Pengaruh Kinerja Operasional Terhadap Kepuasan Pelanggan Pada PT. Prima Megah Irsa

ABSTRAK Karyawan Perusahaan dapat berinteraksi dengan pelanggan , sehingga kinerja karyawan yang memberikan layanan adalah kunci kepuasan pelanggan. Gambar Perusahaan ditampilkan sebagai Layanan untuk Layanan Karyawan Pelanggan. Survei ini menggunakan survei kuantitatif yang berpengaruh untuk mengetahui pengaruh kinerja karyawan terhadap kepuasan pelanggan di PT.Prima Megah Irsa. Metode pengambilan sampel yang digunakan adalah random sampling. Sampel yang dikumpulkan dalam penelitian ini adalah pelanggan PT Prima Megah Irsa , diantaranya berada di Jalan Krikilan No 146 Ds. Krikilan RT. 013 RW. 005 kec. Driyorejo Kab. Gresik, sampel untuk survei ini adalah - 130 orang. Berdasarkan hasil analisis regresi berganda, uji korelasi kinerja-kepuasan karyawan menunjukkan R = 0,856. Juga pada uji korelasi antara kinerja karyawan dengan loyalitas pelanggan, R = 0,602. Maka didapat persamaan regresi berganda = Y = 4.408 + 2.713y + 1.064z. Model Koefisien Regresi ini berarti . Z) Meningkat 1.064. ABSTRACT Company employees can interact with customers, so the performance of employees who provide services is the key to customer satisfaction. Company Images are displayed as a Service for Customer Service Employees. This survey uses an influential quantitative survey to determine the effect of employee performance on customer satisfaction at PT.Prima Megah Irsa. The sampling method used is random sampling. The samples collected in this study were customers of PT Prima Megah Irsa, including those on Jalan Krikilan No 146 Ds. Krikilan RT. 013 RW. 005 district. Driyorejo Kab. Gresik, the sample for this survey is - 130 people. Based on multiple regression analysis, the performance-satisfaction correlation test showed R = 0.856. Also on the correlation test between employee performance and customer loyalty, R = 0.602. Then the multiple regression equation is obtained = Y = 4.408 + 2.713y + 1.064z. This Regression Coefficient Model means . Z) Increase by 1,064.

Prediction of California Bearing Ratio from Consistency and Compaction Characteristics of Fine-grained Soils

Soil’s characteristics are essential for the successful design of projects such as airports runway and flexible pavement. CBR (California Bering Ratio) is one of the significant soil characteristics for highways and airports projects. Thus, the CBR property can be used to determine the subgrade reaction of soil through correlations. Many of the soil geotechnical parameters such as compaction characteristics (Maximum Dry Density, MDD; Optimum Moisture Content, OMC), and consistency parameters (Liquid Limit, LL; Plastic Limit, PL; Plasticity Index, PI) can be in charge of changes that happen in soil CBR value. Soaked and/or non-soaked conditions of soils also affect CBR value. Hence, testing soils in a laboratory for CBR calculation is time-consuming that needs notable effort. Therefore, this study aims to generate some useful correlations for soil’s CBR with compaction and consistency parameters for 85 samples of fine-grained soils. The study trials were applied on natural soil samples of various places in Sulaimani Governorate, Northern Iraq. Statistical analysis has been carried out by using SPSS software (Version 28). Soaked CBR is counted, which is important for conditions such as rural roads that remain prone to water for few days. Based on the statistical analysis, there is a significant correlation between LL, PL, PI, MDD, and OMC with CBR as the dependent variable as a single variable equation with R2 of 0.7673, 0.5423, 0.5192, 0.6489, and 0.51, respectively. In addition, the highest value of R2 correlation was obtained between CBR value with consistency and compaction properties as a multiple regression equation with R2 of 0.82. The obtained equations for correlation purposes are successfully achieved and can be used, notably, to estimate CBR value.

