scholarly journals Effect of Changes Composition and Intensity of Green Space on Surface Temperature: Case Study in Pekalongan Regency, Indonesia

2021 ◽  
Vol 887 (1) ◽  
pp. 012013
Author(s):  
A. Pradana ◽  
A. Pugara ◽  
D. A. Puspasari
Keyword(s):  
Surface Temperature ◽  
Spatial Planning ◽  
Green Space ◽  
Time Series Data ◽  
Development Planning ◽  
Series Data ◽  
Central Java ◽  
Spatial Use ◽  
The Stability

Abstract The spatial planning document is planning guidance intended to regulate an area’s spatial use and development planning. This document contains the component that regulates the composition of green space. This composition is designed to maintain the stability of the existing ecosystem quality. Pekalongan is one of the Regency in Central Java Province with environmental problems related to lack of green space area. The existence of ecological degradation makes environmental quality in Pekalongan one that needs to be considered. This study aims to determine the effect of changes in the composition and intensity of green space on surface temperature from these problems. This study will use time-series data during the initial implementation of spatial planning documents (2013) to the current year (2021) to see how changes in the composition and intensity of green space in each sub-district in Pekalongan Regency. The method used is descriptive quantitative with a GIS approach. The result of this study can be a consideration to make policies related to green space.

scholarly journals Research on Tourism Network Index Model Based on Baidu Index --- A Case Study of Sanya

2018 ◽  
Vol 228 ◽  
pp. 05017
Author(s):  
Caixia Chen ◽  
Chun Shi ◽  
Jue Chen
Keyword(s):  
Time Series Data ◽  
Principal Component ◽  
Series Data ◽  
Analysis Method ◽  
Index Model ◽  
Network Search ◽  
Weighted Analysis ◽  
Development Level ◽  
The Stability

Tourism index is a "barometer" to reflect the overall development level of tourism. The tourism index compiled by historical data can not reflect the real situation accurately with the increasing influence of network events on tourism In the Internet era. This study collects time series data of tourism network search by Baidu index tool and uses data mining method and principal component analysis method to detect and standardize the stability of the data. The spss system and the weighted analysis method are used to construct the tourism network index model. Finally, the model detection is carried out by comparing the actual tourism data in Sanya. This study is an important supplement to the existing tourism index.

scholarly journals Design of an Error Estimation Algorithm for Time Series Data Prediction in Attitude Controlled Systems

2021 ◽  
Vol 13 (3) ◽  
pp. 141-148
Author(s):  
M. RAJA ◽  
Kokila VASUDEVAN ◽  
Kartikay SINGH ◽  
Aishwerya SINGH ◽  
Ayush GUPTA
Keyword(s):  
Error Estimation ◽  
Time Series Data ◽  
Estimation Algorithm ◽  
Series Data ◽  
Controlled Systems ◽  
Data Prediction ◽  
Regression Techniques ◽  
Linear Plot ◽  
The Stability

This research presents an error estimation approach with the combination of traditional multilevel techniques used to minimize errors for an accurate prediction and to investigate the behavior of such an algorithm for a satellite. The traditional techniques mentioned above are a combination derived from multiple regression techniques and perform a case study for data analysis. A linear plot can easily be predicted, however if a system tends to deviate toward non-linearity the overall result derived from such an algorithm can be non-reliable since each value would depict a completely different output at different levels. The stability of the fixed regression derived is used to determine the accuracy of the system.

Producers' Response to Changes in Prices and Marketing Policies: A Case Study of Sugarcane and Paddy in Eastern U.P. by S. C. Gupta and A. Majid. New York: Asia Publishing House, 1965.

