scholarly journals ANALISIS POTENSI SEKTOR BASIS DAN NON BASIS KOTA SABANG TAHUN 2013-2019

2020 ◽  
Vol 6 (1) ◽  
pp. 89-104
Author(s):  
Ferry Setiawan
Keyword(s):  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Quadrant Analysis ◽  
Location Quotient ◽  
Strong Growth ◽  
Aceh Province ◽  
Dynamic Location ◽  
Index Value ◽  
Regional Product

The success of a region in improving its economy can be measured by the growth of  Gross Domestic Regional Product (GDRP) from various existing sectors. This Gross Domestic Regional Product (GDRP) growth occurs if the region has a leading sector or a basic sector whose growth rate is relatively fast and has strong competitiveness and a non-basic sector that has the opportunity to become a basic sector if the local government is able to condition the opportunities that exist into an optimal result. This study uses secondary data obtained from the Central Statistics Agency (BPS) of Aceh Province in the form of time series data for 7 years, namely the 2013-2019 period. This research was conducted to identify the basic and non-basic sectors in the economic structure of the City of Sabang for the period 2013 - 2019 using the LQ (location quotient) analysis method, the Dynamic Location Quotient (DLQ) method, Shift Share Analysis, and quadrant analysis. 10 basic sectors with the highest average index value SLQ ≥ 1 and 7 sectors which are non-basic sectors with index numbers <1. In the quadrant analysis from the results of the existing Shift-Share calculations, there are 3 sectors in Quadrant I with fast and strong growth,3 sectors in Quadrant II with slow and strong growth, and 11 sectors in Quadrant III with fast growth but have weak competitiveness

Analysis of Revenue Inequality and Development of Leading Economic Sectors of District and City in Banten Province, Indonesia

2021 ◽  
Vol 2 (1) ◽  
pp. 24-33
Author(s):  
Bima Mulia ◽  
Mohamad Arief Setiawan ◽  
Kalfin Kalfin
Keyword(s):  
Economic Development ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Time Data ◽  
Economic Sectors ◽  
Location Quotient ◽  
Interregional Inequality ◽  
Dynamic Location ◽  
Underdeveloped Region

The imbalance of inter-regional economic development is a common phenomenon that occurs in the process of economic development of a region. This interregional inequality was originally caused by differences in natural resource content and differences in demographic conditions in each region. As a result of these differences, the ability of an area to increase economic growth and encourage the development process also becomes different. Therefore, it is not surprising that in every region there is usually a relatively developed region and a relatively underdeveloped region. This study aims to analyze how big the level of income inequality that occurs between regencies/cities in Banten Province. Identifying the base sector in each district/city in Banten Province, and predicting the base sector in the future in each Regency/City of Banten Province. Data used in this study is secondary data in the form of time series data to see Developments and changes that occur over a period of time. Data analysis used in this research is Location Quotient (LQ), Dynamic Location Quotient (DLQ), Williamson and Thiel Index. The results of this study are inequality that occurred in Banten is measured by using Williamson Index included in the category of Medium Inequality. On the measurement of Thiel Entropy Index, inequality in Lebak Regency is the lowest and Kota Cilegon has the highest imbalance in Banten Province.

scholarly journals KAJIAN BASIS DAN PRIORITAS DALAM SEKTOR PERTANIAN BAGI PEMBANGUNAN WILAYAH PESISIR BENGKULU

2014 ◽  
Vol 13 (1) ◽  
pp. 44-50
Author(s):  
Melli Suryanty ◽  
. Sriyoto
Keyword(s):  
Agricultural Sector ◽  
Time Series Data ◽  
Secondary Data ◽  
Development Planning ◽  
Series Data ◽  
Location Quotient ◽  
Agriculture Sector ◽  
Year 2000 ◽  
Agriculture Development ◽  
Share Value

The objectives of this research were to identify agriculture subsectors that can be the sector basis for the region development, and give information about priority scale of agriculture subsectors development in Bengkulu region development planning. This research used the secondary data gained from time series data from year 2000-2011. Analysis methods used in this research were sector contribution, location quotient, and shift share analysis. The results of the research showed that fishery subsector gave significant contribution for Bengkulu City PDRB. Fishery subsector became the basis and main priority of the agriculture development in year 2000-2011. This was shown from the biggest contribution value, location quotient value was greater than 1, and positive shift share value. The main priority of agriculture sector development is fishery, livestock, food plant, and estate subsector.    Keywords: Basic sector, agricultural sector, regional development.

