<em>The aim of this research is to test the influence of GCG and CSR on the firm’s value with profitability (ROA) as the moderating variable. This research uses Double Linear Regression Analysis. Causal research method was employed. 45 companies of manufactures in basic and chemical sector were used as the sample for the year 2012 and 2013. GCG as independent variable was represented with independent commissioner and audit committee. CSR variable was analyzed using GRI 4th version in the year 2015. Tobin’s Q model was used to analyze the firm’s value. This research reveals that the GCG, CSR and ROA simultaneously affects the firm’s value. Meanwhile, the CSR variable affects the firm’s value, GCG variable has negative effect on the firm’s value. The ROA does not affect the firm’s value, ROA which interact with CSR resulting negative effect toward the firm’s value. This means that ROA as moderating variable weakens the relation of CSR on the firm’s value. On the other hand, ROA strengthens the relation of GCG on the firm’s value.</em>

Data processing can be done with text mining techniques. To process large text data is required a machine to explore opinions, including positive or negative opinions. Sentiment analysis is a process that applies text mining methods. Sentiment analysis is a process that aims to determine the content of the dataset in the form of text is positive or negative. Support vector machine is one of the classification algorithms that can be used for sentiment analysis. However, support vector machine works less well on the large-sized data. In addition, in the text mining process there are constraints one is number of attributes used. With many attributes it will reduce the performance of the classifier so as to provide a low level of accuracy. The purpose of this research is to increase the support vector machine accuracy with implementation of feature selection and feature weighting. Feature selection will reduce a large number of irrelevant attributes. In this study the feature is selected based on the top value of K = 500. Once selected the relevant attributes are then performed feature weighting to calculate the weight of each attribute selected. The feature selection method used is chi square statistic and feature weighting using Term Frequency Inverse Document Frequency (TFIDF). Result of experiment using Matlab R2017b is integration of support vector machine with chi square statistic and TFIDF that uses 10 fold cross validation gives an increase of accuracy of 11.5% with the following explanation, the accuracy of the support vector machine without applying chi square statistic and TFIDF resulted in an accuracy of 68.7% and the accuracy of the support vector machine by applying chi square statistic and TFIDF resulted in an accuracy of 80.2%.

BATIK -- craft is a cultural heritage of Indonesia which existence keep growing each day. It is characterized by the existence of batik craft in various regions with their own characteristics. As a cultural heritage, batik craft had been around since the time of the kingdom era in our nation. Before the discovery of synthetic materials technology, batik coloration has always been using natural colors that are available in Indonesia. Natural coloration can be taken from tinggi wood, tegeran plant, teak leaf, indigo plant, secang, mahogany, and other plants. As the times progressed, natural coloring began to be replaced and abandoned by the craftsmen. Crafters use synthetic coloring starting in the early 20th century. Currently there is an awareness to return to the natural coloring because it is considered to be more environmentally friendly and cheaper. The use of natural coloring also pushes batik selling value higher when compared to the one using synthetic color

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Scheduling problems at the university is a complex type of scheduling problems. The scheduling process should be carried out at every turn of the semester's. The core of the problem of scheduling courses at the university is that the number of components that need to be considered in making the schedule, some of the components was made up of students, lecturers, time and a room with due regard to the limits and certain conditions so that no collision in the schedule such as mashed room, mashed lecturer and others. To resolve a scheduling problem most appropriate technique used is the technique of optimization. Optimization techniques can give the best results desired. Metaheuristic algorithm is an algorithm that has a lot of ways to solve the problems to the very limit the optimal solution. In this paper, we use a genetic algorithm and ant colony optimization algorithm is an algorithm metaheuristic to solve the problem of course scheduling. The two algorithm will be tested and compared to get performance is the best. The algorithm was tested using data schedule courses of the university in Semarang. From the experimental results we conclude that the genetic algorithm has better performance than the ant colony optimization algorithm in solving the case of course scheduling.

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Wonosobo Batik historically could be traced in Hindu period with the discovery of Syiva wore Parang motif. At the end of the 19th century Wonosobo batik motif was seen in clothes worn by traditional Dutch East Indies officers. In the post-independence period Wonosobo batik was also seen to be worn by the community. Motif used was dominated by Parang motif (machete) Lereng motif (slope) with dark and darkish color. The existence of batik was reappeared at the beginning of 21st century dominated by Carica and purwaceng motifs. These motifs were considered to have local peculiarities of Wonosobo. From these motifs carica combination motif had developed. The motifs which were combined with carica such as Sulur, Sekar Jagat, Kawung, Wayang, Lereng, Lubang Sewu, Kopi, Cabe, Teh, Rejeng, Sidomukti, Topeng, and etc. It meant that Wonosobo batik motifs were varies by adopting potential and local culture