Planning Policies and Strategies Implementation Effects on Accelerated Development in The Pesisir Barat Regency, Lampung Province
Muttaqin*, Budi Supriyatno, Rahimullah
Master of Government Science Study Program, Universitas Satyagama, Indonesia
Email: [email protected]*
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Article Information |
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ABSTRACT |
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Received: February 19, 2023 Revised: February 28, 2023 Approved: March 20, 2023 Online: March 24, 2023 |
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This study aims to analyze the effect of the implementation of policies and planning strategies on the acceleration of development in the Pesisir Barat Regency, Lampung Province, by looking at how the implementation of policies is linked to the implementation of policies and planning strategies with the acceleration of development in the Pesisir Barat Regency, Lampung Province. In addition, the research is limited to the object of research, namely in the Pesisir Barat Regency, Lampung Province. This study uses a quantitative method with explanatory research type, with a population of 98 and a research sample of 49 people determined by the Slovin formula. The data collection technique in this research is the questionnaire and library techniques. The research hypothesis proves that there is a significant and positive influence on the Implementation of Planning Policies and Strategies on the Acceleration of Development. Based on the results of the study, it can be concluded that there is a significant and positive effect of Policy Implementation on the Acceleration of Development of 97.1% and there is a significant and positive influence of Planning Strategy on the Acceleration of Development of 90.5%, where together there is a significant and positive effect of motivation. and the provision of compensation for employee performance by 97.2% with the dominant indicators of accelerated development being attention, responsibility and action programs from strategies in the Acceleration of Development in Pesisir Barat Regency - Lampung Province. |
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Keywords |
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policy implementation; planning strategy; development acceleration |
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INTRODUCTION
In accordance with the 1945 Constitution of the Republic of Indonesia Article 18 (1-5), the territory of the Unitary State of the Republic of Indonesia is divided into provincial regions and provincial regions are divided into regencies/cities, each of which has regional administrations to carry out regional autonomy covering an area of breadth (Wijayanto, 2014). Regional autonomy is the right, authority and obligation of an autonomous region to regulate and manage its own government affairs and the interests of the local community in accordance with statutory regulations. The availability of regulatory opportunities for the division of autonomous regions, or the formation of new autonomous regions, is actually not a new thing in the history of local government in Indonesia (Iskatrinah & Supriyo, 2021). Since the centralized government system in the New Order era, the government has also carried out a lot of forming new autonomous regions. Sub-districts that have increasingly strong urban character are then made Administrative Cities, a deconcentrative regional government unit (field administration) (Aritonang & No, 2017). Furthermore, when this character has strengthened, the area is made a Municipality which is on the same level as the Regency Government. Apart from that, it is also possible to form a new district or provincial government. However, during the New Order period from 1966 to 1998, there was no significant addition of new autonomous regions. The boom in the addition of new autonomous regions, or what is commonly called regional expansion, only occurred after 1999. Amidst the desire of various parties to rationalize regional expansion, the process of regional expansion continued almost every year in the 1998-2008 period.
From a regulatory perspective, the New Order and post-New Order governments gave opportunities for regional expansion. The difference lies in the process of proposing expansion. During the New Order era, the central government played a major role in preparing for the formation of an autonomous region (from the district capital, to an administrative city and then a municipality) and initiated its formation (Reza, 2014). In the post-New Order era, existing regulations emphasized proposals for regions to split themselves in order to form new autonomous regions. However, the existing regulations try to filter the proposed division by considering the capacity of the area to be formed. In addition, not only expansion is possible. But the merging of several regions into one autonomous region was also given a chance.
Based on Law Number 32 of 2004 concerning Regional Government which was renewed by Law no. 23 of 2014 concerning Regional Government (hereinafter written the Regional Government Law), the formation of regions basically aims to improve public services in order to accelerate the realization of social welfare. Regional formation can be in the form of division of one area into two or more areas, or a merger of parts of adjacent areas, or a merger of several regions (Bauw, 2018). Regional expansion is the splitting of a province or district/city into two or more regions. While in practice until 2008, Indonesia had never had any experience of merging regions.