scholarly journals ANALISIS PERTUMBUHAN DAN PERGESERAN SRUKTUR EKONOMI KABUPATEN INDUK DI PROVINSI BENGKULU

2020 ◽  
Vol 2 (1) ◽  
pp. 54-69
Author(s):  
Sunoto Sunoto ◽  
Bertha Iin Esti Indraswanti ◽  
Edy Rahmantyo Tarsilohadi
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Economic Development ◽  
Economic Performance ◽  
Time Series Data ◽  
Economic Structure ◽  
Series Data ◽  
Location Quotient ◽  
Dynamic Location ◽  
Secondary Time

The purpose of this research was to analyze economic growth and shifting of economic structure of the origin district in Bengkulu Province. Base on BPS secondary time series data (2001-2017), descriftive analysis was used to analyze economic growth and shifting economic structure, specialty after the region otonomous era (OTDA).  The DLQ and SSA method was used to determine the potential and leading sectors to increase economic performance. The result of this research was conclude that expansion of the the region in Bengkulu Provinsi has positif impact on economic development for the origin district. The economis structure was shifting from premier sector to secondary and tertier sector. The potential and leading sector after OTDA become more than before (from 4 or 5 sector to 7 untul 9 sector).  Keywords :  Dynamic Location Quotient 1, Shift Share Analysis 2, Economic Growth 3, Economic Structure 4, Potential and Leading Sector 5

scholarly journals IDENTIFICATION OF AGRICULTURAL SECTOR LEADING COMMODITIES IN MAGELANG DISTRICT

2020 ◽  
Vol 4 (2) ◽  
pp. 247-255
Author(s):  
Danta Paramartha ◽  
Mukson Mukson ◽  
Budi Adi Kristanto
Keyword(s):  
Agricultural Sector ◽  
Time Series Data ◽  
Secondary Data ◽  
Growth Patterns ◽  
Series Data ◽  
Agricultural Commodity ◽  
Sweet Potatoes ◽  
Location Quotient ◽  
Fast Growing ◽  
Central Java

Determination of leading commodities is needed to know the potential and prospective commodities that can be developed in an area. Leading commodities are expected to provide greater revenue compared to other commodities. This study aims to determine the leading agricultural subsector that has the potential to be developed as a driver of the economy in Magelang District. and analyze the trends in the growth patterns of subsector and leading agricultural commodities in the district. The method used in this study is descriptive method. The data used is time series data, namely secondary data from the GRDP of Magelang and Central Java Provinces in 2013-2017 and data on the amount of agricultural commodity production over a 7-year period (2011-2017). Data analysis tools used are Analysis of Location Quotient (LQ), Dynamic Location Quotient (DLQ), and Klassen Typology Analysis.The results of the study shows that, horticultural plants, livestock, forestry and natural resources are base / leading subsectors of agricultural sector in Magelang District. The pattern and structure of the growth of the food crop subsector is among those that are rapidly developing, while the horticulture and livestock are among the advanced but depressed subsectors and the most advanced and fast growing food crops are sweet potatoes. On the other hand, the fast-growing group of horticultural commodities of vegetables are cabbage, cayenne pepper, tomatoes, cauliflower, cucumber, scallion, and carrots, whereas horticultural commodities in advanced and fast-growing fruit groups are rambutan and salak. In addition, the rapidly growing livestock commodities are cows, buffaloes, pigs, native chickens, and ducks. Finally the advanced but depressed commodities are goats and broilers.

scholarly journals Evaluasi wilayah unggulan pengembangan kuda Sandelwood di Kabupaten Sumba Barat Daya Provinsi Nusa Tenggara Timur

2021 ◽  
Vol 19 (2) ◽  
pp. 149
Author(s):  
Melkianus Dedimus Same Randu ◽  
Ewaldus Wera
Keyword(s):  
Time Series ◽  
Population Growth ◽  
Quantitative Method ◽  
Local Community ◽  
Time Series Data ◽  
Series Data ◽  
Mapping Data ◽  
Location Quotient ◽  
Dynamic Location ◽  
Potential Area

