PC computer is a flexible electronic device and can receive and process data quickly and accurately, and can also store data for a long time. There is a time when the PC hardware is damaged. So that it annoys the user. In connection with the problems that occur, the researchers aim to build an Expert System application to diagnose damage to PC computers using the Certainty Factor method by using Visual Studio 2010 applications and using Microsoft Access 2013 as a database. Applications that are built can be an alternative in knowing the type of damage and provide alternative solutions in handling damage to PC computer hardware.

The decision support system for the best lecturer selection has been made in this study so that it can be recommended to the foundation so that it is efficient compared to the use of the old system. In determining the lecturer at STMIK Pelita Nusantara, the method used is the TOPSIS method using criteria that will be determined by the Foundation. The selection of lecturers at STMIK Pelita Nusantara is determined by several criteria, namely, attendance, teaching, service, research and neatness. The Topsis method is very suitable because the concept is practical. The output in this system is the calculation value of lecturer selection using the TOPSIS method and the ranking of lecturers at STMIK Pelita Nusantara

Chicken disease is a condition in which the body organs of chickens cannot function normally. Diagnosing a disease requires symptoms that appear on the chicken’s body. To conduct a disease diagnosis, further examination is needed by specialists (experts). An expert system is a system that uses human knowledge that is entered into a computer to solve problems that are usually resolved by experts. The system created in solving problems uses the Bayes Theorem method in which the inference process uses Forward Chaining. The application was developed using the visual basic 2010 programming language and MySQL database.

The Department of Informatics at STMIK Pelita Nusantara is one of the departments at private universities that focuses on the science of information technology. Thesis problems in this department must also be resolved immediately, one of which is a system that utilizes information technology. It is difficult for students to determine the choice of thesis topic to be prepared as a graduation requirement. There are 7 criteria used, namely: Academic Value, Historical Project, Research Activeness, Training, Interests, Value of Practice and Research Place. Research data obtained from STMIK Pelita Nusantara applied the SAW (Simple Additive Weighting) method using Visual Basic Net 2010 with Mysql Database. From the ranking it shows that the highest result is alternative A1 where in this example the thesis topic chosen is Expert System.

The retail business continues to grow rapidly along with the development of science and technology in the era of globalization, but the purchase of fabric is still done manually and not computerized, such as in choosing fabrics, only looking at the shape of the color and the price tag, if it is suitable and likes it is taken immediately without thinking what type of fabric to use. used for these clothes, when they have been made into clothes or clothes, do not match the criteria desired by consumers and many ready-made clothes are returned because the color becomes dull or faded, and does not match the desired motif. The problem in this study is to determine the selection of the best fabric using SPK with the Simple Additive Weighting (SAW) method in selecting the best fabric at Crown Textile Tailor built using PHP MyAdamin programming. The decision support system method used is Simple Additive Weighting (SAW), because it can determine the weight value for each attribute, through a ranking process selecting the best alternative from a number of alternative data, the results obtained are Viscose Rayon Fabrics worth 0.933, (Rank 1), Brukat Lace Fabrics are worth 0 .9 (Rank 2), Toyobo Cotton Fabric is worth 0.716 (Rank 3), Japanese Cotton Fabric is worth 0.700 (Rank 4).