1968 ◽  
Vol 8 (2) ◽  
pp. 308-309
Author(s):  
Mohammad Irshad Khan
Keyword(s):  
New York ◽  
Time Series ◽  
Time Series Data ◽  
Publishing House ◽  
Economic Incentives ◽  
The Other ◽  
Series Data ◽  
Poor Countries ◽  
Northern India

It is alleged that the agricultural output in poor countries responds very little to movements in prices and costs because of subsistence-oriented produc¬tion and self-produced inputs. The work of Gupta and Majid is concerned with the empirical verification of the responsiveness of farmers to prices and marketing policies in a backward region. The authors' analysis of the respon¬siveness of farmers to economic incentives is based on two sets of data (concern¬ing sugarcane, cash crop, and paddy, subsistence crop) collected from the district of Deoria in Eastern U.P. (Utter Pradesh) a chronically foodgrain deficit region in northern India. In one set, they have aggregate time-series data at district level and, in the other, they have obtained data from a survey of five villages selected from 170 villages around Padrauna town in Deoria.

A new approach to detect extreme events: a case study using remotely-sensed precipitation time-series data

2021 ◽  
Vol 24 ◽  
pp. 100618
Author(s):  
Philipe Riskalla Leal ◽  
Ricardo José de Paula Souza e Guimarães ◽  
Fábio Dall Cortivo ◽  
Rayana Santos Araújo Palharini ◽  
Milton Kampel
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Time Series Data ◽  
Remotely Sensed ◽  
Series Data ◽  
Precipitation Time Series ◽  
New Approach

CAUSAL RELATIONSHIP OF ENERGY CONSUMPTION AND ECONOMIC GROWTH – A CASE STUDY OF PAKISTAN

2021 ◽  
Vol 9 (1) ◽  
pp. 139-164
Author(s):  
Saddam Hussain ◽  
Chunjiao Yu
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Energy Consumption ◽  
Causal Relationship ◽  
Inflation Rate ◽  
Time Series Data ◽  
Consumer Price Index ◽  
Series Data ◽  
Relationship Of

This paper explores the causal relationship between energy consumption and economic growth in Pakistan, applying techniques of co-integration and Hsiao’s version of Granger causality, using time series data over the period 1965-2019. Time series data of macroeconomic determi-nants – i.e. energy growth, Foreign Direct Investment (FDI) growth and population growth shows a positive correlation with economic growth while there is no correlation founded be-tween economic growth and inflation rate or Consumer Price Index (CPI). The general conclu-sion of empirical results is that economic growth causes energy consumption.

scholarly journals Daya Tahan Sektor Rumah Tangga Dalam Rangka Menjaga Stabilitas Sistem Keuangan

2018 ◽  
Vol 5 (1) ◽  
pp. 65
Author(s):  
Ita Rakhmawati ◽  
Suhadi Suhadi
Keyword(s):  
Interest Rates ◽  
Time Series Data ◽  
Negative Impact ◽  
Financial System ◽  
Series Data ◽  
Price Stability ◽  
Economic Stability ◽  
Independent Variables ◽  
High Inflation ◽  
The Stability