<p class="MDPI17abstract"><strong>Objective: </strong>The Sandalwood Horse has economic, social, and cultural advantages to the local community in Southwest Sumba Regency. However, sandalwood horse development is experiencing obstacles due to the absence of base area mapping data. This research aims to identify the potential area for the development of the Sandalwood horse in Southwest Sumba Regency.</p><p class="MDPI17abstract"><strong>Methods: </strong>Descriptive quantitative method was used in this research. Time series data (2013-2018) was collected from related stakeholders in Southwest Sumba Regency. The Location Quotient (LQ), Dynamic Location Quotient (DLQ) and a combination of both LQ and DLQ analysis were applied to identify the potential area for the development of the Sandalwood horse. If the value of LQ and DLQ is more than 1, it means that the area/district could be recommended as a potential area for the development of the Sandalwood horse.<strong></strong></p><p class="MDPI17abstract"><strong>Results</strong><strong>: </strong>The result shows that of the 11 (eleven) districts in Southwest Sumba Regency, only 5 (five) districts (Wewewa Utara, Wewewa Barat, Wewewa Selatan, Wewewa Tengah, and Kodi Bangedo) could be recommended as the potential areas for development of sandalwood horses in the future, with an average LQ value ranging from 1.01 to 1.85 and DLQ ranging from 1.27 to 78.27.<strong></strong></p><strong>Conclusions: </strong>Southwest Sumba Regency has potential districts for the development of the Sandalwood horse. The sandalwood horse in the potential districts is a leading commodity that can fulfil the local needs of each sub-district and has a population growth above the average level in Southwest Sumba Regency.

scholarly journals Analisis Penentuan Sektor Unggulan Perekonomian di Kabupaten Kubu Raya

2015 ◽  
Vol 4 (2) ◽  
pp. 253 ◽  
Author(s):  
Hajeri Hajeri ◽  
Erlinda Yurisinthae ◽  
Eva Dolorosa
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Clean Water ◽  
Location Quotient ◽  
Processing Industry ◽  
Combined Analysis ◽  
Analysis Tools ◽  
Dynamic Location ◽  
Basic Price

This research intends to determine leading sectors in the Regency Kubu Raya. Leading sectorscan be determined by combining some analysis tools, such as: Typology Klassen, combinedLocation Quotient dan Dynamic Location Quotient,  Shift Share. Time series data is used in thisresearch, such as PDRB of Kubu Raya Regency and West Borneo Province from 2008 to 2013based on constant basic price. The result of this research showed that  leading sectors economy inKubu Raya Regency based on combined analysing from three analysis tools are transport andcommunications sector. Potential sector to be developed to become  leading sectors in the futureare processing industry, elictricity, gas, and clean water sector. Meanwhile, from the fiveagriculture sub sectors in Kubu Raya Regency based on combined analysis from the threeanalysis tools showed that livestock sub sector has potential to be developed to become a leadingsector economy in Kubu Raya Regency.

scholarly journals Analisis Struktur Ekonomi dan Sektor Unggulan Kabupaten Aceh Besar

2019 ◽  
Vol 2 (1) ◽  
pp. 39-48
Author(s):  
Irwan Safwadi ◽  
Marah Sutan Rangkuti
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Secondary Data ◽  
Economic Structure ◽  
Series Data ◽  
Economic Sectors ◽  
Resource Potential ◽  
Structure Changes ◽  
Aceh Province

Development policy through the optimization of local resource potential is a need that needs to be prepared in order to encourage the acceleration of regional economic growth. Identify changes in economic structure and determine the leading economic sectors including one of the efforts to accelerate the process of achieving economic growth. This study aims to analyze changes in economic structure and determine the leading economic sectors in Aceh Besar District. The data used is secondary data in the form of time series data (time series) Gross Regional Domestic Product (GRDP) of Aceh Besar Regency based on constant prices and GRDP of Aceh Province based on the constant price of 2012-2016. The analyzer used is Shift-Share. During the last five years, Aceh Besar's economic structure based on Shift-Share was only donated by Aceh Province by 19.60 percent. Furthermore, the industry mix contributed 17.89 percent. The leading economic sectors accounted for 62.50 percent of Aceh Besar economic structure changes. The result of Shift Share analysis shows that most of Aceh Besar Regency's economic sector is one of the leading sectors that grow fast in economy in Aceh Province. Only the electricity and gas procurement sector does not excel in Aceh Besar.

