scholarly journals Pre Clearance Analysis on Dwelling Time for Imported Container (Case Study: Boom Baru Port)

2020 ◽  
Vol 5 (7) ◽  
pp. 595-600
Author(s):  
Aulia Safira ◽  
Erika Buchari ◽  
Edi Kadarsah
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Equation Model ◽  
Study Data ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Clearance Time ◽  
Preparation Time ◽  
Dwelling Time

Dwelling time is one of many problems that happens in Boom Baru Port. Dwelling time itself consists of pre-clearance, customs clearance, and postclearance stages. One of the causes of high dwelling time is in the pre-clearance stage due to the length of time for obtaining a product permit, especially for imported commodities. The reasons for the length of time for obtaining this permit include the process of obtaining permits for prohibited and restricted goods, the process of quarantine, preparation of documents. In this study data were acquired through distributing questionnaires to forwarding companies. The analysis is done by entering the variables that has an effect toward the preclearance time at the Boom Baru Port so an equation model that can predict the length of pre-clearance time will be found. After data were analyzed using multiple linear regression, equation Y= 1,384 + 0,380 X1 + 1,078 X2 + 0,290 X3 is achieved, which X1 is the Prohibited and Restricted Goods Permit Process, X2 is the Quarantine Process, dan X3 is Documents Preparation Time.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN KONSUMEN DALAM MEMBELI MOBIL MITSUBISHI PADA PT. LAUTAN BERLIAN UTAMA MOTOR BENGKULU

2018 ◽  
Vol 1 (1) ◽  
pp. 53
Author(s):  
Hermawati Sulaiman
Keyword(s):  
Quantitative Analysis ◽  
Linear Regression ◽  
Qualitative Analysis ◽  
Multiple Linear Regression ◽  
Likert Scale ◽  
Positive Influence ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Design Quality ◽  
Consumer Decisions

The purpose of this study was to determine whether design, quality and service had an effect on consumer decisions in buying Mitsubishi cars at PT. Lautan Berlian Utama Motor. In this study the methods used are quantitative analysis and qualitative analysis. The technique of sampling this study was used by accidental sampling. To facilitate the measurement of scores from the questionnaire so that the calculation is correct, then each item is given a score based on the Likert scale. From the multiple linear regression equation it was found that design (X1), quality (X2), and service (X3) had a positive influence on consumer decisions so that buying a Mitsubishi car at PT. Ocean of Berlian Utama Motor Bengkulu.

scholarly journals FAKTOR YANG MEMPENGARUHI KESELAMATAN BERKENDARA MOBIL DIRUAS JALAN TOL SEMARANG-BAWEN PROPINSI JAWA TENGAH

2020 ◽  
Author(s):  
Andar Sri Sumantri ◽  
Irfan Misbahudin
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Road Safety ◽  
Driving Behavior ◽  
Regression Equation ◽  
Driving Safety ◽  
Linear Regression Equation ◽  
The Road ◽  
Multiple Linear Regression Equation ◽  
Road Condition

<p>Driving safety is influenced by various such as road conditions vehicle condition, driving behavior, knowledge of driving. All four have an important role in influencing the safety of driving. The purpose of this study was to determine whether there is influence of road conditions, vehicle conditions,driving behavior, knowledge of driving on roads Toll-Bawen Semarang Central Java Province either partially or simultaneously.<br />Results of statistical analysis tools SPSS (Statistical Product And Service Solutions) Ver. 22.0 multiple linear regression equation Y= 2,568 +0,268 X1 + 0,266 X2 + 0,216 X3 +0,148 X4 ( The results of multiple linear regression equation showed that there were significant positive influence on Keselamatan drive the road condition (t = 3,229&gt; t tabel = 1,9853) the condition of vehicle on road safety (t =2,624&gt; t tabel = 1,9853 the driving behavior of the safety driving (t = 3,037 &gt; t tabel = 1,9853, drive to the road safety knowledge ( t = 2,139 &gt; table = 1,9853) individually and simultaneously influence, vehicle conditions perilaku driving, and driving knowledge together –have the same effect as 26,529 &gt; F Tabel 2,46. The fourth influence is very strong research variable with the coefficient of determination (R2) were obtained for 50,8 of the safety of driving and 49,2 % are influenced by variable that are not detectedin this study</p><p><strong>Keywords : Road condition, Vehicle condition, Driving behavior, Knowledge of driving, and Driving safety.</strong></p><p> </p><p>Keselamatan berkendara dipengaruhi oleh berbagai factor diantaranya adalah kondisi jalan, kondisi kendaraan, perilaku pengendara, pengetahuan berkendara. Tujuan dari penelitian ini adalah untuk mengetahui ada tidaknya pengaruh antara kondisi jalan, kondisi kendaraan, perilaku pengendara, pengetahuan berkendara diruas jalan Tol Semarang Bawen Propinsi Jawa Tengah. Dalam penelitian ini yang menjadi populasi adalah pengguna mobil golongan I dijalan tol semarang bawen provinsi jawa tengah berjumlah 100 orang. Variabel dalam penelitian ini terdiri dari : Variabel bebas yaitu kondisi jalan x1, kondisi kendaraan perilaku berkendara x3 dan pengetahuan berkendar serta variable terikat yaitu keselamatan berkendara. Semua hipotesis yang diajukan dalam penelitian ini diterima, sehingga model tersebut mengambarkan hubungan yang kausalitas yang terjalin antar variable. Hasil analisi dengan alat bantu statistic program spss ver.22 . Dari hasil persamaan regresi linier berganda menunjukkan bahwa ada pengaruh yang positif dan signifikan antar masing-masing variable. Pengaruh keempat variable penelitian sangat kuat dengan nilai koefisien determinasi yang diperoleh sebesar 50,8% terhadap keselamatan berkendara dan 49,2 % dipengaruhi oleh variable yang tidak terdeteksi pada penelitian ini.</p><p><strong>Kata kunci : Kondisi Jalan, Kondisi Kendaraan, Perilaku Berkendara, Pengetahuan berkendara dan Keselamatan berkendara.</strong></p>

