Judul: Modelling indonesia’s regional inflation using static and dynamic panel data regression
Abstrak: Inflasi merupakan masalah ekonomi yang dialami setiap negara. Inflasi yang tidak terkendali dapat berdampak buruk bagi perekonomian dan mengganggu stabilitas nasional. Inflasi nasional ditentukan oleh inflasi daerah. Inflasi regional di Indonesia besarnya bervariasi karena perbedaan karakteristik daerah dan adanya kebijakan otonomi daerah. Penelitian ini menduga model tingkat inflasi di 31 provinsi di Indonesia periode 2006-2012 dengan menggunakan regresi data panel statis dan dinamis. Nilai RMSE, MAE dan MAPE menunjukan angka yang lebih kecil pada dugaan model regresi data panel dinamis menggunakan prosedur SYS-GMM daripada dugaan model regresi data panel statis menggunakan model efek tetap. Model yang memasukkan peubah tingkat inflasi tahun sebelumnya sebagai peubah bebas lebih baik dari sisi kesalahan pendugaan dibandingkan model yang tidak menggunakan peubah tingkat inflasi tahun sebelumnya. Peubah yang mempengaruhi tingkat inflasi secara signifikan adalah upah minimum provinsi riil, konsumsi energi listrik dan tingkat inflasi tahun sebelumnya., Inflation is an economic problem that is experienced by every country. Uncontrolled inflation rate causes bad impact in national stability. National inflation rate depends on regional inflation rates. Regional inflation rate in Indonesia varies due to differences in the characteristics of the area, the differences in economic structure and the policy of regional authonomy. This study estimates regional inflation rate model using yearly data in 2006 until 2012 from 31 provinces in Indonesia and uses static and dynamic panel data regression. RMSE, MAE and MAPE of dynamic panel data regression using SYS-GMM procedure have smaller value than static panel data regression using fixed effect model. It means that estimation model which includes the previous year’s inflation rate variable as independent variable is better than estimation model which doesn’t use it. The significant variables that affect inflation rate are regional minimum wages, consumption of electricity and previous year’s inflation rate. Keywords: regional inflation, dynamic panel data regression, static panel data regression
Keyword: inflasi regional, regresi data panel dinamis, regresi data panel statis

Judul: Analisis Dinamika Inflasi di Indonesia: Pendekatan Sisi Penawaran
Abstrak: Stability of inflation becomes a main target of every country, including Indonesia. A shock on demand and supply may lead to fluctuation of inflation. Many economists have stated that cost push inflation is the main problem of inflation in developing country. This shock on supply will affect the price level in provinces of Indonesia. A static panel data with cross section data of 33 provinces and time series data of 2008-2012 is used in this research in order to analyze the relation between cost push inflation and regional inflation in Indonesia. The result of this research shows a positive and significant relation between cost push inflation variable and regional inflation in Indonesia, except the main goods price. The cost push inflation variable which has the bigest influence towards regional inflation compared to another variable is the administered price Variabel. Dynamics of inflation has a strong relation with cost of living. The result of this research also shows that provinces with high cost of living are not always followed by the rise of a high cost of living, for example in Jakarta and Papua Province.
Keyword: The rise of high cost of living, Static Data Panel, Dynamics Inflation, Cost of Living, Cost Push Inflation

Judul: Sintesis Flavonol melalui 2’-Hidroksikalkon
Abstrak: Flavonol is a class of flavonoids commonly found in fruits and vegetables. Flavonol is very useful, especially in food sector and health. In this study, flavonol unsubstituted was successfully synthesized from an intermediate material 2’-hydroxychalcone. The 2’-hydroxychalcone was synthesized by Claisen-Schmidt condensation method between o-hydroxyacetophenone and benzaldehyde using 4 different catalysts, namely KOH 60%, solid pellet of KOH-grinding technique, BF3-Et2O, and NaH in DMF. The KOH 60% was the best catalyst, giving the highest yield (57%). Afterward, the flavonol was synthesized in 1-stage oxidation cyclization of o-hydroxyacetophenone using Algar-Flynn-Oyamada (AFO) reaction, giving 76%. The flavonol total yield from 2’-hydroxychalcone was 43%. All synthesized products were characterized by their melting points and their spectra. The success of the synthesis flavonol opens the way to synthesis of useful flavonol derivatives such as quercetin and kaempferol
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