Analisis Pengaruh Pendapatan dan Pengetahuan terhadap Minat Calon Nasabah Berinvestasi Emas di Pegadaian Syariah

This study was conducted to examine the effect of income and knowledge on the interest of prospective customers to invest in gold in Pegadaian Syariah. The sampling technique in this study was carried out through probability sampling with simple random sampling. 99 customers who had not invested in gold in the Pegadaian Syariah is definded as the respondents. The method used is multiple regression analysis and hypothesis testing using t-statistics to test the coefficients together with a level of significance of 5%. In addition, the classical assumption test was also carried out which included normality test, multicollinearity test, heteroscedasticity test and autocorrelation test. The results showed that the research data were normally distributed and there were no variables that deviated from the classical assumptions, which also means that the available data has met the requirements to use the multiple regression equation model. Partially, the income and knowledge variable have a positive and significant effect (with a significance value of 0.000 <0.05) on the interest of prospective customers to invest in gold in Pegadaian Syaria Located in Langsa. Meanwhile, simultaneously the income and the knowledge variable have a positive and significant effect (with a significance value of 0.000 <0.05) on the interest of prospective customers to invest in gold Pegadaian Syaria Located in Langsa.

Predictive value of kinematic indicators for shot put result and selection of novice athletes

Purpose: to determine the most significant kinematic indicators in the sports selection of beginner shot putters. Material and Methods: This study was carried out on a sample of 9 students at the fourth stage of the competition in Division 1, which took place in the 2017/2018 academic year at the Faculty of Physical Education of Maysan University. The following kinematic (biomechanical) parameters were analyzed: the angle of release of the nucleus, the velocity of release, the height of the point of ejection of the nucleus and the speed of swing. The correlation coefficients were determined between the kinematic indicators and the result in the shot put, as well as the regression equation for the dependence of the result in the shot put on the knematic indicators. The data obtained in the study were presented in the form of the arithmetic mean, standard deviation, median, skewness coefficient, Pearson's correlation coefficient, analysis of variance and linear regression, which included the contribution coefficients of each analyzed indicator, standard error, reliability of the regression equation as a whole, and reliability of the coefficients contribution to the shot put result of each kinematic exponent. Results. It has been shown that the swing speed has the greatest influence on the result in the shot put among beginner athletes. The swing speed, shot angle, shot speed and shot height have significant relationships with the shot put result. The multiple regression equation for the dependence of the shot put result on the swing speed, shot angle, shot height and shot point turned out to be reliable in general. However, only the swing speed has a reliable coefficient of the regression equation. The shot angle tends to be the determining factor in the shot put result. The release rate and the height of the release point have significant correlations with the shot put result, although in the regression equation they have unreliable indicators of influence on the shot put result. Conclusions. When teaching beginner shot putters, the greatest attention should be paid to the pushing swing technique, namely the swing speed. The second most important indicator is the angle of the shot put, it is recommended to use the basic prediction equation, which determines the expected results in the selection of young athletes in shot put, with high reliability of the results obtained. These characteristics are recommended to be used for evaluating young athletes, as well as in the process of training and preparing athletes for competitions.

The Use of Econometric Analysis in Forecasting Macroeconomic Processes

The article discusses the issues related to the influence of various price categories of goods on the level of inflation. The possibility of using econometric analysis for predictive purposes is considered. An econometric model of multiple regression of the influence of consumer prices on the level of inflation is formed. A linear multiple regression equation is constructed. The selection of factors for the construction of an econometric model is made. The main groups of goods are identified, the prices of which form the level of inflation and can have a primary impact. The viability of the model and the possibility of forecasting macroeconomic indicators based on econometric analysis are proved.

Evaluation of different traps for the invasive leaf miner, Liriomyza huidobrensis in potato (Solanum tuberosum) fields of the Nilgiris district, Tamil Nadu, India