The crisis in 1997 is the image of the high rise in inflation in Indonesia. The phenomenon of inflation when it reached 82.40% (Anas, 2006). The early mid-1998 also experienced a weakening of the rupiah against the dollar. Condition stable economy is the desire of each country in comparison with the state of the economy has always fluctuated. Economic stability will create an atmosphere conducive economy. stable climatic conditions in the expected level of welfare is the purpose in each country. One of the efforts to maintain economic stability is through monetary policy. For example, with economic growth, maintain price stability (inflation), the achievement of the balance of payments and the reduction of unemployment (Natsir, 2008). The stability of the financial system of a country of which reflected their price stability, in the sense that there are a great price that can be harmful to society, both consumers and manufacturers that will damage the joints of the economy. However, the implementation of the policy, Bank Indonesia as the monetary authority uses monetary variables such as interest rates and the money supply to cope with economic shocks such as inflation. Besides the need for the government’s role in maintaining the rupiah to avoid turmoil in the economy. The importance of inflation control based on the consideration that the high inflation and unstable negative impact on socio-economic conditions of society. Among the high inflation will cause a decline in the real income of the community so that the standard of living of the people down and eventually make everyone, especially the poor get poorer. From one of the effects of inflation are so wide will impact people’s demands to meet the needs of more and more difficult. Their continuousprice increases being offset by rising income of the communities, it can make sure the Indonesian state would worsen. As a result many people’s needs can not be met, so many things that must be met by way of credit. The number of community needs that must be met will cause world of opportunities for banks to offer credit readily available to meet the needs. The third object of research above (inflation, poverty, and credit) does affect the stability of the financial system? In this study using secondary data from the Badan Pusat Statistik (BPS) and Bank Indonesia (BI) with time series data from the years 2007-2015. The process of data analysis was performed using OLS regression with Eviews 8.0. Based on research, if only partial test of the poverty variable significantly affect the stability of the financial system amounted to 2,023 with α = 10%. Meanwhile, two other variables (inflation and poverty) is not significant to the stability of the financial systemMeanwhile, two other variables (inflation and poverty) is not significant to the stability of the financial system. While the value of R-Square (0.629900), indicating that the three independent variables / free consisting of inflation, poverty and credit simultaneously have the effect that make the stabilization of the financial system increases or decreases. That is jointly independent variables (inflation, poverty and loans) contributed / effect of 62.9% against the stability of the financial system. The rest is the influence of other factors beyond the three independent variables studied.

scholarly journals ANALISIS KORELASI CURAH HUJAN DAN SUHU PERMUKAAN LAUT WILAYAH INDONESIA, SERTA IMPLIKASINYA UNTUK PRAKIRAAN CURAH HUJAN (STUDI KASUS KABUPATEN CILACAP) (CORRELATION ANALYSIS OF RAINFALL AND INDONESIA SEA SURFACE TEMPERATURE, AND ITS ...

Agromet ◽  
2007 ◽  
Vol 21 (2) ◽  
pp. 46 ◽  
Author(s):  
W. Estiningtyas ◽  
F. Ramadhani ◽  
E. Aldrian
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Negative Correlation ◽  
Prediction Models ◽  
Time Series Data ◽  
Sea Surface ◽  
Rainfall Pattern ◽  
Series Data ◽  
Rainfall Prediction

