scholarly journals Factors Affecting Income of Pineapple Small Farmers: Case Study at Tangkit Baru Village, Jambi Province, Indonesia

2020 ◽  
Vol 7 (1) ◽  
pp. 303-308
Author(s):  
Boris Kaido
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Small Farmers ◽  
Field Scale ◽  
Land Rent ◽  
Factors Affecting ◽  
Interview Method

This study was conducted in Tangkit baru village, Jambi Province, Indonesia. The Study area was selected purposively based on this village which has produced the highest pineapple conducted by small farmers in Jambi Province. This study aims to determine the factors that affect the income of a small farmer pineapple in Tangkit baru village. The study aims were analyzed in descriptive methods and multiple linear regression analysis. The number of respondents was taken in the Slovin method, with 42 respondents. Data collection used the interview method with the questionnaire conducted directly in the study area. The data were analyzed quantitatively, the results study showed that all variables affected the farmer’s income, it was seen as a significance value of 0.000 < α 5%. Partially, the variables that affect the farmer’s income are field scale (X7) and labor factor (X6), while the variables that have no significant effect on pineapple small farmer’s income are the land rent (X4) and fertilizer (X1). 

scholarly journals Factors Affecting Company's Capability in Performing Integrated Reporting: An Empirical Evidence From Indonesian Companies

2018 ◽  
Vol 7 (2) ◽  
pp. 141
Author(s):  
Putu Sukma Kurniawan ◽  
Made Arie Wahyuni
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Institutional Ownership ◽  
Multiple Linear Regression Analysis ◽  
Managerial Ownership ◽  
Contrast Level ◽  
Integrated Reporting ◽  
Factors Affecting

<p>This study examines the factors that affect the company's capability to perform integrated reporting. The analysis used in testing the hypothesis is multiple linear regression analysis. Results show that company’s size has positive and significant connection and stakeholder’s pressure has negative and significant connection with the company’s capability in performing integrated reporting. In contrast, level of company’s profitability, company’s managerial ownership, and company’s institutional ownership did not have enough connection with company’s capability in performing integrated reporting.</p><p> </p>

scholarly journals Production Analysis of Green Mussel (Perna viridis) in Lampung Province

2020 ◽  
Vol 8 (2) ◽  
pp. 975
Author(s):  
Sulvina Sulvina ◽  
Zainal Abidin ◽  
Supono Supono
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Influential Factors ◽  
Perna Viridis ◽  
Factors Affecting ◽  
Cultivation Process ◽  
Quantitative Descriptive

This study was conducted to find out factors affecting and level of mussel production, level of efficiency of using the tools and materials in cultivation process and whether the cultivation of mussels in Pasaran. This study was analyzed using Cobb-Douglass. The study were analyzed in quantitative descriptive, multiple linear regression analysis, and analysis of efficiency. The dependent variable (Y) is the result of production of green mussels cultivation and free variables are the number of bamboos (X 1), the amount of strap (X2), grouper (X3) and labor (X4). Mussel fisherman in Pasaran NPM with Px calculated to obtain the level of efficiency of each factors of production in messels cultivation. Studies show that the most influential factors production are variable bamboo, rope and labor. While the results of analysis the level of efficiency of using tools and materials is not efficient. The number of bamboo and labor should be reduced, because it tends to be a waste and not profitable either technically or economically. The value of the return to scale of 1.22 showed cultivation mussels are on increasing return to scale.

FACTORS AFFECTING ELECTRONIC MONEY (E-MONEY) SALES CASE STUDY IN BANKING ENTITIES IN INDONESIA

2019 ◽  
Vol 24 (3) ◽  
pp. 236-242
Author(s):  
B Sundari ◽  
Cicilia Erly Istia ◽  
Renita Helena
Keyword(s):  
Regression Analysis ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Marketing Channels ◽  
Analysis Method ◽  
Electronic Money ◽  
Factors Affecting ◽  
Independent Variable ◽  
The Relationship

Electronic money instruments with non-cash transactions continue to increase positively from year to year. This is also due to the launch of the national non-cash or cashless movement which has been widely applied, especially in Indonesia. This study aims to find out what factors influence e-money sales, especially in banking entities in Indonesia. This study uses multiple linear regression analysis method using SPSS 22, which aims to examine the relationship or effect of the dependent variable with the independent variable. The results of the study have found that in the partial sale of electronic money is only influenced by e-money marketing channels / partnerships. While ease of transaction, ease of top up, and type of design do not have an impact on e-money sales. Meanwhile, simultaneously, these factors have an impact on E-Money sales.

