yang dapat dikenali oleh komputer. Produk analisis citra dokumen yang selama ini dikenal dengan baik adalah Optical Character Recognition (OCR) yaitu suatu perangkat lunak yang dapat mengenali karakter-karakter dari dokumen yang dibaca dengan mesin scanner.  Dengan OCR pemakai dapat memperbaiki isi dokumen maupun mencari suatu bagian dari isi dokumen. Dalam paper ini, penulis secara singkat menggambarkan tahapan-tahapan dalam analisis citra dokumen teks.
Penelitian Pendahuluan Transliterasi Citra Aksara Bali Menggunakan Ciri Momen Invarian dan Algoritma Klasifikasi SVM atau CNN Anastasia Rita Widiarti
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3195

Abstract

The lontar manuscript is one of the cultural heritages that must be preserved. The lontar manuscript contains many valuable things but is considered no longer exciting and challenging to learn. The study aims to develop a handwritten Balinese script transliteration system from digitizing lontar manuscripts. The peculiarity of this research is the use of research objects and the combination of algorithms used in transliteration. The method used is machine learning with SVM and CNN classification algorithms. 1001 Balinese script images in lontar manuscripts were used as training data. Using the CNN algorithm, an accuracy of 86.42% is obtained, and an accuracy of 82.32% obtains in the SVM algorithm. The model testing was carried out with 18 digitized script images from printed books and obtained an accuracy of 23.53% using the SVM algorithm. The low accuracy value of the testing data is thought to be due to the different shape of the handwritten script imagery with the training data used. This research opens opportunities to be developed by adding training data from various forms of images from different sources. This study also shows that machine learning approaches with SVM and CNN algorithms can potentially be used in developing Balinese script image transliteration systems.
Studi Pendahuluan Pengembangan Aplikasi Augmented Reality Untuk Transliterasi Aksara Jawa Cetak Widiarti, Anastasia Rita
JATISI Vol 11 No 1 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i1.6576

Abstract

The Javanese script as an Indonesian cultural asset must be preserved and disseminated to the current generation so that it is not increasingly lost from memory. Augmented reality (AR) technology has the opportunity to be used in developing interesting applications, because the nature of the technology that combines the real world with the virtual world can attract young people to use it in their daily lives. The chosen AR development method is the Multimedia Development Life Cycle method, and the software tools used are Unity and Vuforia. As a first step, a collection of marker images has been carried out from the segmentation results of the Hamong Tani manuscript on page 2. From the test results on Javanese script objects, it was found that the AR application functions properly and correctly on Javanese script images with the smallest size of 2x2 cm, and the largest at 11x11 cm. For the smallest font size, the distance from the camera to the Javanese script is a minimum of 5 cm and a maximum of 9 cm, while for the largest font size, the distance is a minimum of 18 cm and a maximum of 46 cm.
Implementasi Projection Profile dan Connected Component untuk Segmentasi Citra Manuskrip Beraksara Jawa Cetak Gerardus Kristha Bayu Indraputra; Anastasia Rita Widiarti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

Javanese script is one of Indonesia's cultural heritages. Many ancient manuscripts in Javanese script are still neatly stored in museums and libraries in Indonesia, but only a few people can utilize the important information contained therein. The difficulty of the transliteration process is one of the challenges in obtaining this important information. With the development of document image analysis science, this research was developed to help shorten the process of transliterating Javanese manuscript images. Segmentation is an essential stage in transliterating the manuscript image, namely, automatically taking each script image in a document. This research developed the segmentation process by combining the projection profile and connected component methods. Using one image from a scanned manuscript in the book "Hamong Tani" written using printed Javanese script on page 5, the results of line segmentation with 100% accuracy and the results of Javanese script segmentation with 95.952% accuracy were obtained after preprocessing. From the large segmentation accuracy value, it can be concluded that the projection profile and connected component methods can be used well in segmenting printed Javanese manuscript images.
PENGEMBANGAN UMKM BERBASIS TEKNOLOGI AUGMENTED REALITY UNTUK PENUNJANG PROMOSI DI DESA WISATA PENTINGSARI Widiarti, Anastasia Rita; Pinaryanto, Kartono; Adji, Fransisca Tjandrasih
ABDIMAS ALTRUIS: Jurnal Pengabdian Kepada Masyarakat Vol 7, No 2 (2024): Oktober 2024
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/aa.v7i2.9237

Abstract

This community service project aims to introduce and implement Augmented Reality (AR) technology for Micro, Small, and Medium Enterprises (MSMEs) in Pentingsari Village, Yogyakarta, enhancing their promotional capabilities. The initiative involved local MSME owners, village officials, lecturers, and students collaborating to integrate modern technology with local wisdom. The project used methods such as presentations, discussions, and AR technology demonstrations to identify unique MSME products suitable for AR enhancement and develop tailored AR applications. The results indicate high enthusiasm among participants in adopting AR technology for their product development and marketing strategies. A user survey of the developed AR application showed an overall positive response, with an average rating of 4.26 out of 5 across various aspects, including ease of installation, operation, user interface quality, and 3D model display. This project demonstrates the potential of AR technology to boost competitiveness significantly and add value to MSME products in Pentingsari Village while highlighting areas for future improvement and expansion of the AR application to support local tourism and economic development further.
DEVELOPMENT OF A SMART DOLL PROTOTYPE FOR EARLY AGE CHILDREN COLOURS LEARNING IN THREE LANGUAGES Kurniastuti, Irine; Widiarti, Anastasia Rita; Nugroho, Robertus Adi; Pinaryanto, Kartono
IJIET (International Journal of Indonesian Education and Teaching) Vol 6, No 2 (2022): July 2022
Publisher : Sanata Dharma University Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijiet.v6i2.4825