Previously, the procedures for establishing, abolishing and merging regions regulated in Government Regulation Number 129 of 2000 were replaced by Government Regulation Number 78 of 2007 concerning Procedures for Formation, Abolition and Merger of Regions (hereinafter written PP 78/07) (Saputra, nd). PP 78/07 regulates the process of regional formation based on 3 (three) requirements, namely administrative, technical and physical territorial (Adlin & Satlita, 2018).
With these requirements, it is expected that the newly formed regions can grow, develop and be able to carry out regional autonomy in order to improve optimal public services in order to accelerate the realization of social welfare and in strengthening the integrity of the Unitary State of the Republic of Indonesia. In the formation of regions, this should not result in the main regions being unable to carry out regional autonomy, so that the objectives of forming regions can be realized with the addition of regional studies.
This regional study is the result of a team study formed by the head of the region concerned to objectively assess the feasibility of forming a new autonomous region which contains a quantitative assessment of technical factors (Sulaeman, 2018). This quantitative assessment is complemented by projections of the dominant factors (population, regional potential, economic capacity and financial capacity) for 10 (ten) years and the Spatial Plan for the Main Area as well as a qualitative assessment of other factors which have their own characteristics, including resource potential unexplored nature, ethnic conditions, conflict potential and history.
Rules regarding the procedures for forming regions, both those regulated in PP no. 129/00 and PP No. 78/07 strongly emphasizes the strong support and regional initiatives in the process of initiating the formation of regions. This is clearly seen if we follow the flow of the process for initiating regional expansion in accordance with Articles 14 to 21 of PP No. 78 of 2007
As previously mentioned, one of the motivations for forming new regions is inseparable from the guaranteed transfer of funds from the central government to the regional governments. In this era of decentralization, this form of transfer funds is known as a balancing fund which consists of the General Allocation Fund (DAU), the Special Allocation Fund (DAK), and the Revenue Sharing Fund (DBH) for both tax-sharing and natural resource revenue-sharing (Amalia et al., 2015). The largest component of transfers from the central government to regional governments is the DAU. The impact of regional expansion on DAU allocations and ultimately burdening the APBN is actually more indirect. This is because the DAU allocated is based on the calculation of the main area and only then is it distributed based on a certain proportion between the main area and the newly created area.
Of course, as a new region, the DAU revenue is more directed at building government infrastructure such as government offices, official residences, and other expenses related to personnel spending. Expenditures related to government apparatus clearly have little effect on the surrounding community. The provision of public goods to the community will certainly be reduced because in the early years of regional expansion, development was more focused on building government facilities (Maulana, 2019). Therefore, the flow of DAU to the newly created regions becomes an opportunity loss for the provision of infrastructure and public services to the community. This amount is certainly not small.
Thus, the BPK has a strategic role in assisting the DPR, DPRD and DPD in supervising the government budget to be efficient and effective so as to create good governance by carrying out audits of the management and accountability of state finances in accordance with the mandate of Law Number 15 of 2004 concerning Audit Management and State Financial Responsibility (Cahyani & Hermawan, 2018).
StudyThe Influence of Policy Implementation and Planning Strategy on the Acceleration of Development in Pesisir Barat District - Lampung ProvinceThis is intended as a concept of applying government science, especially government management, to be able to enrich knowledge scientifically and practically and the objectives of this research are; (1) to find out and analyze the effect of Iimplementation of the Policy for the Acceleration of Development of the West Coast District of Lampung Province, (2) to find out and analyze the influence of the Planning Strategyon the Acceleration of Development of the West Coast District of Lampung Province, and (3) to find out and analyze the effect of Iimplementation of the Policy and Planning Strategy jointly for the Acceleration of Development of the West Coast District of Lampung Province.
METHODS
In this research on the Effect of Policy Implementation and Planning Strategy on the Acceleration of Development in Pesisir Barat Regency - Lampung Province, it was carried out with a quantitative approach research that is explanatory or explanatory in the sense that statistical tests are carried out, to find out how much the strength of the relationship between the independent variables (free) and the variable un-independent (bound), either individually or jointly.
The population is 98 consisting of employees of the Regional Development Planning Agency, community leaders (Customary, Religious, Cultural, Social and Political) 45 people, members of the Regency DPRD (Representatives of Commissions 1-3 and Fractions) 17 people and development actors (Representatives of ASN, Laborers, Honorary, Fishermen, Traders, Farmers, Entrepreneurs) 36 people.
