Text Mining an Automatic Short Answer Grading (ASAG), Comparison of Three Methods of Cosine Similarity, Jaccard Similarity and Dice's Coefficient

Wahyuningsih, Tri Agung; Henderi, Henderi; Winarno, Winarno

doi:10.47738/jads.v2i2.31

Cited by 19 publications

(14 citation statements)

References 12 publications

(12 reference statements)

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“…Results in [4] tells that the NB method is more accurate than J48 DT to categorize agriculture datasets since it classifies 98 percent of occurrences correctly. An experiment is undertaken in the health domain to classify 3163 patients' data as indicated in [15]. Naïve Bayes (NB), Bayesian Network (BayesNet), J Ripper (JRip), One Rule (OneR), and PART classification methods are utilized.…”

Section: Methodsmentioning

confidence: 99%

“…As another attempt, a comparison analysis is undertaken by Parsania et al [15] to determine the best data mining classification approaches based on healthcare data in terms of accuracy, sensitivity, precision, false-positive rate, and f-measure. Naïve Bayes, Bayesian Network, J RIPPER (JRip), OneRule (OneR), and PART methods are selected to be used on a dataset from a health database.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Brief Overview of the Accuracy of Classification Algorithms for Data Prediction in Machine Learning Applications

Jen

2021

J. Appl. Data Sci.

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Many business applications rely on their history data to anticipate their company future. The marketing products process is one of the essential procedures for the firm. Customer needs supply a useful piece of information that helps to promote the suitable products at the proper moment. Moreover, services are recognized recently as products. The development of education and health services is reliant on historical data. For the more, lowering online social media networks problems and crimes need a big supply of information. Data analysts need to utilize an efficient categorization system to predict the future of such businesses. However, dealing with a vast quantity of data demands tremendous time to process. Data mining encompasses numerous valuable techniques that are used to anticipate statistical data in a number of business applications. The classification technique is one of the most extensively utilized with a range of algorithms. In this work, numerous categorization methods are revised in terms of accuracy in diverse domains of data mining applications. A complete analysis is done following delegated reading of 20 papers in the literature. This study intends to allow data analysts to identify the best suitable classification algorithm for numerous commercial applications including business in general, online social media networks, agriculture, health, and education. Results reveal FFBPN is the best accurate algorithm in the business arena. The Random Forest algorithm is the most accurate in categorizing online social networks (OSN) activity. Naïve Bayes method is the most accurate to classify agriculture datasets. OneR is the most accurate method to classify occurrences inside the health domain. The C4.5 Decision Tree method is the most accurate to classify students' records to forecast degree completion time.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A Brief Overview of the Accuracy of Classification Algorithms for Data Prediction in Machine Learning Applications

Jen

2021

J. Appl. Data Sci.

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“…Knowledge sharing allows for the benefit of knowledge gained by Irum and Pandey [13]. The main reason for sharing individual knowledge with the entire organization is that the knowledge should not disappear if that employee leaves the organization [15]. The organization must put some measures (incentives) in place to ensure knowledge sharing and discourage hoarding and monopoly.…”

Section: Knowledge Sharingmentioning

confidence: 99%

The Role of Knowledge Management in Raising the Saudi Universities Performance Efficiency: An Applied Study on the Administrative Body of King Abdulaziz University

Alsharyofi

2022

IJIIS Int. J. Informatics Inf. Syst.

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This study aimed at identifying the role of knowledge management in raising the efficiency of the performance of the administrative body at King Abdulaziz University. In light of this goal, a number of hypotheses were developed and tested by preparing a questionnaire comprising two variables, namely knowledge management (information technology, organizational culture, organizational structure) and the performance of the administrative body (personal elements, performance elements, knowledge of job requirements). This study was conducted at King Abdulaziz University. The necessary information was obtained through the questionnaire tool prepared for this purpose. Data were collected from 304 individuals of the administrative body of King Abdulaziz University. The results were analyzed using correlation and regression analyzes of the SPSS program. The snowball sample method was relied upon, and the link was sent to a number of the administrative body with a recommendation for them to distribute it among their university colleagues. In light of this, 315 responses were obtained, 11 responses were excluded because they were not valid. Consequently, the responses valid for analysis were 304 questionnaires. Then the student concluded with a set of recommendations related to the research variables.

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“…Many types of medical equipment require consumables and accessories. Therefore, in conjunction with the medical equipment inventory, the healthcare facility should maintain a separate inventory of consumables necessary to operate medical equipment [9]. These include items such as blood tubing sets, electrodes, electrocardiographic (ECG) paper, conductive gel and reagents.…”

Section: Literature Reviewmentioning

confidence: 99%

Implementation of Apriori Data Mining Algorithm on Medical Device Inventory System

Avizenna

2021

J. Appl. Data Sci.

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The pattern of the need for drugs and medical devices in various hospitals has a tendency to be repeated and similar in a relatively long period of time, especially in one particular department, because the cases found are often similar or even similar. Ensuring the availability of stock in each departmental depot is very vital, because the procurement of medical devices must go through a certain process and time, so that cases of critical rheumatism often occur but the equipment needed at depositors does not meet the standards. need or run from inventory and must indent first. By calculating the trend of demand patterns and needs using an algorithm (Apriori Association) in the dataset, a rule is formed that in the pattern of dependence between itemsets that have supporting criteria in the form of 33.3% support and 85% Confidence, where the items that appear are items with frequency of occurrence and associations so that it can be taken into consideration to ensure the availability of drugs and medical devices.

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Text Mining an Automatic Short Answer Grading (ASAG), Comparison of Three Methods of Cosine Similarity, Jaccard Similarity and Dice's Coefficient

Cited by 19 publications

References 12 publications

A Brief Overview of the Accuracy of Classification Algorithms for Data Prediction in Machine Learning Applications

A Brief Overview of the Accuracy of Classification Algorithms for Data Prediction in Machine Learning Applications

The Role of Knowledge Management in Raising the Saudi Universities Performance Efficiency: An Applied Study on the Administrative Body of King Abdulaziz University

Implementation of Apriori Data Mining Algorithm on Medical Device Inventory System

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