The analysis process for determining Small and Medium Industry (IKM) centers to produce IKM that are able to develop and excel in the era of the COVID-19 pandemic in the City of Yogyakarta. Determination of leading IKM plays an important role in creative and innovative industries. However, there are still many unresolved IKM decisions that are made manually, which makes the process long and inefficient. The entry of technology into various disciplines makes the process of determining the leading IKM more efficient and systematic. To facilitate the determination of leading IKM, you can use the Decision Support System (DSS), where the author in conducting the analysis applies the Analytical Hierarchy Process (AHP) method which can facilitate the determination of IKM by determining the weight of the selected criteria. The results showed that the consistency ratio value was 0,0961 or < 0,1 which from the calculation results can be interpreted as correct based on the CR arithmetic theory in the AHP method and is feasible to use. This study resulted in a ranking of the leading IKM centers, namely alternative A9 in 1st, A3 in 2nd, A2 in 3rd, A8 in 4th, A5 in 5th, A1 in 6th, A10 in 7th, A7 in 8th, A4 in 9th and A6 in 10th. The results of the study found that the AHP method could be used for decision making in determining the leading IKM centers.

Financial problems are one of the reasons why small and medium-sized industries (SMIs) in West Kutai have not developed optimally. Government assistance programs are one of the solutions. This program must be appropriate, so a decision-making tool is needed to help choose the right SMIs to be assisted later. The weight of the criteria was determined using the Analytical Hierarchy Process (AHP) technique, and the priority of the SMIs as the preferred proposal for the recipients of development assistance was determined using the Technique for Other Reference by Similarly to Ideal Solution (TOPSIS) approach. Labor, investment, production capacity, production value, and raw materials were used to determine the priorities of SMIs beneficiaries. Furthermore, TOPSIS prioritizes the development of alternative small and medium-sized industries with types of handicraft commodities. Integration of AHP and TOPSIS methods has been successfully used in the IKM Development Priority Determination Application, with 83.3% precision and 96.4% accuracy achieved by using a confusion matrix so that the IKM ranking can be known. The results of the study found that integration of the two methods was successfully used for Small and Medium Industries Development Decision Making.

Determining small-medium industries (SMIs) centers on producing SMIs capable of developing and excelling in Yogyakarta City. The determination of superior SMIs plays a crucial part in the development of new and creative industries. However, many unresolved SMIs decisions were made manually, thus making the long and ineffective process. Technology entry into various disciplines can make determining superior SMIs more efficient and systematic. To facilitate the determination of superior SMIs, it took advantage of the Decision Support System (DSS), where the author, when carrying out the analysis, applied the Multi-Attributive Border Approximation Area Comparison (MABAC) method for alternative rankings. This research resulted in the ranking of superior SMIs centers, namely alternatives (A6) ranked 1st, (A9) 2nd order, (A2) 3rd order, (A8) 4th order, (A10) 5th order, (A1) 6th order, (A3) 7th order, (A5) 8th order, (A4) 9th order, and (A7) 10th order. The MABAC method was successfully used in the decision-making of superior SMIs centers with a precision of 83.3% and an accuracy of 93.5%, calculated using a confusion matrix. The study’s results discovered that the MABAC approach was successfully used for decision-making for determining superior small and medium industry centers.