Population as much98 people, with the slovin formula above and the precision level set at 10%, the number of samples is known as follows:
98
n =
1 + (98) (0,1)2
98
n =
1 + 1,98
= 49 samples
Data collection can be done with two sources, namely primary and secondary sources. Primary sources are data sources that directly provide data to data collectors, and secondary sources are sources that do not directly provide data to data collectors, for example through other people or through documents.
Data analysis technique
In the process, after the researcher collects data and processes the data, the next step is to analyze it. The data obtained in the form of an ordinal scale is then scored which is then described through the use of the Frequency Distribution Table for the purposes of analyzing data.
The data analysis technique used in this study is inference statistical analysis or inductive statistics. In analyzing the data carried out through several stages, including; (1) tabulation of data from the results of respondents' answers, (2) make a frequency distribution of respondents' answers, and (3) testing the relationship between the independent variables and the dependent variable.
As a tool to measure and examine the relationship between the independent variable and the dependent variable (Acceleration of Development), where the independent variable consists of more than one variable (Policy Implementation and Planning Strategy), data testing is carried out using correlation analysis. Meanwhile, to find out whether the level of relationship between these variables is significant or not, testing the correlation coefficient is used through a test test.
The data obtained from the results of distributing questionnaires in the West Coast District Government, given a predetermined score and analyzed using statistical tests. Statistical analysis was processed using the Statistical Product for Service Solution (SPSS) 16.0 for windows computer program. The steps taken by the authors in this study are as follows:
Descriptive statistics
The results of the calculation of Descriptive Statistics from the independent variables (X1 and X2) and the dependent variable (Y) can be in the form of statistics such as the mean, median, maximum, minimum, standard deviation, skewness and kurtosis values; and displays in the form of histograms and graphs.
Validity and Reliability Test
Validity test
According to Singarimbun and Effendi (2003), validity is an index that indicates the extent to which a data measurement tool is able to measure what is to be measured in this study. Thus, validity is a criterion that is used as a benchmark to indicate the level of validity of a data measuring instrument. An instrument or data measuring tool is said to be valid or legitimate, if the instrument is used to extract data it will produce data that has high validity and vice versa. Test the validity by using the Product Moment Correlation formula, namely:
Information:
rxy : product moment correlation coefficient
x : independent variable
y : dependent variable
n : number of respondents
Reliability Test
Reliability according to Singarimbun and Effendi (2003) shows the consistency of an instrument or data measuring tool in measuring the same phenomenon.
If an instrument or data measuring device is used twice or more to measure the same symptoms and the measurement results obtained are relatively consistent, then the measuring device is said to be reliable.
Reliability test research uses the Spearman Brown formula, namely by correlating the answers to the even questions, then the internal reliability.
rj =
=
=
Where :
rj = Correlation
k = Number of independent variables
S2 = Variances
JK = Squared sum
n = Sample
S = Amount
Classic assumption test
Data Normality Test
The normality test is used to test in a regression model, the dependent variable, the independent variable or both have a normal distribution or not. A good regression model is a normal distribution or close to normal.
The data normality test was carried out by the One-Sample Kolmogorov-Smirnov Z Test. The basis for making the decision is that if the Kolmogorov-Smirnov Z value is greater than 0.05 (5%), then the data is said to be normally distributed or meets the normality requirements.
Heteroscedasticity
This test is carried out to show that the variance of each error is heterogeneous, which means it violates the classical assumption which requires that the variance of the error must be homogeneous. The steps in testing heteroscedasticity are as follows:
Ho : There is no heteroscedasticity
Ha : There is heteroscedasticity
Testing is done using the Glejser decision test:
a) If significant (probability) < 0.05 Ho is rejected
b) If significant (probability) > 0.005 Ho is accepted.
Autocorrelation
Autocorrelation shows that there is a correlation between the error and the previous period's error which, according to the classical assumption, this should not happen. The problem of autocorrelation is only relevant if the data used is time series data. Autocorrelation testing can also be done with Durbin Watson. The decisions taken in the autocorrelation test with the Durbin Watson test are:
a) DW numbers below –2 means there is a positive autocorrelation.
b) DW numbers between –2 to + 2, means there is no autocorrelation.
c) A DW number above +2 means that there is a negative autocorrelation.
