Optimization of Indonesian telematics SMES cluster: industry 4.0 challenge

Eneng Tita Tosida, Irfan Wahyudin, Fredi Andria, Apri Diana Sanurbi, Atik Wartini


Indonesia’s economic are strengthened by 99% of SME players, and one of the growing field of Indonesia’s SMEs is telematics SMEs. Increasing SMEs Telematics Services in Indonesia is a potential that must be supported to have a competitive value, especially in facing Industrial 4.0. But there are many difficulties in determining the decision to provide assistance to SMEs who really need. One of the causes is the number of data and the qualification standard to decide the feasibility of SMEs to be given assistance. The purpose of this research is to explain the optimization process of the formation of the Indonesian telematics SMEs cluster, which are potential to be given assistance, and to face the challenges of Industrial 4.0. The cluster optimization process is carried out by Partitioning around Medoids (PAM) and Fuzzy C-Means (FCM). The data used is the data of SMEs Telematics Services in Indonesia according to the National Economic Census (SUSENAS) data in 2006 Indonesian Central Bureau of Statistics (CBS). The 2006 data usage is caused by the SUSENAS 2016 not yet released by Indonesian CBS. Even though the data used comes from SUSENAS 2006, it is still relevant to be analyzed and mapped into the current conditions. The cluster of Indonesian telematics SMEs was validated using Silhoutte Coefficient which resulted in a value of upper then 0.99. The validation values of the two clustering techniques show a very strong cluster structure.


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