scholarly journals Multiple Linear Regression Approach for Strategic Decisions on Industrial Productivity under Limited Available Budget

2020 ◽  
pp. 36-45
Author(s):  
Oluwaseun Oluwagbemiga Ojo ◽  
David Ifeoluwa Oladapo ◽  
Abiola Olufemi Ajayeoba ◽  
Basil Olufemi Akinnuli ◽  
Temitayo Daniel Omotayo
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Multiple Linear Regression Model ◽  
Coefficient Of Determination ◽  
Strategic Decisions ◽  
Long Run ◽  
Industrial Productivity ◽  
Labor Inputs ◽  
Increase Productivity ◽  
The Relationship

Proper planning and improved productivity is highly desired in industrial settings to optimize the available resources when there is limited resources and to control excessive spending in time of surplus.  Productivity is achievable by good levels of Materials, Time and Labor inputs which needs to be measured scientifically in order to maintain long run profit. This study explored processing data and incorporated Statistical Package for Social Science (SPSS) to find the relationship and predict the response of the available budget with the inputs of Materials, Time and Labor using Olam Cocoa Processing Industry, Nigeria as case study. The analyses were done using Multiple Linear Regression Model developed (i.e. ), it was discovered that the inputs of the selected strategic decisions  collectively affected the response of the available budget with F-value of 88.48 but each of them cannot reduce or increase the amount of budget except for manpower which has 0.069 or 93.1 % significant effect on the available budget. Also, Coefficient of determination established a strong fitness of the relationship between the strategic decisions and the available budget with the value of 0.974 (or 97.4 %). It is recommended that the project manager should subject his decisions making into scientific measures rather than brainstorming so as to increase productivity in the company.

PENGARUH HARGA DAN BRAND TRUST TERHADAP KEPUTUSAN PEMBELIAN OPPO SMARTPHONE (Studi kasus pada OPPO Store, Sinergy Celular Medan)

2019 ◽  
Vol 14 (1) ◽  
pp. 17
Author(s):  
Andi S Tarigan ◽  
Zulkarnaian Siregar
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Coefficient Of Determination ◽  
Purchase Decision ◽  
Brand Trust ◽  
Significance Level ◽  
Research Hypothesis ◽  
Analysis Technique ◽  
The Relationship

AbstrakPenelitian ini bertujuan untuk mengetahui Pengaruh Harga dan Brand Trust Terhadap Keputusan Pembelian pada Sinergy Celular Medan.Sampel dalam penelitian ini adalah seluruh pengunjung Sinergy Celular Medan sebanyak 77 orang.Teknik pengumpulan data yang digunakan adalah melalui kuesioner (angket) yaitu dengan cara menyebarkan kuesioner kepada sampel (responden) dan mengumpulkannya kembali. Teknik analisis data yang digunakan adalah Regresi Linear Berganda.Sebelum data diregresikan maka terlebih dahulu di uji keterkaitannya antara variabel, datanya diuji menggunakan uji normalitas data, multikolinearitas, dan heterokedastisitas.Serta untuk mengetahui kontribusi faktor Harga dan Brand TrustTerhadap Keputusan Pembelian digunakan rumus Koefisien Determinasi (R2). Hipotesis penelitian diterima apabila t hitung >  t tabel dengan tingkat signifikansi 0,1. Nilai t tabel dalam penelitian ini 1,993. Nilai t hitung variabel X1 sebesar 2,107 t hitung lebih besar dari t tabel maka hipotesis di terima, nilai t hitung variabel X2   sebesar 3,405 t hitung lebih besar dari t tabel maka hipotesis di terima. Kata kunci: Harga, Brand Trust, Keputusan Pembelian AbstractThis study aims to determine the Influence of Price and Brand Trust on Purchasing Decision at Sinergy Celular Medan. The sample in this study is all visitors Sinergy Celular Medan as many as 77 people.Data collection technique used is through questionnaire (questionnaire) that is by distributing questionnaires to the sample (respondent) and collect it back. Data analysis technique used is Multiple Linear Regression. Before the data is diregresikan then first in the test the relationship between variables, the data tested using the test of data normality, multicollinearity, and heterokedastisitas. And to know the contribution of price factors and Brand Trust Against Purchase Decision is used the formula Coefficient of Determination (R2). Research hypothesis accepted if t arithmetic> t table with significance level 0,1. The value of t table in this study is 1,993. Value t arithmetic variable X1 of 2.107 t arithmetic greater than t table then the hypothesis received, the value of t arithmetic variable X2 of 3.405 t arithmetic greater than t table then the hypothesis received. Keywords: Price, Brand Trust, Purchase Decision