Multicollinearity
Multicollinearity is done to show that the independent variables have a direct relationship (correlated). The consequence of multicollinearity will cause the regression questionnaire to have a small value, if the regression standard error is large, the individual test is not significant. The characteristics of multicollinearity are high R2, significant F-test but many t-tests are not significant. The steps in multicollinearity testing are carried out as follows:
Ho = No multicollinearity
Ha = There is multicollinearity
By using decision making as follows:
a) If the Variance Inflation Factor (VIF) > 10 then Ho is rejected (there is multicollinearity)
b) If the Variance Inflation Factor (VIF) < 10 then Ho is rejected (no multicollinearity).
Determination Analysis
To test the suitability of the multiple regression model, the Coefficient of Determination (R2) is used to explain the variability of the dependent variable of the regression equation model used, especially of the independent variables used.
Linear Regression Analysis
Regression according to is a measuring tool that is also used to measure whether or not there is a correlation between variables. Linear regression is a regression in which the independent variable (variable X) has the highest rank of one (Hasan, 2008). To test the variable Policy Implementation on the Acceleration of Development, a simple linear regression model Y over X1 is used with the formula:
Ŷ = a+bX1
To examine the role of the Planning Strategy variable on the Acceleration of Development, the formula is used:
Ŷ = a+bX2
Hypothesis testing
The hypothesis test design is used to test the hypotheses proposed in this study, whether the statistical values resulting from the results of statistical analysis can be generalized or applied to the population.
arithmetic t test
To test the hypothesis or each regression coefficient is done by t test with the following formula:
bi – 0
t arithmetic = –––––––
Se (bi)
Where Se (bi) is the standard error of the guess parameterbi.
The hypothesis proposed in carrying out a significant test of the simple regression coefficient is:
Ho : b = 0 (regression coefficient is not significant)
Ha : b ≠ 0 (significant regression coefficient)
The criteria for testing the hypothesis are as follows:
If the t-test value < t-table value, then Ho is accepted
If the t-test value > t-table value, then Ho is accepted
Arithmetic F test
Simultaneous hypothesis testing is carried out by the F test. The test statistics used in the F test are:
SSR / k
F arithmetic = ––––––––––
SSE / n-k-1
Where:
SSRS = Sum of squared regression
SSE = Sum of squares of remainder
n = Number of samples
k = Number of independent variables
The hypothesis proposed in carrying out a significant test of the multiple regression coefficients is:
Ho : b1 = b2 (There is no significant effect between X1and X21 against Y)
Ha : b1 ≠ b2 (There is a significant effect between X1and X2 against Y)
The criteria for testing the hypothesis are as follows:
If the value of the F-test < the value of the F-table, then Ho is accepted
If the F-test value > F-table value, then Ha is accepted
Hypothesis Test Design
The hypothesis to be tested in this study can be formulated as follows:
H0: b1 = 0
There is no significant and positive influencePolicy Implementation for the Acceleration of Development of the West Coast District of Lampung Province.
Ha:b1¹0
There is a significant and positive influencePolicy Implementation for the Acceleration of Development of the West Coast District of Lampung Province.
H0: b2 = 0
There is no significant and positive influencePlanning Strategy for the Acceleration of Development of the West Coast District of Lampung Province.
Ha:b2¹0
There is a significant and positive influencePlanning Strategy for the Acceleration of Development of the West Coast District of Lampung Province.
H0: b1 : b2 = 0
There is no significant and positive influenceImplementation of Policies and Planning Strategies together for the Acceleration of Development of the West Coast District of Lampung Province.
Ha:b1 :b2¹0
There is a significant and positive influenceImplementation of Policies and Planning Strategies together for the Acceleration of Development of the West Coast District of Lampung Province.