Potatoes are currently threatened by the pea leaf miner (Liriomyza huidobrensis Blanchard), an exotic, exceedingly polyphagous, and chemically resistant pest that attacks a wide range of crops, ornamental plants, and weeds. The present work was conducted to study the attractiveness of various traps to Liriomyza leaf miner, one of the invasive pests recently observed in potato fields of Kotagiri and Ooty in Nilgiris district of Tamil Nadu. A trial was conducted at these two different locations, the Nilgiris district, in 2021. The results revealed that among different traps tested for their efficacy in attracting the leaf miner, L. huidobrensis, yellow sticky trap was found to be more efficient in attracting adult leaf miner flies with the mean trap catches of 40.49 and 36.64 adult flies/ 10 cm2 areas at Kotagiri and Ooty respectively. The peak population of leaf miners was recorded in the last week of April (45.67 adult flies/ 10 cm2 areas) at Ooty and during the 3rd week of June (52.33 adult flies/ 10 cm2 areas) at Kotagiri. The correlation study revealed a significant positive correlation of the trap catches with maximum temperature, diurnal variation (DV) and growing day degrees (GDD). Multiple regression equation was also developed, where the abiotic factors contributed 46.1% and 65.5% to the Liriomyza leaf miner population fluctuation in the potato ecosystem. The trappers may be used to determine the initial presence of a leaf miners’ population and in projecting their future population through pest management models and management decisions.

Effect of temperature and sunshine on the productivity of rice crop

Based on the experimental work with 8 different thermal and light environments, the effect of temperature and sunshine on rice crop (var : IR-36) was studied. It was found that the rice crop grown during winter/summer season experience, extremes of minimum temperature at seedling and vegetative stages and extemes of maximum temperature at reproductive and maturity stages. Correlation coeffcients between the grain yield and maximum and minimum temperature growing degree days and total number of sunshine hours at each of the growth stages.viz:. seedling. vegetative. reproductive and maturity stages were worked out. Multiple regression equation was worked out with 5 parameters upto vegetative stage to predict the grain yield of rice

Weather based prediction of Chickpea Helicoverpa armigera population in Bundelkhand agroclimatic zone of Madhya Pradesh

An attempt was made to find out the impact of rainfall, temperature and growing degree day (GDD) on the larval incidence and peak population of Helicoverpa armigera on chickpea and its growth in the Bundelkhand Agroclimatic zone of Madhya Pradesh. Besides, an attempt was also made to examine the association with weather variables of rising and falling phase of the larval population of Helicoverpa armigera. It was found that there was not any significant impact of monthly (September and October) rainfall on the larval population but the monthly rainfall of January and February significantly influenced the incidence of the pod borer and GDD plays a vital role in increasing and decreasing of its peak population. Minimum temperature and rainfall play a crucial role for larval incidence and its population growth. Growing degree day from 1st January to 15th February were presented in relation to the number of peak larval population in chickpea. The correlation of weather factors with larval population was also presented and different weather parameters were screened for its prediction and management. A multiple regression equation was also developed. It was found that if the cumulative growing degree day from 1st January to 15th February 350 degree day and weekly minimum temperature ranged from 6 to 12 C along with number of rainfall events 5 days, then number of larval population of H. armigera in chickpea is high and vice-versa. This study will be very useful not only for forecasting the peak larval population of H. armigera in chickpea but in formulating effective pest management strategies too.

Factors Affecting Poverty on the Island of Sumatera

Poverty is a problem faced by many developing countries in general. Poverty is a reflection of the economic activities carried out by a country. The poverty level of a country shows that the development programs implemented by the government are not optimal. This study was conducted to analyze the determinants of poverty in 10 provinces on the island of Sumatra from 2006-2019. Multiple regression equation models were built for this research using the Ordinary Least Squares (OLS) method with the e-views 8 tool. The results show that simultaneously, the independent variable has a significant effect on poverty and partially one variable that does not significantly affect poverty, namely unemployment. An increase in education (literacy rate) and infrastructure (road length) leads to an increase in poverty and inequality in income distribution (the Gini Index), resulting in a decrease in poverty. It is hoped that future researchers will use education, infrastructure, and income distribution variables with different proxies.

Evapotranspiration and heat unit requirement of cowpea

Weighing gravimetric lysimeters are used to measure actual evapotranspiration of cowpea for an experiment conducted for two years during Kharif 2004 and 2005. A multiple regression equation has been generated for relating crop coefficient of cowpea with week after sowing. The highest value of crop co-efficient was found to be 1.015 on 6th week after sowing under Bangalore climate, the average values of actual evapotranspiration from cowpea crop and heat unit requirements over a period of 89 days in the Kharif season are found to be 284.8 mm and 1293 degree days respectively.