Statistical Analysis of Performance Goals Effect to Lecturer Work Achievement in Higher Education

Ibrahim, Muhdi B. Hi; Jufri, Muhammad; Alam, Sitti Nur; Zakaria,; Akbar, Muhammad Aldrin; Budiman, Edy

doi:10.1109/eiconcit.2018.8878571

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…Data analysis used descriptive statistics and Pearson's bivariate correlation analysis [17]. Descriptive analysis is used to describe the results of measuring participants' perceptions, including validity testing.…”

Section: Data Analysis Techniquementioning

confidence: 99%

Mobile Data Usage on Online Learning during COVID-19 Pandemic in Higher Education

Budiman

2020

Int. J. Interact. Mob. Technol.

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Information about network availability and the amount of internet data usage is very important for planning and implementing management of free internet data assistance programs in the COVID-19 pandemic for students. Research Objectives to analyze for the mobile data usage in online learning (Zoom cloud meetings apps) during the COVID-19 pandemic at Higher Education institutions. The results study revealed that access to online learning using the Zoom cloud meeting apps for 1-minute internet data usage of 5.02bB for a meeting duration of 40 minutes and for a meeting duration of 60 minutes (1 hour) of 13.66 Mb. The measurement results are then used as a reference in the internet data assistance program for students as an effort in supporting the online learning process (Learning-From-Home), objective and proportionate in its distribution to beneficiaries

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Section: Data Analysis Techniquementioning

confidence: 99%

Mobile Data Usage on Online Learning during COVID-19 Pandemic in Higher Education

Budiman

2020

Int. J. Interact. Mob. Technol.

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“…This type of quantitative research, where data is collected, is recorded, compiled, and presented in tabular form [4], [5], which is then measured in statistical values to prove the truth of the theory. This research was conducted to classify the fixed voter list data to determine how many beginner voters in a sub-districts by clustering beginner voters between 17 and 20 years of age.…”

Section: Introductionmentioning

confidence: 99%

Fixed Voters Clustering to Determine the Level of Beginner Voters Using Data Mining Techniques

Hairah

2020

ETJ

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Data mining clustering technique is used to classify the level of beginner voters using the K-Means method. Fixed voter clusters are used for decision making for stakeholders regarding information on beginner voters in each district and sub-district. The error calculation method is used to measure the level of error value for each distance calculation used, the distance calculation method used ie Euclidean, Manhattan, and Minkowski Distance with the Means Square Error (MSE) approach to measure the level of the error value. The calculation results show that the lowest error occurs in the calculation of the Minkowski Distance model 3 cluster, where the error rate is 11%, while the highest error rate occurs in the calculation of the Manhattan Distance model 5 cluster, which is 38%.

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“…Weighting methods are classified in a variety of different ways, found in [9], i.e: holistic or unravelled, direct or indirect, statistical or algebraic, and compensatory or non-compensatory. Further, according to [9] several popular weighting methods such as the ranking method include scoring, point allocation, pairwise comparison [11], outranking method, trade-off analysis and others, each of which is different in terms of complexity, accuracy, convenience for users, and theoretical foundation, as well as generating a different set of criterion weights [9].…”

Section: Introductionmentioning

confidence: 99%

Importance weighted Ranking Methods for Preference the Covid 19 Pandemic Social Assistance

Budiman¹

2020

IJEAT

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Issues importance-weighted value is a critical aspect of decision making. Differences in weight, even the slightest change in weight assignment, can drastically change the final decision. Moreover, in the case of distributing social assistance during the Covid-19 pandemic, objectivity and accuracy of weighting the criteria for potential recipients are very important applied for the welfare of the community. The proposes study 3 popular models of ranking methods for weighting criteria in the internet data package assistance cases. Weighting is given to 390 alternatives with 5 decision-making criteria based on online learning needs and economic cost capabilities. The decision analysis method uses the reference point and optimization from Moora. The study results were found accuracy, precision and error rate performance each method using a confusion matrix approach. The study results discussed raised several important points of findings, that the three ranking methods (RS, RR, ROD) have their respective characteristics in weighting importance, where the level of accuracy and precision of the rank-sum method is better than the RR and ROD methods (for the case: 5 criteria; 390 alternatives). Other things in giving weight value from important to most important are comparable, and the weight value of the non-benefit (cost) criteria in the ranking method have a significant effect on performance results. These three methods are simple in use and with the assessment of replacement weights that can be determined how important these variables are to the principal of these criteria.

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Statistical Analysis of Performance Goals Effect to Lecturer Work Achievement in Higher Education

Cited by 3 publications

References 2 publications

Mobile Data Usage on Online Learning during COVID-19 Pandemic in Higher Education

Mobile Data Usage on Online Learning during COVID-19 Pandemic in Higher Education

Fixed Voters Clustering to Determine the Level of Beginner Voters Using Data Mining Techniques

Importance weighted Ranking Methods for Preference the Covid 19 Pandemic Social Assistance

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