Factors Affecting Land Conversion From Rice Plants to Lime Plants in Watabenua Village Landono District

2021 ◽  
Vol 6 (3) ◽  
pp. 95
Author(s):  
Rimat Maulana ◽  
Lukman Yunus ◽  
Samsul Alam Fyka
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Lowland Rice ◽  
Land Conversion ◽  
Factors Affecting ◽  
Citrus Production ◽  
The Cost ◽  
Rice Plantations

This study aims to determine what factors influence land conversion from lowland rice plantations to lime plantations in Watabenua Village, Landono District. The population in this study were all farmers who had converted land in Watabenua Village, Landono District, South Konawe Regency, and as many as 33 people, where all were used as samples by the census method 33 respondents. The analytical method used is multiple linear regression analysis. The results of this study are the factors that affect the conversion of land from lowland rice plantations to lime plantations in Watabenua Village are the cost of citrus production. In contrast, the factors that do not affect land conversion are rice income, the distance between irrigation water sources to rice fields, the price of another product, namely oranges.

Wavelet and multiple linear regression analysis for identifying factors affecting particulate matter PM2.5 in Mumbai City, India

2019 ◽  
Vol 36 (10) ◽  
pp. 1750-1783 ◽  
Author(s):  
Vivekanand Venkataraman ◽  
Syed Usmanulla ◽  
Appaiah Sonnappa ◽  
Pratiksha Sadashiv ◽  
Suhaib Soofi Mohammed ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Control Measures ◽  
Data Set ◽  
Content Type ◽  
Factors Affecting ◽  
Significant Factors

Purpose The purpose of this paper is to identify significant factors of environmental variables and pollutants that have an effect on PM2.5 through wavelet and regression analysis. Design/methodology/approach In order to provide stable data set for regression analysis, multiresolution analysis using wavelets is conducted. For the sampled data, multicollinearity among the independent variables is removed by using principal component analysis and multiple linear regression analysis is conducted using PM2.5 as a dependent variable. Findings It is found that few pollutants such as NO2, NOx, SO2, benzene and environmental factors such as ambient temperature, solar radiation and wind direction affect PM2.5. The regression model developed has high R2 value of 91.9 percent, and the residues are stationary and not correlated indicating a sound model. Research limitations/implications The research provides a framework for extracting stationary data and other important features such as change points in mean and variance, using the sample data for regression analysis. The work needs to be extended across all areas in India and for various other stationary data sets there can be different factors affecting PM2.5. Practical implications Control measures such as control charts can be implemented for significant factors. Social implications Rules and regulations can be made more stringent on the factors. Originality/value The originality of this paper lies in the integration of wavelets with regression analysis for air pollution data.

scholarly journals The Effect of Perceived Value and Personal Selling on Participants 'Decision on Employment BPJS Bengkulu Branch (Case Study on Wage Non-Recipient Category Customers)

2019 ◽  
Vol 3 (12) ◽  
pp. 43-48
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Personal Selling ◽  
Perceived Value ◽  
Multiple Linear Regression Analysis ◽  
Analysis Technique

The purpose of this study was to determine the effect of perceived value and personal selling on participants' decisions on BPJS Employment in the category of Non Wage Recipients (NRP). The population in this study were all BPJS Employment participants in the Non Wage category during 2018. The sample in this study was 100 respondents. The analysis technique in this study used multiple linear regression analysis. The results of this study indicate that the variables perceived value and personal selling jointly influence the decisions of the BPJS Employment participants. Perceived value has a positive and significant effect on participants' decisions and personal selling has a positive and significant effect on the decisions of BPJS Employment participants.

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