his research is based on the background of the problem that cost estimation is very beneficial for the owner, contractor and consultant. Errors in estimating costs are very often done, this is due to lack of experience and information obtained by an estimator. The purpose of this study is to obtain an equation that can help an estimator in estimating costs whose results approach the actual cost and can speed up the estimation process. The data that used in this research is from RAB’s 45 type house in Central Sulawesi. The method that will be used in this research is Pearson Correlation and Quadratic Regression. Pearson correlation is used to see the correlation between the independent and dependent variables while the Quadratic Regression is used to get the equation between the independent variable and the dependent variable. Regression modeling results obtained are y=-649,15X1+0,0022X1^2+182X3-0.0005X3^2+e, with R2 = 95%. The variables that significant in this research are raw material ( X1) and concrete brick ( X3)
Unemployment is a very complex problem because it affects and is influenced by several factors that interact with each other following a pattern that is not always easy to understand. If unemployment is not immediately addressed, it can cause social vulnerability and potentially lead to poverty. This research will use the spline regression method in modeling the 2018 Sulawesi open unemployment rate. The results obtained are the best spline model obtained from the optimum knots point with a combination of knots 3,3,1,1,3,3. This model has the minimum GCV value 1,97 with R2 77,67%. All variables significantly influence the open unemployment rate.
Human Development Index (HDI) is an important issue in designing and strategizing of sustainable development. Multivariate Adaptive Regression Spline (MARS) is a regression approach that produces models with continous character on knots. MARS models are determined based on trial and error for a combination of basis function (BF), maximum interaction (MI), and minimum observation (MO). The determination of knots is based on the minimum Generalized Cross Validation (GCV) value. The results of this study are the combination value of BF = 52, MI = 3, and MO = 2 with a minimum GCV of 0,00049. The factors that influence HDI are average school length (X2) per capita expenditure (X4), life expactancy (X3), persentage of poor woman aged 15-49 who use the birth control tool (X5).
Auction in Indonesia is carried out by the Office of State Assets and Auction Services (KPKNL). Goods auctioned at KPKNL are quite diverse including land, wood, inventory, vehicles, and other goods. However, not all of the items auctioned were sold. Because not a few items have been auctioned but no one has made an offer. The Purpose of this study is to compare two classification methods, C4.5 and C5.0 algorithm and to determine which items were successfully auctioned with those that did not and its factors. The methods that used were comparing the classification tree C4.5 algorithm and C5.0 algorithm with cross validation. From the results of the comparison of the two methods, it was found that the C5.0 Algorithm method was rated better than the C4.5 algorithm in classifying the auction results with an accuracy of 96.43% and 92.86% respectively. In this case, C5.0 has a higher precision than C4.5.
Local Own-source Revenue (LOR) is all regional revenue that comes from the region's original economic resources. It is very important to identify it by researching and determining the Regional Local Own-source Revenue (LOR) by properly researching and managing the source of revenue so as to provide maximum results. Central Sulawesi Province itself has Local Own-source Revenue (LOR) in the Regional Revenue and Expenditure Budget of the 2018 Budget Year has reached Rp1 trillion. The increase or decrease in growth of local revenue is influenced by the amount and type of tax, levies collected by local governments and the lack of incentives for the management apparatus to carry out tax collection and levies. This study uses spline regression analysis because the data of the Local Own-source Revenue (LOR) in Central Sulawesi in 2018 does not have a pattern so that it fits perfectly with that method. Then after processing the data obtained the results of spline nonparametric regression modeling using the optimal knots point obtained from the minimum GCV value. The best spline nonparametric regression model is written as follow . It can be concluded that in Central Sulawesi in 2018 the lowest Local Own-source Revenue (LOR) value was Banggai Laut Regency with 21,776 billion rupiahs and the highest Local Own-source Revenue (LOR) value was Palu City at 267,402 billion rupiahs.
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