Freight forwarding services are increasingly developing and each delivery service provider competes to provide the best service, resulting in competition in terms of price and delivery time, in order to attract the attention of users of shipping services. The number of service providers with various types of packages offered by freight forwarding services, making users difficult in determining the right service provider. One way to overcome this problem is by the existence of a method that can provide recommendations as consideration for making appropriate decisions. This study aims to create a decision support system for the selection of goods delivery services by applying the Simple Additive Weighting method that can solve problems by comparing between shipping services. The results of this study are in the form of conclusion calculations that can be taken into consideration for decision making in choosing the most widely chosen freight forwarding services for students and getting the best results in decision making. The results of calculations using the Simple Additive Weighting method, the highest value based on time criteria is JNE YES with a value of 0.73, based on price criteria is a vehicle with a value of 0.68, based on the weight criteria is JNE YES with a value of 0.75, while based on the volume criteria the highest value is a vehicle with a value of 0.70 .

Fulfillment of academic information to support a decision in a college is very necessary, especially to support an academic planning and evaluation in higher education. Often management asks the student academic bureau to find out the number of students based on their class, period, number of graduates, class schedules to student grades. This encourages the student academic bureau to create a desktop-based application that can be used to find out more quickly the needs requested by management. By using the extreme programming (XP) model, it can accommodate the academic information needs of student affairs in universities in the form of a recap of academic data that can be presented in real time and quickly for the upper level management.

This research was conducted to help determine the menu or package that is often purchased simultaneously. The priori algorithm is used to produce data mining regarding the determination of association rules which is carried out by calculating support and confidence in the sales of food menu mechanisms in a restaurant with a case study of the restaurant d'DSL Lembang. The resulting a priori algorithm will be implemented and tested with the Tanagra application. From the results of the discussion and data analysis carried out, it was found that with the application of the a priori algorithm in determining the combination between itemset with a minimum support of 60% and a minimum confidence of 90%, it was found in the initial calculation of the combination of one itemset, a combination of 2 itemset, a combination of 3 itemset and a final association rule with The highest value of support and confidence is if the consumer orders the Hot Sweet Tea menu, Chicken Driver Package and Liwet Rice at the same time with a support value of 58% and a confidence value of 100%.