scholarly journals production of milk yield from udder circumference and distance between teats in West African Dwarf and red Sokoto goats

2021 ◽  
Vol 36 (1) ◽  
pp. 1-11
Author(s):  
M.N. Benji ◽  
O.A Osinowu
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Milk Production ◽  
Milk Yield ◽  
West African ◽  
Regression Equation ◽  
Predictive Equation ◽  
Linear Regression Equation ◽  
West African Dwarf ◽  
Independent Variables

Udder circumference (UD) and distance between teats (DBT) measured before and after  milking were used to determine CUC (UC before milking minus UC after milking) and CDT (DBT before milking minus DBT after milking).  All four parameters were utilized as independent variables in two milk yeild from 202 weekly records of 17 lactating does, consisting of 8 West African Dwarf (WAD) and 9 Red sokoto (RS) goats. WAD and RS goats hadsimilar mean values for daily milk yield ( 270.34±12.47 ml vs 245.26±14.51 ml) and UC(28.49±0.33 vs 28.49± 0.13 cm). Both models had significant ( P<0.001) R2 values ranging from 0.244 to 0.757. UC was the best index of milk yeild (R2=0.688) followed by CUC (R2=0.467) in the linear regressionequation while DBT and CDT yeilded lower R2 Values (0.244 vs 0.258).  Inclusion of all four parameters in the multiple linear regression equation yeilded the highest R2 (0.757). The predictive equation was Y= 441.443 + 25.739X1 + 23.349-21.265X2 +61.080X4 in which Y is milk yeilded, Xi , X4  represent UC, CUC, DBT and CDT respectively. Positive and significant (P<0.001) phenotypic correlations were observed between UCand milk yeilded (0.759), CUC and milk yeilded (0.690). DBT and milk yield (0.498), CDT and milk yield(0.508). In the current practice of collecting collecting weekly records, early prediction of future milk production from udder circumference measured prior to milking will be accurate using linear regression predictive equation. Alternatively, if more traits related to udder size such as UC, CUC,DBT and CDT are incorporated as independent variables in multiple linear regression equation, milk production would be predicted with better accuracy.

An Aspen Bark Factor Equation for Michigan

1991 ◽  
Vol 8 (1) ◽  
pp. 12-15
Author(s):  
Gary W. Fowler
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Tree Height ◽  
Prediction Equation ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Trembling Aspen ◽  
Breast Height ◽  
Relative Errors ◽  
Factor Equation

Abstract A multiple linear regression equation was developed to predict bark factor for aspen in Michigan as a function of tree height. Bark factors for bigtooth aspen were, in general, somewhat larger than bark factors for trembling aspen. Even though equations were developed for both species, the differences between the two equations were small, and not statistically significant, and a pooled equation based on both species is recommended. The pooled prediction equation yielded average relative errors from - 2.3 to 0.87% and - 1.02 to 3.83% at all tree heights for bigtooth and trembling aspen, respectively. For more accurate predictions of bark factor, the separate prediction equations for bigtooth and trembling aspen should be used. The new equations can be used to more accurately estimate tree and log wood volumes than when using a constant bark factor determined at breast height, which, in general, leads to underestimates of wood volumes. North. J. Appl. For 8(1):12-15.

