Batik is a native Indonesian cultural heritage. The batik industry is spread in several cities such as Surakarta, Yogyakarta, Pekalongan, Cirebon, Madura and other cities. The development of the batik industry not only increased people incomes but also on various environmental impact. The batik production process consists of several stages, each stage using different chemicals, so the impact is also different. This study, therefore, aims to compare the environmental impacts caused by each stage in the batik production process, in an that it can be seen where the process with the highest environmental impact can be proposed for further improvement. The parameters analyzed include Human Health, Ecosystem Quality and Resources. The result is a coloring that has the greatest environmental impact when compared to other processes. This was due to the use of chemicals for the coloring process, encompassing remasol, water glass, soda ash mixed with water. The many chemicals used cause the greatest environmental impact compared to other processes. Therefore, reducing and reusing of chemicals dyes for the subsequent coloring processes or the adoption of natural dyes from plants origin are capable of reducing the environmental impacts.

Batik fabric is a product of the creative industry which is a product of micro, small and medium enterprises (SMEs) in the field of handmade. The aim of the study is to raise the potential of batik fabric products, performance marketing mix model so that batik fabric products (batik) able to increase sales volume. The design and construction strategy marketing mix applied to increase sales is through the development of marketing mix approaches 9Ps (products, prices, promotions, distribution, people, physic evidend, process, payment, packaging) to sales volume in pandemi Covid 19. This research is beneficial as a marketing development model of “Batik” fabric products so that the output is used as a source/material in mentoring or guiding marketing for “Batik” fabric entrepreneurs. The method of data analysis through Structural Equation Modelling (SEM) analysis to design models of marketing mix on sales volume.

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