Whole Facility Measurement for Quantifying Energy Saving in an Office Building, Malaysia

2015 ◽  
Vol 785 ◽  
pp. 676-681 ◽  
Author(s):  
Nor Shahida Razali ◽  
Nofri Yenita Dahlan
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Energy Saving ◽  
Linear Regression Model ◽  
Energy Use ◽  
Multiple Linear Regression Model ◽  
Office Building ◽  
Coefficient Of Determination ◽  
Independent Variable

This paper presents the concept of International Performance Measurement and Verification Protocol (IPMVP) for determining energy saving at whole facility level for an office building in Malaysia. Regression analysis is used to develop baseline model from a set of baseline data which correlates baseline energy with appropriate independents variables, i.e. Cooling Degree Days (CDD) and Number of Working Days (NWD) in this paper. In determining energy savings, the baseline energy is adjusted to the same set condition of reporting period using energy cost avoidance approach. Two types of energy saving analyses have been presented in the case study; 1) Single linear regression for each independent variable, 2) Multiple linear regression for each independent variable. Results show that NWD has coefficient of determination, R2 higher than CDD which indicates that NWD has stronger correlation with the energy use than CDD in the building. Finding also shows that the R2 for multiple linear regression model are higher than single linear regression model. This shows the fact that more than one component are affecting the energy use in the building.

scholarly journals The Effect of Phase on Paper Thickness Optimization in the Paper Recycling Process Using Recycling Machine

2020 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Fauzhia Rahmasari
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Multiple Linear Regression Model ◽  
Thickness Optimization ◽  
Recycling Process ◽  
Paper Recycling ◽  
Independent Variables ◽  
The Relationship

AbstractEfforts to manage the recycling of paper waste into new paper have been carried out in recent times. It takes a tool or machine that is able to effectively and efficiently recycle used paper into new paper. There are several factors that affect the effectiveness of paper recycling machines, one of which is the paper thickness. One method that can be used to analyze the factors that influence paper thickness in the paper production process using a paper recycling machine is regression analysis. Regression analysis is data analysis techniques in statistics that is used to examine the relationship between several independent variables and dependent variable. However, if we want to examine the relationship or effect of two or more independent variables on a dependent variable, the regression model used is a multiple linear regression model. This study purposes are to analyze the factors that influence paper thickness using a paper recycling machine using multiple linear regression and to inform the modeling about that. The results showed that the factors that affect the paper thickness optimization are destruction and press phase. AbstractUpaya pengelolaan daur ulang sampah kertas menjadi kertas baru telah banyak dilakukan pada jaman sekarang. Dibutuhkan suatu alat atau mesin yang mampu secara efektif dan efisien dalam mendaur ulang kertas bekas menjadi kertas baru. Terdapat beberapa faktor yang mempengaruhi tingkat efektifitas mesin daur ulang kertas diantaranya adalah ketebalan kertas. Salah satu metode yang dapat digunakan untuk menganalisis faktor-faktor yang mempengaruhi ketebalan kertas pada proses produksi kertas menggunakan mesin daur ulang kertas adalah analisis regresi. Analisis regresi merupakan teknik analisis data dalam statistika yang digunakan untuk mengkaji hubungan antara beberapa variabel bebas dengan variabel tidak bebas. Namun, jika ingin mengkaji hubungan atau pengaruh dua atau lebih variabel bebas terhadap satu variabel tidak bebas, maka model regresi yang digunakan adalah model regresi linier berganda. Tujuan dalam penelitian ini yaitu menganalisis faktor-faktor yang mempengaruhi ketebalan kertas menggunakan mesin daur ulang kertas menggunakan regresi linier berganda serta memberikan informasi pemodelan mengenai hal tersebut. Hasil penelitian menunjukkan bahwa faktor yang mempengaruhi keoptimalan ketebalan kertas adalah fase penghancuran dan pemadatan kertas

