scholarly journals Parametric Software Effort Estimation Based on Optimizing Correction Factors and Multiple Linear Regression

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ho Le Thi Kim Nhung ◽  
Vo Van Hai ◽  
Radek Silhavy ◽  
Zdenka Prokopova ◽  
Petr Silhavy
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correction Factors ◽  
Effort Estimation ◽  
Software Effort Estimation

Regression Analysis Based Software Effort Estimation Method

2016 ◽  
Vol 26 (05) ◽  
pp. 807-826 ◽  
Author(s):  
Fatih Yücalar ◽  
Deniz Kilinc ◽  
Emin Borandag ◽  
Akin Ozcift
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Estimation Method ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Development Effort ◽  
Software Project ◽  
Effort Estimation ◽  
Software Effort Estimation

Estimating the development effort of a software project in the early stages of the software life cycle is a significant task. Accurate estimates help project managers to overcome the problems regarding budget and time overruns. This paper proposes a new multiple linear regression analysis based effort estimation method, which has brought a different perspective to the software effort estimation methods and increased the success of software effort estimation processes. The proposed method is compared with standard Use Case Point (UCP) method, which is a well-known method in this area, and simple linear regression based effort estimation method developed by Nassif et al. In order to evaluate and compare the proposed method, the data of 10 software projects developed by four well-established software companies in Turkey were collected and datasets were created. When effort estimations obtained from datasets and actual efforts spent to complete the projects are compared with each other, it has been observed that the proposed method has higher effort estimation accuracy compared to the other methods.

scholarly journals COMPARATIVE ANALYSIS OF SOFTWARE EFFORT ESTIMATION USING DATA MINING TECHNIQUE AND FEATURE SELECTION

2021 ◽  
Vol 6 (2) ◽  
pp. 167-174
Author(s):  
Abdul Latif ◽  
Lady Agustin Fitriana ◽  
Muhammad Rifqi Firdaus
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Feature Selection ◽  
Linear Regression ◽  
Software Development ◽  
Data Mining Algorithm ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Data Mining Technique ◽  
Software Business

Software development involves several interrelated factors that influence development efforts and productivity. Improving the estimation techniques available to project managers will facilitate more effective time and budget control in software development. Software Effort Estimation or software cost/effort estimation can help a software development company to overcome difficulties experienced in estimating software development efforts. This study aims to compare the Machine Learning method of Linear Regression (LR), Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Decision Tree Random Forest (DTRF) to calculate estimated cost/effort software. Then these five approaches will be tested on a dataset of software development projects as many as 10 dataset projects. So that it can produce new knowledge about what machine learning and non-machine learning methods are the most accurate for estimating software business. As well as knowing between the selection between using Particle Swarm Optimization (PSO) for attributes selection and without PSO, which one can increase the accuracy for software business estimation. The data mining algorithm used to calculate the most optimal software effort estimate is the Linear Regression algorithm with an average RMSE value of 1603,024 for the 10 datasets tested. Then using the PSO feature selection can increase the accuracy or reduce the RMSE average value to 1552,999. The result indicates that, compared with the original regression linear model, the accuracy or error rate of software effort estimation has increased by 3.12% by applying PSO feature selection

Pengaruh Motivasi Kerja Terhadap Kinerja Pegawai Kantor Sekretariat Daerah Kabupaten Gunungkidul

2017 ◽  
Vol 23 (2) ◽  
pp. 121-137
Author(s):  
Ary Sutrischastini ◽  
Agus Riyanto
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Sampling Method ◽  
Work Motivation ◽  
Probability Sampling ◽  
Random Probability

This paper will discuss the effect of work motivation (incentives, motives and expectations) on the performance of the staff of the Regional Secretariat Gunungkidul. The purpose of this paper is: 1) Determine the effect of incentives on the performance of the staff of the Regional Secretariat Gunungkidul, 2) Determine the effect of motive on the performance of the staff of the Regional Secretariat Gunungkidul, 3) To know the effect of expectations on the performance of the staff of the Regional Secretariat Gunungkidul, 4)To know the effect of incentives, motives and expectations on the performance of the staff of the Regional Secretariat Gunungkidul.Research sites in the Regional Secretariat Gunungkidul and the population is 162entire employee in the Regional Secretariat Gunungkidul. Samples amounted to 116 respondents taken with simple random probability sampling method. Data were analyzed using multiple linear regression. Results obtained: (1) incentives positive and significant effect on the performance of, (2) motif positive and significant effect on the performance of, (3) expectations positive and significant impact on the performance of , and (4) incentives, motives and expectations of positive and significant impact on the performance of the staff of the Regional Secretariat Gunungkidul.

PENGARUH FAKTOR-FAKTOR INTERNAL PERBANKAN TERHADAP NON PERFORMING FINANCING PADA BANK UMUM SYARIAH

2019 ◽  
Vol 6 (2) ◽  
pp. 115-130
Author(s):  
Eka Ambara Harci Putranta ◽  
Lilik Ambarwati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Capital Adequacy ◽  
Annual Reports ◽  
Regression Methods ◽  
Capital Adequacy Ratio ◽  
Negative Effect ◽  
Independent Variable

The study aims to analyze the influence of internal banking factors in the form of: Capital Adequency Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing at Sharia Banks. This research method used multiple linear regression analysis with the help of SPSS 16.00 software which is used to see the influence between the independent variables in the form of Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing. The sample of this study was 3 Islamic Commercial Banks, so there were 36 annual reports obtained through purposive sampling, then analyzed using multiple linear regression methods. The results showed that based on the F Test, the independent variable had an effect on the NPF, indicated by the F value of 17,016 and significance of 0,000, overall the independent variable was able to explain the effect of 69.60%. While based on the partial t test, showed that CAR has a significant negative effect, Total assets have a significant positive effect with a significance value below 0.05 (5%). Meanwhile FDR does not affect NPF.

Faktor-Faktor Yang Mempengaruhi Keputusan Mahasiswa Memilih Program Studi Kebidanan STIKES Muhammadiyah Ciamis Tahun 2016

2018 ◽  
Vol 5 (1) ◽  
pp. 69-82
Author(s):  
Evi Mariana
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Sampling ◽  
Sampling Method ◽  
Marketing Mix ◽  
Stratified Random Sampling ◽  
Price Promotion ◽  
F Test ◽  
Physical Evidence

The purpose of this study was to analyze the factors that influence the decisionof the students chose to study in Obstetrics Prodi STIKES Muhammadiyah Ciamis and analyze the factors that most influence the decision of the students chose to study in Obstetrics Prodi STIKES Muhammadiyah Ciamis. Collecting data in this study was conducted using a survey by questionnaire to 114 students by stratified random sampling method. Methods of data analysis using multiple linear regression, F test and test T. The result is a marketing mix that significantly is the product, place, and physical evidence. And that does not affect the marketing mix is price, promotion, place, and processes

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

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