scholarly journals Pengaruh Inflasi dan Pengangguran terhadap Penduduk Miskin di Sumatera Utara Tahun 2006–2020

2021 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Intan Permata Sari Sembiring ◽  
Surtama Simanjuntak ◽  
Vini Alvionita Sitepu
Keyword(s):  
Time Series

Penduduk Miskin adalah penduduk yang memiliki rata-rata pengeluaran perkapita perbulan dibawah garis kemiskinan. Masalah kemiskinan merupakan masalah yang kompleks dan multidimensi yang meliputi berbagai aspek dalam lini kehidupan manusia, tak terkecuali bagi pemerintah daerah di Sumatera Utara. Usaha untuk mengentaskan kemiskinan harus memperhatikan akar permasalahan kemiskinan itu sendiri. Indicator yang dipakai dalam penelitian imi adalah inflasi, pengangguran dan jumlah penduduk miskin. Penelitian ini bertujuan untuk menganalisis seberapa besar pengaruh Inflasi dan pengangguran terhadap penduduk miskin di Sumatera Utara periode 2006sampai dengan 2020 baik secara simultan maupun secara parsial. Jenis data yang digunakan dalam penelitian ini adalah data sekunder  time series dari tahun 2006 sampai dengan 2020. Data yang digunakan yang digunakan ialah data yang diperoleh dari website resmi Badan Pusat Statistik (BPS) Sumatera Utara. Metode analisis yang digunakan dalam penelitian ini adalah analisis regresi linier berganda dengan software statistika SPSS. Hasil penelitian menunjukkan bahwa variabel inflasi berpengaruh positif dan tidak signifikan terhadap penduduk miskin di Provinsi Sumatera Utara dengan perolehan nilai sig 0.510 > 0,05; Secara parsial variabel pengangguran berpengaruh  positif dan signifikan terhadap penduduk miskin di Provinsi Sumatera Utara dengan perolehan sig 0,000 < 0,05; secara simultan variabel inflasi dan pengangguran berpengaruh signifikan terhadap penduduk miskin di Sumatera Utara pada tahun 2006- 2020.

The LDE-Type Flare Occurrence (1969-1993)

1994 ◽  
Vol 144 ◽  
pp. 279-282
Author(s):  
A. Antalová
Keyword(s):  
Time Series ◽  
Fourier Analysis ◽  
Sunspot Cycle ◽  
List Type ◽  
Type Number ◽  
Solar Cycles ◽  
Type Iv ◽  
Long Duration ◽  
Cycle Maximum ◽  
Flare Index

AbstractThe occurrence of LDE-type flares in the last three cycles has been investigated. The Fourier analysis spectrum was calculated for the time series of the LDE-type flare occurrence during the 20-th, the 21-st and the rising part of the 22-nd cycle. LDE-type flares (Long Duration Events in SXR) are associated with the interplanetary protons (SEP and STIP as well), energized coronal archs and radio type IV emission. Generally, in all the cycles considered, LDE-type flares mainly originated during a 6-year interval of the respective cycle (2 years before and 4 years after the sunspot cycle maximum). The following significant periodicities were found:• in the 20-th cycle: 1.4, 2.1, 2.9, 4.0, 10.7 and 54.2 of month,• in the 21-st cycle: 1.2, 1.6, 2.8, 4.9, 7.8 and 44.5 of month,• in the 22-nd cycle, till March 1992: 1.4, 1.8, 2.4, 7.2, 8.7, 11.8 and 29.1 of month,• in all interval (1969-1992):a)the longer periodicities: 232.1, 121.1 (the dominant at 10.1 of year), 80.7, 61.9 and 25.6 of month,b)the shorter periodicities: 4.7, 5.0, 6.8, 7.9, 9.1, 15.8 and 20.4 of month.Fourier analysis of the LDE-type flare index (FI) yields significant peaks at 2.3 - 2.9 months and 4.2 - 4.9 months. These short periodicities correspond remarkably in the all three last solar cycles. The larger periodicities are different in respective cycles.

Automatic Identification of Autoregressive Integrated Moving Average Time Series

1982 ◽  
Vol 14 (3) ◽  
pp. 156-166 ◽  
Author(s):  
Chin-Sheng Alan Kang ◽  
David D. Bedworth ◽  
Dwayne A. Rollier
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Automatic Identification ◽  
Autoregressive Integrated Moving Average

Smoothing Facilitates the Detection of Coupled Responses in Psychophysiological Time Series

2000 ◽  
Vol 14 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Joni Kettunen ◽  
Niklas Ravaja ◽  
Liisa Keltikangas-Järvinen
Keyword(s):  
Time Series ◽  
Type I Error ◽  
Electrodermal Activity ◽  
Moving Average ◽  
Type I ◽  
Facial Electromyography ◽  
Response Characteristics ◽  
Smoothing Methods ◽  
Response Systems ◽  
Different Response

Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.

Sign in / Sign up

Export Citation Format

Share Document