The Impact of Climate Change on Agriculture in Morocco: An Econometric Study

2020 ◽  
Vol 1 (2) ◽  
pp. 19-28
Author(s):  
Faycel Tazigh
Keyword(s):  
Climate Change ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Independent Variables ◽  
Temperature And Precipitation ◽  
The Impact ◽  
The Relationship

This paper aims to analyze the relationship that may exist between climate change and cereal yield in Morocco. In order to study this correlation between variables, we used the most common form of regression model which is the multiple linear regression model. There are two main uses of multiple linear regression model. The first one is to quantify the weight of impact that the independent variables had on the dependent variable. The second use is to predict not only the relationship that may found between variables but also their impacts. In our case, we have chosen temperature and precipitation as an independent variables and cereal yield as dependent variable.

Canine Parvoviral Enteritis and Its Determinants-An Epidemiological Analysis

2021 ◽  
Author(s):  
M. Geetha ◽  
G. Selvaraju
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Tamil Nadu ◽  
Multiple Linear Regression Model ◽  
Age Group ◽  
Environmental Determinants ◽  
Disease Occurrence ◽  
The Relationship

Background: Canine parvoviral enteritis (CPVE) is a highly contagious disease of dogs of less than two years age group characterized by vomiting, haemorrhagic foul smelling diarrhoea, high grade pyrexia, dehydration and followed by death. The disease is caused by Canine parvovirus type-2 (CPV-2) and its variants, CPV-2a, 2b and 2c. Environmental and host determinants are playing an important role in the occurrence of CPVE in dogs. Limited numbers of research studies have been were conducted on the role of the determinants associated with the disease occurrence. Hence, the present study was aimed to assess the influence of host and environmental determinants associated with the incidence of CPVE in dogs. Methods: Retrospective data on the incidence of CPVE in Namakkal region, Tamil Nadu was collected (2017-2019) from Veterinary Clinical Complex (VCC), Veterinary College and Research Institute (VC and RI), Namakkal, Tamil Nadu and had been subjected to temporal and spatial clustering and regression analysis. One hundred and twenty three faecal samples were collected from dogs with clinical signs of CPVE and subjected to PCR using H primer of CPV. Cross-sectional study was used to investigate the relationship between the disease and hypothesized causal factors. Relative risk, odds ratio were used to determine the causal association. Weather data was collected for the period from 2017-2019 from Animal Feed Analytical and Quality Control Laboratory (AFAQAL), VC and RI, Namakkal to assess the relationship of disease occurrence with the environmental determinants. Multiple linear regression model was developed for prediction of CPVE by correlation of environmental determinants with the occurrence of CPVE. Result: Temporal analysis revealed endemic pattern of CPVE started last week of April, peaks in June and ends in August and second peak was noticed at November month. Higher incidences ( greater than 70%) were noticed in males and less than 6 months age group dogs. Polymerase chain reaction for confirmation of CPV infection in dogs revealed the positivity of 70.73%. Analysis of risk factors associated with CPVE revealed that vaccination, roaming of dogs, maternal vaccination and early weaning having positive statistical association with the incidence of CPVE. Multiple linear regression model revealed that relative humidity is positively associated with the occurrence of CPVE in dogs. Vaccination of dogs against CPV and administration of boosters at regular intervals, weaning of dogs after 45 days of age are used as primary strategies for prevention of CPVE.