Abstract

Early childhood is a golden age to learn a language, not only the mother tongue but also a second or third language. However, learning media that can be used to attract children's interest in learning multi-language is still limited. Therefore, this study aims to develop a smart doll that attracts children to learn Javanese, English, and Indonesian. In particular, this media is intended to help children recognise colours in three languages. This research is developmental research with the following steps: First, collecting information about the product being developed, conducting a literature review and interviewing teachers and parents. Second, planning product design in accordance with the results of the needs analysis. Third, developing the initial product form. Fourth, conducting a preliminary field test on 3 children. Fifth, revising the main product. Sixth, field testing on eight children. Seventh, evaluate the testing result for the next development plan. The result of this research is a prototype of a smart doll that is able to recognize colours in 3 languages. Based on the field trials results, the prototype of this smart doll can attract children’s enthusiasm for learning colours and improve their ability to recognise colours in three languages. Some things that need to be improved will be discussed further.
Aplikasi Pengenalan Citra Warna Dasar Yosef Yudha; Dhesa Ardhiyanta; Laurensius Haris; Anastasia Rita Widiarti
Widya Teknik Vol. 15 No. 1 (2016)
Publisher : Fakultas Teknik, Universitas Katolik Widya Mandala Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33508/wt.v15i1.1524

Abstract

Pengenalan warna primer dan sekunder menjadi salah satu hal mendasar yang harus diajarkan kepada seorang anak, karena banyak peraturan yang berlaku di dalam kehidupan hanya disimbolkan dengan warna, demikian juga dengan berbagai hal penting lain yang memerlukan pemahaman mengenai warna. Contoh penggunaan simbol warna adalah pada rambu-rambu peraturan lalu lintas di jalan raya yang berlaku sama di seluruh tempat di dunia ini. Paper ini menyodorkan sebuah contoh aplikasi deteksi warna merah, hijau, biru, cyan, magenta, dan kuning atau warna RGB-CMY pada suatu citra warna masukan. Prinsip yang dipergunakan untuk mendeteksi warna adalah dengan melihat rentang warna setiap piksel di kanal merah, hijau, dan biru. Apabila dalam rentang intensitas warna suatu piksel di setiap kanal berada dalam jangkauan warna tertentu sesuai aturan rentang warna yang ditetapkan, maka piksel tersebut berwarna tertentu. Dari hasil pengujian pada 20 citra data uji, diperoleh informasi bahwa untuk setiap citra masukan dengan tingkat kecerahan yang baik, warna pada citra tersebut dapat dideteksi dengan baik. Namun, untuk citra masukan yang mempunyai intensitas warna keabuan dan hitam, sistem tidak dapat mendeteksi warna yang muncul, karena rentang warna keabuan dan hitam berlaku dari 0 sampai dengan 255.
Implementation of 4-Directional Depth First Search and Projection Profile for Javanese Manuscript Image Segmentation Indraputra, Gerardus Kristha; Anastasia Rita Widiarti
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15433

Abstract

One of the key steps in digitizing Javanese manuscripts is image segmentation, which separates elements such as lines and characters. This study evaluates the Projection Profile and Four-Directional Depth-First Search (4-Directional DFS) methods for segmenting handwritten Javanese script. The Projection Profile method is used for line segmentation, while 4-Directional DFS identifies interconnected pixels for character segmentation. A total of 20 scanned images were randomly selected from Serat Pratanda and Serat Primbon Reracikan Jampi Jawi. After grayscale conversion and binarization, each image underwent two treatments: with and without advanced preprocessing, before segmentation. Results showed that line segmentation achieved 100% accuracy in both treatments. Character segmentation reached 91.02% accuracy with advanced preprocessing and 84.28% without it. Segmentation errors were mainly caused by over-segmentation and under-segmentation. These results demonstrate that the Projection Profile and 4-Directional DFS methods are effective in segmenting handwritten Javanese manuscripts. They show promise for supporting future developments in automatic Javanese script transliteration.
Enhancing Visibility in Low-Illumination Street Images Using HE, AHE, and CLAHE Techniques Putra Pratama, Fernandous; Anastasia Rita Widiarti
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15451

Abstract

Low-quality images, such as those resulting from digital capture under low-light conditions, present a significant challenge in the field of digital image processing. This study aims to enhance image visual quality using three contrast enhancement methods: Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), and Contrast Limited Adaptive Histogram Equalization (CLAHE). The dataset consists of 110 grayscale-converted street images captured under various lighting conditions (morning, noon, night, rainy, and clear weather). Evaluation was conducted using objective metrics, including Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), execution time, and subjective assessment from 35 respondents. The results show that CLAHE consistently produces the best visual quality, achieving the highest PSNR of 12.93 dB and the lowest MSE of 3310.28 on a 32×32 grid, with an average execution time of 2–25 seconds. In comparison, HE recorded the lowest PSNR of 8.07 dB and the highest MSE of 10119.23, but had the fastest runtime of 0.3–0.4 seconds. AHE had the longest processing time, reaching up to 103 seconds, with inconsistent output quality. Based on user preference, 65% of respondents favored AHE, despite CLAHE being objectively superior. This study confirms CLAHE as the most effective method for enhancing image quality under extreme lighting conditions without sacrificing important visual details.