ANALISA PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN METODE ARIMA

2020 ◽  
Vol 2 (2) ◽  
pp. 454
Author(s):  
Julkifli Purnama ◽  
Ahmad Juliana
Keyword(s):  
Capital Market ◽  
Stock Price ◽  
Time Series Data ◽  
Arima Model ◽  
Secondary Data ◽  
Actual Data ◽  
Series Data ◽  
Analysis Technique ◽  
The Right ◽  
The Capital Market

Investment in the capital market every manager needs to analyze to make decisions so that the right target to produce profits in accordance with what is expected. For that, we need a way to predict the decisions that will be taken in the future. The research objective is to find the best model and forecasting of the composite stock price index (CSPI). Data analysis technique The ARIMA Model time series data from historical data is the basis for forecasting. Secondary data is the closing price of the JCI on July 16 2018 to July 16 2019 to see how accurate the forecasting is done on the actual data at that time. The results of the study that the best Arima model is Arima 2.1.2 with an R-squared value of 0.014500, Schwarz criterion 10.83497 and Akaike info criterion of 10.77973. Results of forecasting actual data are 6394,609, dynamic forecast 6387,551 selisish -7,05799, statistics forecas 6400,653 difference of 6,043909. For investors or the public can use the ARIMA method to be able to predict or predict the capital market that will occur in the next period.

scholarly journals PENGARUH KONSUMSI ENERGI DAN REZIM TERHADAP PERTUMBUHAN EKONOMI DI INDONESIA

2019 ◽  
Vol 1 (2) ◽  
pp. 401
Author(s):  
Zakiah Husna ◽  
Idris Idris
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Renewable Energy Consumption ◽  
Energy Regime ◽  
Negative Effect ◽  
Positive Effect

This study aims to determine the effect of energy consumption and regime on economic growth in Indonesia. The data used is secondary data in the form of time series data from 1988-2017, with documentation and library study data collection techniques obtained from relevant institutions and agencies. the variables used are economic growth (GDP), non-renewable energy consumption, renewable energy consumption and regime, the research methods used are: (1) Multiple Regression Analysis (OLS), (2) Classical Assumption Test results of research stating that: ( 1) non-renewable energy consumption has a positive effect on economic growth in Indonesia. (2) consumption of renewable energy has a positive effect on economic growth in Indonesia. (3) the energy regime has a negative effect on economic growth in Indonesia. (4) non-renewable energy consumption, renewable energy consumption and energy regime have a significant effect on economic growth in Indonesia. so only the energy regime has a negative effect on economic growth in Indonesia.

scholarly journals ANALISIS FAKTOR PENENTU INDEKS HARGA SAHAM GABUNGAN DI INDONESIA

2019 ◽  
Vol 1 (4) ◽  
pp. 37
Author(s):  
Yulizar Fikri ◽  
Ali Anis
Keyword(s):  
Economic Growth ◽  
Foreign Exchange ◽  
Stock Price ◽  
Price Index ◽  
Time Series Data ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Foreign Exchange Reserves ◽  
Stock Price Index

This study aims to determine the analysis of the determinants of the composite stock price index in Indonesia. The independent variables in this study are inflation as X1, foreign exchange reserves as X2, exchange rates as X3, and economic growth as X4, and the dependent variable of the composite stock price index as Y. The data used are secondary data in the formof time series data from 2010Q1 until 2019Q2, with data collection techniques, namely documentation from Bank Indonesia publications, the Central Statistics Agency, investing. comsite and library research. The research methods used are: (1) Multiple Linear Regression, (2) Classical Assumption Test (3) coefficient of determination. The results of this study indicate that:(1) inflation does not significantly influence the composite stock price index. (2) foreign exchange reserves have a significant positive effect on the composite stock price index. (3) the rupiah exchange rate has an influence on the composite stock price index and (4) economic growth hasno significant effect on the composite stock price index.

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