1,720,962 research outputs found
Digital regional language dictionary of Gayo-Batak
No full textIn Indonesia we have unity language of nation that is Bahasa Indonesia and for the tribe community of Gayo and Batak have
a special language area that is Gayo and Batak language. Nowadays, most of the community are no longer familiar with Gayo
and Batak language, due to the influence of free social language this language of Gayo dan Batak dissapeared. The writer tries to
make an aplication design as dictionary of Gayo language to preserve the language through smartphone aplication. We know the
dictionary in the form of books has been widely circulated in the market today, but it will take long time and has short of
vocabularies in finding of words. Therefore, here the writer has designed the dictionary in smartphone aplication. In
accomplishment the design of Gayo batak dictionary has several parts, they are UML, it will explain about the design of the
application system as the part of UML is use case diagram, and the display designed which will explain about the design of the
initial appearance of the application to the end of the application. This application can be implemented on smartphone with
version 4.2.2 or more, it requires memory space of 20,225 Bytes, for a capacity of 1 KB will be able to accommodate about 9
records of words. For development of application, it has the following suggestions are: reproduce the translation database, this
app can be uploaded to Market or Play Store on smartphone, it can be added with voice searching facility and can also display
the translation result by voice
Digital regional language dictionary of Gayo-Batak
No full textIn Indonesia we have unity language of nation that is Bahasa Indonesia and for the tribe community of Gayo and Batak have a
special language area that is Gayo and Batak language. Nowadays, most of the community are no longer familiar with Gayo and
Batak language, due to the influence of free social language this language of Gayo dan Batak dissapeared. The writer tries to make
an aplication design as dictionary of Gayo language to preserve the language through smartphone aplication. We know the
dictionary in the form of books has been widely circulated in the market today, but it will take long time and has short of
vocabularies in finding of words. Therefore, here the writer has designed the dictionary in smartphone aplication. In
accomplishment the design of Gayo batak dictionary has several parts, they are UML, it will explain about the design of the
application system as the part of UML is use case diagram, and the display designed which will explain about the design of the
initial appearance of the application to the end of the application. This application can be implemented on smartphone with version
4.2.2 or more, it requires memory space of 20,225 Bytes, for a capacity of 1 KB will be able to accommodate about 9 records of
words. For development of application, it has the following suggestions are: reproduce the translation database, this app can be
uploaded to Market or Play Store on smartphone, it can be added with voice searching facility and can also display the translation
result by voice
Application of PCA and K-Means Clustering Methods to Identify Diabetes Mellitus Patient Groups Based on Risk Factors
Full text linkDiabetes mellitus is a chronic disease characterized by high levels of glucose (sugar) in the blood that is high for a long period of time. Identification is the process of recognizing and determining the characteristics of a particular object or entity. hypertension (high blood pressure), smoking and lack of physical activity can affect the condition of diabetes mellitus patients. Therefore, an approach is needed that can identify groups of diabetic patients based on their risk factors, so that appropriate management and treatment can be carried out. The purpose of this study is to apply PCA method by reducing data dimension to identify the linear combination of the most contributing risk factors in diabetes mellitus patient data and apply K-Means Clustering to cluster into groups based on similar risk factors. The methods to be used are Principal Component Analysis (PCA) and K-Means Clustering. type of quantitative research, this research can be categorized as analytic research, variables are risk factors for diabetes mellitus disease. The results of research using the PCA (principal component analysis) method obtained 9 main components (PC) 86.9275%. correlation between attributes and principal components, then a matrix component is formed with a loading value that the greater the value, the stronger the correlation with the principal component formed with a cut off point of loading value> 0.4 regardless of positive and negative. By using the K-Means Clustering method, The clustering results obtained are divided into 3 groups of diabetes patients based on existing risk factors. Centroid C1 represents a group of diabetes mellitus patients whose condition is at a mild level, while Centroid C2 represents a group of diabetes mellitus patients who are at a moderate level, and Centroid C3 represents a group of patients with severe or dangerous diabetes mellitus
Detecting Data Leakage in Cloud Storage Using Decision Tree Classification
Full text linkData leakage in cloud storage systems poses a significant security threat, potentially leading to unauthorized access, loss of sensitive information, and operational disruptions. This research proposes a classification model for detecting potential data leakage incidents using the Decision Tree algorithm. The dataset, obtained from the Kaggle public repository, contains user activity logs representing both normal and anomalous behaviors in cloud storage environments. Several preprocessing steps were applied to improve model quality, including handling missing values, removing outliers, and converting categorical data into numerical form. Hyperparameter optimization was performed using GridSearchCV to determine the best configuration for the Decision Tree classifier. Experimental results demonstrate that the optimized model achieved high classification performance, with an accuracy of 70,84%, a precision of 55% for the data leakage class, and an F1-score of 40%. The analysis also highlights the significance of certain features, such as multi-factor authentication usage and access to confidential data, in predicting potential leakage events. This study provides a theoretical contribution by \establishing a robust methodology for applying Decision Tree algorithms to a novel cloud security dataset, offering a scalable and interpretable framework for automated threat detection
Comparison of Apriori and FP-Growth Algorithms in Analyzing Association Rules
Full text linkThe problem objectives of this research include the following: To implement Apriori and FP-Growth Algorithms in determining the comparison of association rules and To build a jupyter notebook application model in determining the comparison of association rules of Apriori and FP-Growth Algorithms. This research compares Apriori and FP-Growth algorithms in analyzing association rules, with a focus on implementation and model development in Jupyter Notebook. Through manual calculation using 10 transaction data samples and testing on 38,765 groceries data entries from Kaggle, differences were found in the lift results between itemsets. Apriori algorithm often shows a negative relationship between items, while FP-Growth gives a similar interpretation but with slightly different lift values, showing a different influence in the relationship between items. In addition, FP-Growth proved to be more efficient with a much faster execution time (5.2757 seconds) than Apriori (185.9585 seconds), especially in handling large datasets. The results of this study indicate that the selection of an appropriate algorithm should consider the characteristics of the dataset and the purpose of the analysis
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
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