RESULTS
In this study, researchers wanted to assess whether there was an influence of policy implementation and planning strategies on the acceleration of development in West Coast District - Lampung Province. The following is the result of data processing that has been obtained through filling out questionnaires for 49 respondents. Based on calculations using SPSS 24 for windows and Ms.excel, a description of the variable data for Policy Implementation (X1), Strategy Planning (X2), and Acceleration of Development (Y) is obtained as follows:
Policy Implementation (X1)
The results of processing data processed using Ms.Excel on the policy implementation variable obtained a description, namely the average score of respondents' answers was 4.18; the average maximum value of respondents' answers is 4.51, which is a program indicator and the minimum average value of respondents' answers is 3.82, which is an indicator of improving work programs. To find out the average distribution of respondents' answers to the policy implementation variable can be seen in table 1.
Table 1. Policy Implementation Variable Average Score (X1)
Planning Strategy (X2)
The results of data processing which were processed using Ms.Excel on the planning strategy variable obtained a description, namely the average score of respondents' answers was 4.17; the maximum value of the average respondent's answer is 4.51, which is an indicator of attention and the minimum value of the average respondent's answer is 3.82, which is an indicator of understanding. To find out the average distribution of respondents' answers to the planning strategy variables can be seen in table 2
Table 2. Planning Strategy Variable Average Score (X2)
Development Acceleration (Y)
The results of data processing which were processed using Ms.Excel on the development acceleration variable obtained a description, namely the average score of respondents' answers was 4.17; the maximum value of the average respondent's answer is 4.51, which is an indicator of independence and the minimum value of the average respondent's answer is 3.82, which is an indicator of value. To find out the average distribution of respondents' answers to the development acceleration variable can be seen in table 3
Table 3. Development Acceleration Variable Average Score (Y)
Testing Requirements Analysis
The analysis requirements test in the study of the Influence of Policy Implementation and Planning Strategy on the Acceleration of Development in Pesisir Barat Regency - Lampung Province is a data instrument test in the form of a validity test and a reliability test. For each test described as follows:
Validity test
Validity test was conducted to determine the level of validity of the instrument (questionnaire) used in data collection. The validity requirement of the instrument (questionnaire) is the value of r count > r table. Based on the results of the analysis using the "product moment" correlation technique, the r count for each variable is obtained as follows:
Policy Implementation Variable (X1)
Table 4. Results of Validity Test of Policy Implementation Variables (X1)
From the table above it can be seen thatthe r-count value of all policy implementation variable question instruments obtained is greater than r-table (0.275), then all 20 research data instruments are said to be valid. The dominant indicators are skills, providing opportunities, solving problems, and providing corrections.
Planning Strategy Variable (X2)
Table 5. Results of the Validity Test of Planning Strategy Variables (X2)
From the table above it can be seen thatthe r-count value of all the planning strategy variable question instruments obtained is greater than the r-table (0.275), then all 20 research data instruments are said to be valid. The dominant indicators are quality, organizational goals, efficiency and effectiveness as well as aspects of image.
Personnel Performance Variable (Y)
Table 6. Variable Validity Test ResultsDevelopment Acceleration (Y)
From the table above it can be seen thatthe r-count value of all question instruments on the accelerating development variable obtained is greater than r-table (0.275), so all 20 research data instruments are said to be valid. The dominant indicators are attention, responsibility, incentives, and action programs.
Reliability Test
Reliability tests are carried out to determine whether the instrument is used more than once, will produce consistent data.In this study, the reliability test was carried out using the Alpha Cronbach technique. The instrument is declared reliable if the Alpha Cronbach value > r-table (0.275).
Table 7. Reliability Test Results
Based on the results of instrument reliability testingindicates that the instrument used is reliable, which means that the instrument can be trusted enough to be used as a data collection tool.
Classic assumption test
The classical assumptions tested consist of three tests, including the normality test, multicollinearity test, and heteroscedasticity test.
Normality test
Normality test to determine whether the dependent variable, independent or both are normally distributed, close to normal or not. To be able to see whether the multiple regression model has normal distribution or not, the One-Sample Kolmogorov-Smirnov test is used on unstandardized residual data at a significance level (α) of 0.05. If the significance value is greater than 0.05, it indicates that the data is normally distributed.
Table 8. Probability Value of the One-Sample Kolmogorov-Smirnov Test
Based on the table above, it can be seen that the Kolmogorov-SmirnovZ value is 0.113 with a probability value of 0.158. Because the probability value of the estimated result is greater than the established significance level (0.158 > 0.05), it can be concluded that the unstandardized residual data has a normal distribution.
