1,720,963 research outputs found
TINJAUAN SISTEMATIS ANALISIS SENTIMEN DENGAN METODE PRISMA (2021–2025)
Full text linkThis study presents a systematic review of sentiment analysis research conducted between 2021 and 2025 using the PRISMA method. From searches across three databases, namely Google Scholar, Semantic Scholar, and Garuda, a total of 12,089 articles were identified and then filtered down to 30 selected studies. The aim of this study is to identify the methods, algorithms, data sources, and accuracy levels used in sentiment analysis research. The findings indicate that the Naïve Bayes algorithm is the most widely applied, followed by SVM, while other algorithms such as KNN, Random Forest, Logistic Regression, and CNN were used only in limited cases. These findings highlight that sentiment analysis remains largely directed toward digital and social media issues, with classical algorithms such as Naïve Bayes and SVM continuing to be the main choices due to their ease of implementation and competitive accuracy
Exploring The Role of Augmented Reality in Education: Systematic Literature Review
Full text link The development of digital technology drives innovation in education, one of which is through the implementation of augmented Reality (AR), which increases interactivity and understanding of abstract concepts in learning. This study employs a Systematic Literature Review (SLR) with the PRISMA method to analyze the implementation of AR in education. Of the 3,225,372 articles reviewed, 30 journals met the research criteria, with Marker-Based Tracking as the most commonly used AR method because of its stability and accuracy. The study results showed that AR increases students\u27 interactivity, facilitates understanding of abstract concepts, increases student engagement, improves information retention and memory, facilitates simulation and practice, develops creativity and collaboration, adapts learning to individual needs, and improves cost and resource efficiency, although it still faces challenges in the infrastructure and technical skills of teachers. Therefore, further development in AR applications at various education levels is recommended to improve understanding and adaptation to scientific developments.
Keywords: Augmented Reality, Learning Media, Marker-Based Tracking
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
ALGORITMA K-MEANS DALAM IMPLEMENTASI BIDANG PEKERJAAN
Full text linkRapid technological advances have affected various fields, especially in data management. The increasing volume of data generated from various sources demands efficient management and analysis methods. Data mining techniques offer a structured approach in processing, classifying, and grouping data to support decision making in various fields. This study is a systematic review of the application of data mining techniques, with a primary focus on the K-Means Clustering algorithm. This study analyzes the trend of data mining applications, especially in data classification and grouping to improve the effectiveness of decision making. Based on a systematic literature review, it was found that the K-Means Clustering algorithm is widely applied in sales analysis, market segmentation, stock optimization, and predictions in the social and health fields. In addition, other algorithms such as Decision Tree, Naïve Bayes, and K-Nearest Neighbor are also commonly used in predictive analysis and data classification. This study provides insight into the effectiveness of various data mining techniques and their future development opportunities
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