Implementasi Metode Topsis Pada Sistem Pendukung Keputusan Penentuan Prioritas Penerima Bantuan Mesin Untuk Sentra Ikm Berbasis Website (Studi Kasus : Dinas Perindustrian Dan Perdagangan Provinsi Bengkulu) - Exca Wella Monica; Desi Andreswari; Julia Purnama Sari (Jurnal Pseudocode, 2026)
The industrial sector is one of the economic sectors being developed in Indonesia as a driving force for the progress of other economic sectors. One form of this is the Small and Medium Industries (SMEs), which are quite dependent on government assistance, both in terms of capital and equipment. One of the government programs to advance SMEs is the provision of machinery assistance to SME centers. In practice, the selection process for machine assistance recipients at the Bengkulu Industry and Trade Office still uses Microsoft Excel, which has limitations, including the risk of human error, logical errors in formulas, differences in results due to rounding numbers, and a lack of objectivity in assessments. Therefore, a Decision Support System (DSS) is needed to minimize errors, producing more objective, transparent, and accurate decisions. This study uses the TOPSIS method to calculate the preference value of SMEs and data aggregation techniques (averages) to calculate the final value of SME centers. The resulting output is a ranking of SME centers eligible for machine assistance. Of the total of 26 comparisons between the rankings from the system and the rankings from the Industry and Trade Office, 20 rankings were obtained that were the same, so that the system accuracy reached 76.92%. Furthermore, the system's feasibility test achieved an interval score of 4.6, or 92%, which is considered very good. The final result of this research is the creation of a website-based decision support system for prioritizing recipients of machine assistance for small and medium enterprises SME centers.