Heteroscedasticity Test
The heteroscedasticity test was carried out to find out whether in a regression model there is an unequal variance from the residuals of one observation to another. Estimation results using the help of the SPSS program application are presented through the Glejser test where the independent variables are regressed with unstandardized residual absolute data at a significance level (α) of 0.05. If the significance value of each independent variable is greater than 0.05, it indicates that the data has beenhas met the assumption of homoscedasticity.
Table 9. Glejser Heteroscedasticity Test Probability Value
Based on the table above, it can be seen that the magnitude of the probability value of each independent variable is Policy Implementation (X1) = 0.686 and Planning Strategy (X2) = 0.822. Because the probability value of the estimation results for each independent variable is greater than the specified significance level (0.05), it can be concluded that the datahas met the assumption of homoscedasticity.
Multicollinearity Test
The multicollinearity test aims to evaluate whether or not there is a strong correlation between independent variables, where a strong correlation between independent variables indicates that the use of independent variables in the regression model is not efficient. By using the help of the SPSS application program, the estimated results of the VIF value of each independent variable for the multicollinearity test are as follows:
Table 10. Multicollinearity Test VIF Value
The VIF value estimation results presented in the table above show that the VIF value of each independent variable is below the critical value of 10, namely Policy Implementation (X1) = 9.486 and Planning Strategy (X2) = 9.486. Based on these results, it can be concluded that there is no multicollinearity between the independent variables in the regression model.
Hypothesis test
Hypothesis testing was carried out in this study using simple linear regression and multiple linear regression. Based on testing using SPSS (Statistical Product and Service Solution) 24 for Window, the results of hypothesis testing can be obtained which can be explained as follows:
Effect of Policy Implementation on the Acceleration of Development
H0 : ß1 = 0 : there is no effect of policy implementation on the performance of accelerated development
Ha : ß1 ≠ 0 : there is an effect of policy implementation on the performance of accelerated development
If t arithmetic > t table, then H0 is rejected and Ha is accepted.
t test
Table 11. The results of the t-test variable X1 against Y
Based on the calculation results of SPSS (Statistical Product and Service Solution) 24 for Window, the t arithmetic value is 39.353 and the ttable with df nk-1 = 49-2-1 = 46 at α (0.05) is 1.678. Thus t arithmetic 39.353 > t table 1.678 so that H0 is rejected and Ha is accepted. This shows that policy implementation has a positive and significant effect on accelerating development.
Determination Analysis
Table 12. Coefficient of Determination of Variable X1 to Y
Based on the calculation results of SPSS (Statistical Product and Service Solution) 24 for Window the value of the coefficient of determination (R2) is 0.971. This shows that 97.1% of the variation in the acceleration of development is caused by the diversity of policy implementation, while the remaining 2.9% is caused by other variables.
Simple Linear Regression Equations
As forThe simple linear regression equation for the influence of policy implementation on accelerated development is as follows:
- Ŷ = a + b1X1
- Ŷ = 0.194 + 0.951X1
This linear regression equation shows that every 1 increase in the value of the policy implementation variable can increase the value of development acceleration by 1.145 with an estimate of the constant work discipline variable.
The Effect of Strategic Planning on the Acceleration of Development
H0 : ß2 = 0 : there is no effect of the planning strategy on the acceleration of development.
Ha : ß2 ≠ 0 : there is an effect of strategic planning on accelerated development
If tcount > ttable, then H0 is rejected and Ha is accepted.
t test
Table 13. The results of the t test of the variable X2 against Y
Based on the calculation results of SPSS (Statistical Product and Service Solution) 24 for Window, the t arithmetic value is 21.189 and the t table with df nk-1 = 49-2-1 = 46 at α (0.05) is 1.678. Thus t arithmetic 21.189 > t table 1.678 so that H0 is rejected and Ha is accepted. This shows that the planning strategy has a positive and significant effect on accelerating development.
Determination Analysis
Table 14. Coefficient of Determination of Variable X2 to Y
Based on the calculation results of SPSS (Statistical Product and Service Solution) 24 for Window the value of the coefficient of determination (R2) is 0.905. This shows that 90.5% of the variation in the acceleration of development is due to the diversity of planning strategies, while the remaining 9.5% is due to other variables.
