Sabar Hanadwiputra
@stmik.banisaleh.ac.id
Teknik Informatika
STMIK Bani Saleh
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Linda Marlinda, Yusuf Durachman, Eva Zuraidah, Tukino, Widivawati, and Sabar Hanadwiputra
IEEE
Indonesian online sales are currently experiencing rapid growth and can provide solutions to the problems of marketing products for Micro, Small, and Medium Enterprises (MSMEs) managed by women entrepreneurs. There are several obstacles in marketing the product, including lack of e-marketplace information, HR skills, product design that is less attractive, and the quality of the goods produced so that it can cause bankruptcy. The sample in this study was taken from MSMEs, managed by women entrepreneurs randomly in Indonesia. This study uses primary data obtained through questionnaire instruments. Data is processed using the Simple Multi-Attribute Rating Technique (Smart) Method. The results of this study found that market services, infrastructure, transaction security, costs, promotions, and value-added services had a positive impact on seller loyalty. Market service is a factor that has the greatest influence on the loyalty of women entrepreneurs in online sellers.
H Setiawan, K Mukiman, Satria, S Hanadwiputra, and A Suwarno
IOP Publishing
Abstract Manufacturing companies engaged in the production of cosmetic products and herbal products on a national and international scale, this company is required to be able to carry out production planning by using classification methods in determining the pattern of delay in production orders for the C4.5 classification algorithm based on Particle Swarm Optimization. The research method used in this experiment is the Cross Industry Standard Model for Data Mining (CRISP-DM). From the results of the C4.5 algorithm optimization analysis with particle swarm optimization (PSO), it can be concluded that the accuracy value obtained from the PSO-based C4.5 algorithm model is 82.52%. This is better than the C4.5 algorithm model which produces an accuracy value of 80.17%. The Difference of 0.033 with the details of the C4.5. Algorithm producing an AUC value of 0.855 with a diagnosis of Good Classification. The results of the optimization analysis of the C4.5 algorithm with PSO, the pattern of delay that is formed is that the production status is the status that causes the most delay in production orders. then followed by the status of waiting for pre-production and administrative status. the emerging status must be a correction and attention so that management becomes better.