Judul: Pendekatan Regresi Spasial dalam Pemodelan Tingkat Pengangguran Terbuka
Abstrak: Solution of unemployment rate becomes one of the focuses of Indonesia development. The highest open unemployment rate is in Java. So it is interesting to study about factors that influence open unemployment rate in Java. The connection between area (spatial effect) are need to be considered. In this case, there is a spatial effect that can be solve with regression of area approach. Spatial regression with area approach are Spatial Autoregressive Model (SAR), Spatial Error Model (SEM), and General Spatial Model (GSM). The model selection criteria are the coefficient of determination (R2), value of variance estimate and the value of AIC (Akaike’s Information Criterion). The results show that GSM and SAR is better regression model than OLS and SEM and the factors that affect open unemployment rate are the percentage of people who did not complete primary school (SD), the gross regional domestic product constant prices for regency/city, percentage of people working in agriculture and minimum salary for regency/city.
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Judul: Model regresi spasial untuk deteksi faktor-faktor kemiskinan di Provinsi Jawa Timur
Abstrak: Poverty is one of the biggest problems in Indonesia. An approach to overcome this problem is to determine the factors that affect poverty usually using ordinary least square regression model (OLS). However, poverty is not only influenced by explanatory variables but also by various aspects related to surrounding locations. Therefore, this research employed spatial regression models, i.e. Spatial Autoregressive Models (SAR), Spatial Error Models (SEM), and Spatial General Models (SGM). Contiguity matrix is as spatial weighting matrix. The model selection criteria are the coefficient of determination (R2), slope regression of dependent variable to its estimator and the value of RMSE (Root Mean Square Error). The results show that SAR is better regression model than OLS and the factors that affect poverty are the percentage of people who did not complete primary school (SD), the percentage of people who drink another kind of water instead of drinking water, and the percentage of people who live in unhealthy houses with floor area at least 8 m2 per capita.
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Judul: Sintesis 7-Hidroksiflavonol dan Fisetin
Abstrak: Fisetin (7,3’,4’-trihydroxyflavonol) is commonly found in fruits and vegetables. It is potential as antioxidant, anti-inflammation, and antidiabetic. In this study, fisetin was synthesized by following 7-hydroxyflavonol synthesis method. 7-Hydroxyflavonol was succesfully synthesized from resacetophenone and benzaldehyde. Both starting materials were protected by tetrahydropyranyl (THP) group and then condensed with 60% KOH as catalyst forming THP-protected chalcone. Cyclization of the chalcone into THP-protected 7-hydroxyflavonol was carried out by using Algar-Flynn-Oyamada oxidative cyclization. Deprotection of the THP protecting group with p-toluenesulfonic acid resulted 7-hydroxyflavonol. The overall yield was 22% with total synthesis time of 7 days, faster than isolation from natural products. However, development of this method to synthesize fisetin from resacetophenone and 3,4-dihydroxybenzaldehyde as starting materials only gave 1% yield. Further study with other protecting groups for 3,4-dihydroxybenzaldehide as well as variation of reactants’ composition and reaction conditions are necessary in order to increase the fisetin yield. All synthetic products had been characterized by melting point and spectroscopy analysis
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