Simple Linear Regression Equations
The simple linear regression equation from the influence of policy implementation on accelerated development is as follows:
- Ŷ = a + b2X2
- Ŷ = 0.053+ 0.987X2
This linear regression equation shows that every 1 increase in the value of the planning strategy variable can increase the value of accelerated development by 1.030 with an estimated constant leadership variable.
Effect of Policy Implementation and Planning Strategy on the Acceleration of Development
H0 : ß1 = ß2 = 0 : there is no effect of implementing policies and planning strategies together on accelerating development.
Ha : one or both β≠ 0 : there is an effect of the implementation of policies and planning strategies together on accelerated development.
If F arithmetic > F table, then H0 is rejected and Ha is accepted.
F test
Table 15. F Test Results (Anova Table)
Based on the calculation results of SPSS (Statistical Product and Service Solution) 24 for Window, the F arithmetic value obtained is 790.472 and F table with df nk-1 = 49-2-1 = 46 at α (0.05) is 3.20. Thus F arithmetic 790.472 > F table 3.20 so that H0 is rejected and Ha is accepted. This shows that the implementation of policies and planning strategies together to accelerate development.
Determination Analysis
Table 16. Coefficient of Determination
Based on analysisobtained a coefficient of determination of 0.972. This shows that 97.2% of the variation in the acceleration of development is due to the diversity of policy implementation and planning strategies, while the remaining 2.8% is caused by other variables not examined.
Multiple Linear Regression Equations
Table 17. Multiple Linear Regression Equations
The linear regression equation from multiple linear regression analysis of the influence of policy implementation and planning strategies on accelerated development is as follows:
Ŷ = a + b1X1 + b2X2
Ŷ = 0.139 + 0.844X1 + 0.121X2
The definition of the multiple linear regression equation above are; (1) every 1 increase in the value of the policy implementation variable can increase the acceleration of development by 0.983 with an estimated constant planning strategy variable, (2) every 1 increase in the value of the planning strategy variable can increase the acceleration of development by 0.260 with an estimated constant policy implementation variable, and (3) every 1 increase in the value of the policy implementation variable and 1 value of the planning strategy variable together, can increase the acceleration of development by 1.243.
DISCUSSION
Effect of Policy Implementation on the Acceleration of Development
Based on the results of research data analysis that has been done, it has been proven that policy implementation has a positive and significant effect on accelerating development in West Coast District - Lampung Province. The coefficient of determination of the effect is equal to 97.1%. The positive effect of policy implementation on accelerating development indicates that better policy implementation will be able to increase the acceleration of development in West Coast District - Lampung Province.
The results of this study are in line with research conducted by Moch Fitra Repas Alamindah (2016) with the title Implementation of West Ring Road Infrastructure Development Policy in the Context of Accelerating Development of the Kepanjen Region (Study in Malang Regency) (Alaminda, 2016). In his research, it is known that the implementation of the western ring road development policy has succeeded in accelerating the development of the Kepanjen area because it fulfills the aspects that must be met.
Based on the policy implementation model according to Donald Van Metter and Carl Van Horn, the dimensions and objectives of the policy explained that measuring the performance of policy implementation certainly emphasizes certain standards and targets that must be achieved by policy implementers (Solichin, 2015). Policy performance is basically an assessment or level of achievement of these standards and targets. An understanding of the general intent of a standard and policy objectives is important. Successful policy implementation may fail when implementers are not fully aware of the standards and objectives of the policy. Standards and policy objectives have a close relationship with the disposition of the implementers. The direction of disposition of implementers towards policy standards and objectives is also crucial. Implementation may fail in carrying out the policy, because they refuse or do not understand what is the purpose of a policy.
Regulations and targets have been set since the beginning, but in practice some were not achieved and some were achieved. Because based on the theory of Van Meter and Van horn above, it says that successful policy implementation may fail when implementers are not fully aware of the standards and objectives of the policy (Kurniawan & Maani, 2019). Like the program that was set from the start, namely preparing for accelerated development in the West Coast District - Lampung Province, here the West Coast District Government is trying to realize the development of the West Coast District more quickly and effectively than before. In its implementation, accelerated development will be achieved if the implementing instruments can implement the policy properly.