scholarly journals Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques

2019 ◽  
Vol 5 (1) ◽  
pp. 82 ◽  
Author(s):  
Rami Raad Ahmed Al-Ani ◽  
Basim Hussein Khudair Al-Obaidi
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Sediment Accumulation ◽  
Multiple Linear Regression Model ◽  
Sediment Deposition ◽  
Coefficient Of Determination ◽  
Ann Model ◽  
Sewer Rehabilitation ◽  
Artificial Neural Network Ann

Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers proposed an alternative method for sewer sediment accumulation calculation using predictive models harnessing multiple linear regression model (MLRM) and artificial neural network (ANN). AL-Thawra trunk sewer in Baghdad city is selected as a case study area; data from a survey done on this trunk is used in the modeling process. Results showed that MLRM is acceptable, with an adjusted coefficient of determination (adj. R2) in order of 89.55%. ANN model found to be practical with R2 of 82.3% and fit the data better throughout its range. Sensitivity analysis showed that the flow is the most influential parameter on the depth of sediment deposition.

scholarly journals Investigating the Relationship between Traffic Violations and Crashes at Signalized Intersections: An Empirical Study in China

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Ze-Hao Jiang ◽  
Xiao-Guang Yang ◽  
Tuo Sun ◽  
Tao Wang ◽  
Zheng Yang
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Multiple Linear Regression Model ◽  
Signalized Intersections ◽  
Traffic Light ◽  
Traffic Crashes ◽  
Traffic Crash ◽  
Crash Data ◽  
Traffic Violations ◽  
The Relationship

About 90% of traffic crashes are caused by human factors, within which traffic violations are one of the most typical and common causes. In order to investigate the relationship between traffic violations and traffic crashes, this research targets signalized intersections in two Chinese cities: Yinchuan and Suqian. Thirty-one intersections are selected as the research sites, and additionally, the traffic volume, traffic violation, and traffic crash data of each intersection are collected for one year. A White’s test is conducted to test the homoscedasticity of the data and a multiple linear regression model is employed to investigate the relationship between traffic crashes and violations. The results show the following: (1) although the research sites are located in two different cities, the data is homoscedastic, which suggests that the above result may be statistically stable between different cities. (2) There is a significant multiple linear regression relationship (R2 = 0.782, adjusted R2 = 0.716) between the total number of traffic crashes and traffic violations. Among the chosen 7 independent variables, four are significantly related to the dependent variable, namely, driving commercial vehicle during internship, wrong-way entry, speeding, and traffic-light violation. (3) With the increase of annual average daily traffic (AADT), the number of total crashes goes up; however, the injury-or-fatality rate decreases, which means that intersections with smaller traffic volumes tend to have higher traffic crash severity. Based on the above conclusions, it is possible to conduct more targeted enforcement to improve the safety of intersections.

Urgensity of “Halal Tourism”: Religiosity, Awareness, and Interest from Stakeholders

2021 ◽  
Vol 12 (4) ◽  
pp. 968
Author(s):  
Muhammad Ridlo ZARKASYI ◽  
Dhika Amalia KURNIAWAN ◽  
Dio Caisar DARMA
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Decision Makers ◽  
Muslim Countries ◽  
Tourism Sector ◽  
The Relationship ◽  
Survey Approach

The push for the “halal tourism’ attribute in Muslim countries is quite enthusiastic. There are great interest and encouragement from tourists. Explicitly, currently, several regions in Indonesia such as Ponorogo Regency are trying to realize this concept. In this paper, we have the ambition to see how much influence “halal tourism’ has in Ponorogo Regency. Through variable boundaries, the relationship between religiosity, awareness, and interest can be found. This study attempt to reach all stakeholders who are already involved in the tourism sector. The survey approach was carried out by open interviews, where data was collected based on 409 informants. A multiple linear regression model is applied to answer the hypothesis design empirically. As a result, the informants who are divided into 5 groups who have experience in the field of tourism consider the concept of ‘halal tourism’ quite urgent to be revitalized. Other analyzes also found that religiosity and awareness had a significant effect on interest (p <0.05). Awareness plays an important role in the relationship between religiosity and interests. The originality of this invention lies in the elements (variables and items) used, therefore it deserves to be used as a reference at a later date by decision-makers.

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