Consumer Price Index (CPI) are the indicators used to measure the inflation and deflation of a group of goods and services in general. Forecasting CPI to be important as early detection in facing price hikes. This study uses the SSA and SARIMA. SARIMA a parametric model that requires various assumptions while SSA is a nonparametric technique that is free from a variety of assumptions, but both methods require seasonal patterns in the data. Based on the research results, methods of SSA with length window(L) of 24 and a grouping of 4 (1 group of seasonal and 3 groups of trends) and SARIMA models of order (0,1,1), (0,1,1) 6 is the most accurate and reliable models in forecasting CPI to the value Padang Sidempuan City. Forecasting CPI Padang Sidempuan City for the next 5 months with SSA method and SARIMA (0,1,1), (0,1,1) 6 shows the pattern of a trend is likely to increase but forecasting the 5th month with SSA method showed a surge in the value of CPI high or high inflation will occur.
This article evaluates the effect of digitalization and credit access in boosting regional growth performance across 38 districts in East Java over the 2010-2021 period. Using google trend analysis, we capture the pattern and spatial distribution of main explanatory variables, which are digitalization and credit access to support our empirical findings. Results show that overall the google trends’ portraits indicate adequate similarities in credit access, which declare the negative yet significant effect to growth. We also find interesting findings to be highlighted for internet access. Both google trends and empirical data show negative correlation between digitalization and credit access. From the standpoint of spatial spills-over effect, there is significant and positive spatial autocorrelation in internet access across districts in Indonesia. Applying spatial econometric model, two key factors appear to boost economic growth in the recovery period, which are digitalization and education-related variable. This article concludes that digitalization can not work itself. The inclusion of spills-over effect and spatial dependence across districts is needed to accelerate regional growth. Thus, from policy perspectives, our findings suggest that spatial-based policies by combining digitalization with human capital are more appropriate to boost growth performance in East Java.
Produktivitas tenaga kerja merupakan salah satu agenda prioritas pemerintah dalam upaya meningkatkan daya saing nasional, khususnya di masa pandemi Covid-19 yang telah berefek ke berbagai aktivitas ekonomi di berbagai sektor. Penelitian ini bertujuan untuk mengidentifikasi produktivitas tenaga kerja beradasrkan sektor pertanian dan industri pengolahan di Sumatera Utara periode sebelum dan saat pandemi Covid-19 dan menganalisis faktor-faktor yang memengaruhinya. Faktor penentunya diantaranya adalah dimensi kesehatan dengan proksi Angka Harapan Hidup (AHH), dimensi Pendidikan dengan proksi Rata-rata Lama Sekolah (RLS), pembangunan fisik dengan proksi Pembentukan Modal Tetap Bruto (PMTB), dan Upah Minimum Kabupaten/Kota (UMK). Hasil identifikasi menunjukkan bahwa produktivitas tenaga kerja sektor pertanian tertinggi berada di Kota Sibolga dan produktivitas tenaga kerja sektor industri pengolahan berada di Kabupaten Labuhan Batu Selatan. Berdasarkan hasil analisis regresi multivariat, RLS dan UMK memiliki pengaruh positif dan signifikan terhadap produktivitas tenaga kerja di sektor pertanian sedangkan variabel dummy kondisi pandemik berpengaruh negatif dan signifikan. Sementara itu, PMTB dan AHH tidak signifikan secara statistik pengaruhnya terhadap produktivitas tenaga kerja di sektor pertanian. RLS, PMTB, dan UMK berpengaruh positif terhadap produktivitas tenaga kerja di sektor industri pengolahan sedangkan variabel dummy kondisi pandemi berpengaruh negatif dan signifikan. Sementara itu, AHH tidak signifikan secara statistik pengaruhnya terhadap produktivitas tenaga kerja di sektor industri pengolahan di Sumatera Utara. Berdasarkan nilai eta square lambda sebesar 0,756 menunjukkan bahwa keragaman model dapat dijelaskan oleh variabel RLS, AHH, PMTB, UMK, dan variabel dummy kondisi pandemi sebesar 75,6 persen dan sisanya sebesar 24,4 persen dijelaskan oleh variabel lain di luar model.
Entrepreneurial activity is considered as one of the solutions in reducing the unemployment rate because it can absorb labor and encourage national economic development. Several Asian countries have experienced economic changes over the last three decades which were marked by an increase in the number of business activities and business output with the direction of achievement in line with the pace of economic growth. Meanwhile, novice business actors at the national level are still relatively low. Based on this, it is interesting to explore the segmentation of potential entrepreneurs and startups and the aspects that influence it by utilizing GEM data. The results showed that with the Chi-Squared Automatic Interaction Detection (CHAID) method, people living on the island of Java with an age range of 35-44 years with the status of working at home, or working full time or part time, are likely to become potential entrepreneurs around 59.7%. The results of the logistic regression show that internal factors (career choice, business skills and knowledge, and fear of failure in entrepreneurship), and external factors (people around who are also entrepreneurs, the first opportunity to start a business, media showing business success stories, and respectable social status of business people) affects the increase in potential entrepreneurs.
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