The Effect of Planning Strategy on the Acceleration of Development
Based on the results of research data analysis that has been done, it has been proven that the planning strategy has a positive and significant effect on accelerating development in West Coast District - Lampung Province. The coefficient of determination of the influence is equal to 90.5%. The positive influence of the planning strategy on accelerating development indicates that the better the planning strategy will be able to increase the acceleration of development in West Coast District - Lampung Province.
The results of this study are in line with research conducted by Rangkuti (2017) namely the Strategy for Development of Underdeveloped Regions in Efforts to Accelerate Rural Economic Development in South Labuhanbatu District. In this study it is known that there is a relationship between the hierarchy of physical potential and the hierarchy of levels of equitable development, in which areas that have high physical potential and high equity will affect the acceleration of development and their welfare.
The development planning strategy aims to optimize the use of potential while reducing development disparities between regions. Sometimes there are many problems in its implementation, including a lack of planning consistency to problems with planning implementation in the field. In addition, the space for local government in planning and managing development with priority according to regional potential is limited. In Regional Autonomy, various aspects that are closely related to development planning relate to the allocation of resources, increasing the role of the community, regional potential and diversity. All of these aspects are combined in a unified national development system (Bastian, 2006).
In looking at the characteristics of implementing agencies, as stated by Van Meter and Van Horn (1975), then this discussion cannot be separated from the bureaucratic structure. Bureaucratic structure is defined as the characteristics, norms and patterns of relationships that occur repeatedly in executive bodies that have both potential and actual links with what they have by executing policy. At the South Labuhanbatu Regency Development Planning Agency it would be good if there was one area that controlled the e-planning system, namely the Administration, People's Welfare and Research and Development Division which developed a planning strategy which would certainly accelerate the development process. If the bureaucratic structure can place employees according to their abilities and not be complicated, fast and effective development will be achieved.
Effect of Policy Implementation and Planning Strategy on the Acceleration of Development
Based on the results of research data analysis that has been carried out, it has been proven that together the implementation of policies and planning strategies has a positive and significant effect on accelerating development in Pesisir Barat Regency - Lampung Province. The coefficient of determination of the effect is equal to 97.2%. The positive influence of planning strategies on accelerating development indicates that better implementation of policies and planning strategies will be able to increase the acceleration of development in West Coast District - Lampung Province.
The success of a policy promoted by the government has different characteristics and models. Where in the context of public policy the success of a policy lies in the element of implementation by the government which is developing its region or is realizing the mission of accelerating government development. The acceleration of development also cannot be separated from the existence of a well-thought-out planning strategy. A development planning bureaucracy that understands planning strategies and is able to implement them is important to develop in terms of accelerating regional development.
The concept of regional development is inseparable from commitment and consistency in the planning, implementation and fundamental changes in an area. The old paradigm that considers development is as if the government's "masterpiece" must be transformed into development as an effort of people's creativity (Samugyo, 2013). Regional development is basically a process that is dynamic, complex, and has multiple dimensions. Even if all stakeholders are involved, the results are not necessarily satisfactory. In other words, unwanted results (externalities) are always born, especially with regard to unemployment, mistargeted subsidies, and poverty. That is why the conceptual basis for regional development is directed at development that is effectively capable of dealing with development problems in each region.
This is where the role of the Regional Government is in utilizing the potentials of the Region they have, meaning that the Region must have the ability to utilize all of its potential so that it runs in a unified movement. Therefore the regions need to continuously update the concept of partnership between regional potentials, so that no regional potential feels left out in the development process with its planning and implementation strategy.
CONCLUSION
Policy implementation has a positive and significant effect on the Acceleration of Development in West Coast District - Lampung Province with a coefficient of determination of 97.1% and the dominant indicators are skills, providing opportunities, solving problems, and providing corrections.
Planning strategy has a positive and significant effect on the Acceleration of Development in West Coast District - Lampung Province with a coefficient of determination of 90.5% and the dominant indicators are quality, organizational goals, efficiency and effectiveness as well as aspects of image
Implementation of Policies and Planning Strategies together have a positive and significant effect on the Acceleration of Development in West Coast District - Lampung Province with a coefficient of determination of 97.2% and the dominant indicators of accelerated development are attention, responsibility, incentives and action programs.
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