Publication Search

Fingerprint recognition is a popular biometric technology due to its unique properties and high accuracy rate. Fingerprint recognition systems generally use fingerprint image representations, such as grayscale images, phase images, skeleton images, and minutiae. In this research, fingerprint image pre-processing is performed using Gaussian Blur, Median Blur, Thresholding, Otsu Thresholding, Thinning with Guo-Hall algorithm, and Minutiae Detection. Minutiae detection produces 426 termination points and 459 bifurcation points. The results of the pre-processing and minutiae detection were then used for minutiae matching on 5 different images. Minutiae matching produces varying degrees of similarity with a high level of accuracy, reaching an average accuracy of 88.80%.

The purpose of this study is to map and analyze the development of zakat accounting research and identify the latest trends developing in this field. This research uses bibliometric approach to achieve the objective, which is by analyzing research publications related to zakat accounting. This approach allows researchers to understand the development of knowledge in the field of zakat accounting and identify future research opportunities. The data source of this research is metadata collected using Google Scholar, covering publications from 2019 to 2024. The metadata was then exported into RIS format and analyzed using VOSviewer software. This study found that the newest topic in zakat accounting research is "Infaq". In addition, "PSAK" and "Research" were identified as emerging themes and predicted to be the focus of research in 2024 and beyond. The bibliometric approach used in this study offers an effective and accessible way for researchers to understand zakat accounting issues and identify potential future research topics. This approach allows the study to gain a better understanding of zakat accounting and paves the way for innovative new contributions in this research.