The purpose of this research is to develop a model for measuring the efficiency of the TTO incubation process performance to accelerate the commercialization of research results in universities. The method of analyzing the efficiency used in this research is the Data Envelopment Analysis (DEA) method based on Banker, Charnes, and Cooper (BCC), which is output-oriented. The software used in analyzing the efficiency of TTO performance is MaxDEA 8. The output of this research is a mathematical model tool for measuring the efficiency of TTO performance by DEA, which considered 17 parameters and proposed recommendations for TTO performance strategies. The limitation of this research is the object of research in one university that has succeeded in the commercialization of research. This research implies that the performance efficiency measurement model is an alternative predictive way to increase the acceleration of commercialization. The practical implications of this research are that it can evaluate performance or inefficient strategies in the incubation process of higher education research results to the Technology Transfer Office (TTO). This research also provides recommendations on strengthening the TTO function that can be used as a reference for improving performance at universities. This research measures the level of performance evaluation of TTO in the incubation process, which refers to the Death Valley framework. This incubation process is the main process accelerating the commercialization of research results in universities.

The development of technology and information has a significant impact on society, both positively and negatively. Digitalization has resulted in many people switching from printed newspapers to digital newspapers. This could lead to demand uncertainty in the newspaper industry. At PT.XYZ, the number of newspapers produced and distributed to realtors often exceeds customer demand. In 2017, the company's return rate reached 5%. However, every January, March, and April where the Chinese New Year Festival, Dalang Cilik Festival, and World Dance Day are held, the demand will increase. This surge in demand, if not anticipated properly, can result in unfulfilled customer demands. For this reason, in this research, forecasting is carried out by considering special event factor using Holt-Winter's, Decomposition, and Exponential Smoothing Event-Based method. To decide which method is the best, the MAPE value was used as criteria. The MAPE value for Holt-Winter's, Decomposition, and Exponential Smoothing Event-Based method respectively are 0,92%, 1,05%, and 3%. Based on the MAPE value for each method, it can be seen that the most effective forecasting method is Holt's-Winter method with a MAPE value of 0.92%.

The rapid development of communication and information technology has given birth to new digital-based media that have changed people's behavior in consuming mass media. Consumers are significantly moving from conventional media to digital. Print media lost readers drastically, especially from the young group. This had some negative effects on the demand for printed newspapers, with frequent supply-demand inaccuracies resulting in many newspapers being returned. For this reason, it is necessary to determine the method of forecasting the number of newspaper requests that has the smallest error rate so that it can help companies reduce losses due to newspaper returns. This study calculates demand forecasting using the trend line analysis method in three conditions, namely when demand decreases, increases, and is seasonal. Furthermore, the three conditions are compared with the forecasting results. The selection of the forecasting method for the best conditions is done by comparing the error rate (MAPE) of each condition with the trend line analysis method, then the trend line analysis method is chosen under certain conditions with the smallest error rate. Based on the comparisons made, it can be seen that the forecasting method that has the smallest error rate is the trend line analysis method with an uptrend with a MAPE value of 4.56%. Therefore, the conditions that are suitable for using the trend analysis method are obtained, namely when demand increases or has an uptrend.

The main factors in achieving maximum company profits is the distribution of goods/products. Optimal distribution means that the product is received by the consumer in the right quantity, in good condition, at the time promised and at a low cost. One example in the case of the newspaper industry, there is a problem related to determining vehicle routes that aim to minimize route distances and minimize transportation costs from distribution warehouses to consumers or what is commonly called the Capacitated Vehicle Routing Problem (CVRP). CVRP is related to determining the distribution channel of a product optimally. The purpose of this research is the formation of the Capacitated Vehicle Routing Problem model on the daily distribution route problem of PT. ABC in the Solo Raya area by using a comparison between the sweep algorithm and the heuristic algorithm. The results of the study showed that the best method to solve CVRP problems at PT. ABC is a heuristic algorithm with less distance traveled than the sweep algorithm method.