scholarly journals ANALISIS FAKTOR STRATEGIK MANAJEMEN SUMBER DAYA MANUSIA UNTUK MENINGKATKAN KINERJA KARYAWAN

Akademika ◽  
2019 ◽  
Vol 8 (02) ◽  
pp. 117-128
Author(s):  
Dian Ika Ningrum ◽  
Tjiptogoro Dinarjo Soehari
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Work Environment ◽  
Significant Influence ◽  
Employee Performance ◽  
Regression Equation ◽  
Dominant Factor ◽  
Linear Regression Equation ◽  
Independent Variables ◽  
Analyze Data

Peningkatan kinerja karyawan sangat penting untuk mendukung jalannya bisnis perusahaan dibidang properti. Sehingga penelitian ini dijadikan sebagai dasar kebijakan untuk meningkatkan kinerja melalui variabel lingkungan kerja, kompetensi dan kompensasi. Metodologi yang digunakan dalam penelitian ini adalah metode kuantitatif eksploratif dan software SPSS for Windows versi 24. Adapun variabel yang digunakan yaitu Kinerja Karyawan (Y) sebagai variabel dependent sedangkan Lingkungan Kerja (X1), Kompetensi (X2) dan Kompensasi (Y) sebagai variabel independent. Penelitian ini dilakukan di PT Jasamarga Properti dengan populasi sebanyak 64 orang dan menggunakan sampel jenuh. Sehingga seluruh karyawan digunakan sebagai sampel. (1) Persamaan regresi linear berganda Y = 1,419 + 0,313 X1 + 0,199 X2 + 0,187 X3 + e; Rsquare = 0,759, F = 59,844 (2) Lingkungan kerja menjadi faktor paling dominan terhadap Kinerja Karyawan; (3) Kompetensi dan Kompensasi memiliki pengaruh yang signifikan terhadap Kinerja Karyawan. Hasil dari Kinerja Karyawan adalah sebesar 1,419. Apabila X1, X2 dan X3 dianggap nol maka akan mempengaruhi kinerja karyawan sebesar 1,419 dalam skala likert 1-5 termasuk kategori sangat tidak baik.     Abstract: Improvement employee performance is very important to support company’s business in property industry. Therefore, this research is used as a basic policy to improve employee performance. The methodology in this research is quantitative exploratory method and analyze data used software SPSS for Windows version 24. The variables are Employee Performance (Y) as dependent variable,  Work Environment (X1), Competence (X2) and Compensation (X3) as independent variables. This research was conducted at PT Jasamarga Properti with a population of 64 people as saturated samples. All employees are used as samples. (1) Multiple linear regression equation Y = 1.419 + 0.313 X1 + 0.199 X2 + 0.187 X3 + e; Rsquare = 0.759, F = 59.844 (2) The work environment is the most dominant factor in Employee Performance; (3) Competence and Compensation have a significant influence on Employee Performance. The results of Employee Performance are 1,419. If X1, X2 and X3 are considered zero, it will affect employee performance by 1.419 in the Likert scale 1-5. The result is that employee performance is categorized as a very bad category.    

scholarly journals PENGARUH PENERAPAN SELF ASSESSMENT SYSTEM, KESADARAN DAN PEMAHAMAN PERPAJAKANTERHADAP KEWAJIBAN MEMBAYAR PAJAK

2020 ◽  
Vol 1 (2) ◽  
pp. 150-167
Author(s):  
I Ketut Yudana Adi
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Sampling Methods ◽  
Regression Equation ◽  
Assessment System ◽  
The Self ◽  
Linear Regression Equation ◽  
System Implementation ◽  
Self Assessment ◽  
Probability Sampling

This study discusses the Influence of Self Assessment System Implementation, Awareness and Understanding of Tax Liability on Paying Taxes On KPP Pratama Badung Utara. The data in this study was obtained from questionnaires distributed to taxpayers registered in KPP Pratama Badung Utara using probability sampling methods. Respondents were used in this study were 98 responden.Uji hypothesis is used multiple linear regression equation Y = -7.874 - 0.083X1 + 0,522X2 - 0.048X3 + é where partial awareness of taxation affect the obligation to pay taxes is indicated by the level of Sig. 0.002 <0.05, while the self-assessment system and partial understanding of taxation does not affect the obligation to pay taxes, this is indicated by the level of Sig. respectively - variable massing 0.076> 0.05 and 0.759> 0.05, but simultaneously, self-assessment system, awareness and understanding of taxation positive and significant effect on the obligation to pay taxes, this is indicated by the level Sig.0.000 <0.05.

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