<p>Significant decrease in rainfall caused extreme climate has significant impact on agriculture sector, especialy food crops production. It is one of reason and push developing of rainfall prediction models as anticipate from extreme climate events. Rainfall prediction models develop base on time series data, and then it has been included anomaly aspect, like rainfall prediction model with Kalman filtering method. One of global parameter that has been used as climate anomaly indicator is sea surface temperature. Some of research indicate, there are relationship between sea surface temperature and rainfall. Relationship between Indonesian rainfall and global sea surface temperature has been known, but its relationship with Indonesian’s sea surface temperature not know yet, especialy for rainfall in smaller area like district. So, therefore the research about relationship between rainfall in distric area and Indonesian’s sea surface temperature and it application for rainfall prediction is needed. Based on Indonesian’s sea surface temperature time series data Januari 1982 until Mei 2006 show there are zona of Indonesian’s sea surface temperature (with temperature more than 27,6 0C) dominan in Januari-Mei and moved with specific pattern. Highest value of spasial correlation beetwen Cilacap’s rainfall and Indonesian’s sea surface temperature is 0,30 until 0,50 with different zona of Indonesian’s sea surface temperature. Highest positive correlation happened in March and July. Negative correlation is -0,30 until -0,70 with highest negative correlation in May and June. Model validation resulted correlation coeffcient 85,73%, fits model 20,74%, r2 73,49%, RMSE 20,5% and standart deviation 37,96. Rainfall prediction Januari-Desember 2007 period indicated rainfall pattern is near same with average rainfall pattern, rainfall less than 100/month. The result of this research indicate Indonesian’s sea surface temperature can be used as indicator rainfall condition in distric area, that means rainfall in district area can be predicted based on Indonesian’s sea surface temperature in zona with highest correlation in every month.</p><p>------------------------------------------------------------------</p><p>Penurunan curah hujan yang cukup signifikan akibat iklim ekstrim telah membawa dampak yang cukup signifikan pula pada sektor pertanian, terutama produksi tanaman pangan. Hal ini menjadi salah satu alasan yang mendorong semakin berkembangnya model-model prakiraan hujan sebagai upaya antipasi terhadap kejadian iklim ekstrim. Model prakiraan hujan yang pada awalnya hanya berbasis pada data time series, kini telah berkembang dengan memperhitungkan aspek anomali iklim, seperti model prakiraan hujan dengan metode filter Kalman. Salah satu indikator global yang dapat digunakan sebagai indikator anomali iklim adalah suhu permukaan laut. Dari berbagai hasil penelitian diketahui bahwa suhu permukaan laut ini memiliki keterkaitan dengan kejadian curah hujan. Hubungan curah hujan Indonesia dengan suhu permukaan laut global sudah banyak diketahui, tetapi keterkaitannya dengan suhu permukaan laut wilayah Indonesia belum banyak mendapat perhatian, terutama untuk curah hujan pada cakupan yang lebih sempit seperti kabupaten. Oleh karena itu perlu dilakukan penelitian yang mengkaji hubungan kedua parameter tersebut serta mengaplikasikannya untuk prakiraan curah hujan pada wilayah Kabupaten. Hasil penelitian berdasarkan data suhu permukaan laut wilayah Indonesia rata-rata Januari 1982 hingga Mei 2006 menunjukkan zona dengan suhu lebih dari 27,6 0C yang dominan pada bulan Januari-Mei dan bergerak dengan pola yang cukup jelas. Korelasi spasial antara curah hujan kabupaten Cilacap dengan SPL wilayah Indonesia rata-rata bulan Januari-Desember menunjukkan korelasi positip tertinggi antara 0,30 hingga 0,50 dengan zona SPL yang beragam. Korelasi tertinggi terjadi pada bulan Maret dan Juli. Sedangkan korelasi negatip berkisar antara -0,30 hingga -0,70 dengan korelasi negatip tertinggi pada bulan Mei dan Juni. Validasi model prakiraan hujan menghasilkan nilai koefisien korelasi 85,73%, fits model 20,74%, r2 sebesar 73,49%, RMSE 20,5% dan standar deviasi 37,96. Hasil prakiraan hujan bulanan periode Januari-Desember 2007 mengindikasikan pola curah hujan yang tidak jauh berbeda dengan rata-rata selama 19 tahun (1988-2006) dengan jeluk hujan kurang dari 100 mm/bulan. Hasil penelitian mengindikasikan bahwa SPL wilayah Indonesia dapat digunakan sebagai indikator untuk menunjukkan kondisi curah hujan di suatu wilayah (kabupaten), artinya curah hujan dapat diprediksi berdasarkan perubahan SPL pada zona-zona dengan korelasi yang tertinggi pada setiap bulannya.</p>

scholarly journals Analisis Peningkatan Upah Minimum Terhadap Penyerapan Tenaga Kerja di Provinsi Jawa Tengah

2021 ◽  
Vol 10 (3) ◽  
pp. 134-143
Author(s):  
Annisa Yulianti ◽  
Hadi Sasana
Keyword(s):  
Economic Growth ◽  
Minimum Wage ◽  
Time Series Data ◽  
Series Data ◽  
Short Term ◽  
Central Java ◽  
Meaningful Relationship ◽  
Short Time ◽  
Relationship Of

 This study aims to analyze the short-term and long-term relationship of increasing the minimum wage in Central Java on employment. The research method used is ECM. The variables of this study include labor, minimum wages, PMDN, and economic growth. The data used are time-series data from 1990-2020. The results show that the minimum wage has a positive and significant relationship to the employment in the long term but not significantly in the short time. PMDN has a negative but significant correlation in the short and long term. At the same time, the variable economic growth has a positive but not meaningful relationship to employment absorption in the long and short term.

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