DIGITAL TRANSFORMATION IN THE SMALL TO MEDIUM INDUSTRIES (IKM) AUTOMOTIVE COMPONENTS IN INDONESIA

Digital transformation is a new strategy in maintaining business continuity and supporting the stability of SMI players when the conditions of the business environment experience rapid changes, especially in the midst of the Corona Virus Disease 2019 (Covid-19) pandemic.. The research developed a model of the moderating effect of adaptive leadership on the relationship of strategic flexibility to digital transformation by integrating strategic intelligence, workforce transformation


INTRODUCTION
Digital transformation is the application of digital technology in all aspects of people's lives, including business.With collected data and the right digital strategy, businesses can create products and services tailored to consumer tastes, reduce excessive spending costs, and increase revenue streams.The urgency to help Small and Medium Industries (IKM) automotive components transform and adapt to the rapidly changing digital economy is very important, because the key to successful digital transformation is investing in people's digital literacy skills (Dinisari, 2021).It is deemed necessary for automotive component SMEs to adopt digitalization to maintain productivity and maintain their income amidst Covid-19.Digital sales penetration could be their main strategy because this strategy can expand market reach (Jelita, 2021).
The large contributions and contributions from automotive component IKMs are a sign that digital economic transformation through automotive component IKMs is an important thing to pay attention to as a driver of the Based on the table above, it can be seen that the outer model value or correlation between constructs and variables meets convergent validity because all indicators have loading factor values above 0.700.Therefore, it can be concluded that the indicators used in this research have met convergent validity and can be used for further data processing.
Apart from that, the overall convergent validity used for each construct variable can also be seen from the AVE value.The AVE value is required to be > 0.5, which means that 50% or more of the indicator can be explained (Ghozali, 2014).The results of the AVE value test can be seen in the following table: From the results of testing the reliability construct values above, it shows that the Cronbach's alpha or composite reliability value of all constructs has a value of > 0.7 so it can be concluded that all indicators in this study have met the reliability requirements, and the research variables are proven to have accuracy, consistency and precision of the instruments in measure the construct well.The correlation coefficient value above can be explained as follows: 1.The correlation coefficient value obtained between strategic intelligence and strategic flexibility is 2.757, which shows that the model is strong because it is in the interval > 0.35.The positive correlation coefficient value indicates that the relationship between the two is unidirectional, meaning that the better the strategic intelligence (increasing by 1 unit), the impact will be on increasing strategic flexibility (i.e 2.757).2. The correlation coefficient value obtained between workforce transformation and strategic flexibility is 1.711, which shows that the model is strong because it is in the interval > 0.35.The positive correlation coefficient value shows that the relationship between the two is unidirectional, meaning that the better the workforce transformation (increasing by 1 unit), the impact will be on increasing strategic flexibility (i.e 1.711).3. The correlation coefficient value obtained between dynamic capabilities and strategic flexibility is 3.598, which shows that the model is strong because it is in the interval > 0.35.The positive correlation coefficient value shows that the relationship between the two is unidirectional, meaning that the better the dynamic capability (increasing by 1 unit), the impact will be on increasing strategic flexibility (i.e 3.598).4. The correlation coefficient value obtained between strategic intelligence and digital transformation is 0.283, which indicates that the model is moderate because it is in the interval 0.15-0.35.The positive correlation coefficient value shows that the relationship between the two is unidirectional, meaning that the better the strategic intelligence (increasing by 1 unit), the impact will be on increasing digital transformation (by 0.283).5. 5.The correlation coefficient value obtained between workforce transformation and digital transformation is 0.532, which shows that the model is strong because it is in the interval > 0.35.The positive correlation coefficient value shows that the relationship between the two is unidirectional, meaning that the better the workforce transformation (increasing by 1 unit), the impact will be on increasing digital transformation (i.e 0.532).6.The correlation coefficient value obtained between dynamic capabilities and digital transformation is 0.238, which indicates that the model is moderate because it is in the interval 0.15-0.35.The positive correlation coefficient value indicates that the relationship between the two is unidirectional, meaning that the better the dynamic capabilities (increasing by 1 unit), the impact will be on increasing digital transformation (i.e 0.238).7. The correlation coefficient value obtained between adaptive leadership and digital transformation is 3.285, which shows that the model is strong because it is in the interval > 0.35.The positive correlation coefficient value shows that the relationship between the two is unidirectional, meaning that the better the adaptive leadership (increasing by 1 unit), the impact will be on increasing digital transformation (i.e 3.285).8.The correlation coefficient value obtained between strategic flexibility and digital transformation is 5.161, which shows that the model is strong because it is in the interval > 0.35.The positive correlation coefficient value shows that the relationship between the two is unidirectional, meaning that the better the strategic flexibility (increasing by 1 unit), the impact will be on increasing digital transformation (i.e 5.161).

Coefficient of Determination (R2)
The coefficient of determination is a number that shows the magnitude of the influence contribution given by the exogenous latent variable to the endogenous latent variable.Based on the test results, the following results were obtained: ).These results show that the variables strategic intelligence, workforce transformation, dynamic capabilities, adaptive leadership, and strategic flexibility together have an influence of 88.1% on digital transformation, while the remaining 11.9% is (1-R Square) the magnitude of the contribution of influence provided by other factors not studied.

Predictive-Relevance (Q2)
Q Square predictive relevance for structural models is used to measure how well the observed values are produced by the model and also its parameter estimates.A model is considered to have relevant predictive value if the Q Square value is more than 0 (> 0).The predictive-relevance value is obtained by: The predictive-relevance values for the strategic flexibility variable are: Meanwhile, the predictive-relevance value for the digital transformation variable is: Based on the calculation results above, a Q Square value of 0.974 is obtained.This shows that the large diversity of research data that can be explained by the research model is 97.4%, so that the research model produces very good observation values and parameter estimates and has predictive relevance.Meanwhile, the remaining 2.6% is explained by other factors outside this research model.
The Q Square value of strategic flexibility was obtained at 0.613, which indicates that the variables strategic intelligence, workforce transformation, and dynamic capabilities have a good level of prediction of strategic flexibility.Then the Q Square for digital transformation was obtained at 0.776, which shows that strategic intelligence, workforce transformation, dynamic capabilities, adaptive leadership and strategic flexibility have a good level of prediction of digital transformation.
Thus, from these results, this research model can be stated to have good goodness of fit (GOF).

Relationship of Direct and Indirect Influence
In this research, a model of the direct and indirect influence of strategic intelligence variables, workforce transformation, dynamic capabilities, and adaptive leadership on strategic flexibility and digital transformation can be seen as below: Based on the table above, explain the direct and indirect influences in this research as follows: 1.The direct and indirect influence of strategic intelligence on digital transformation through strategic flexibility.
The magnitude of the direct influence of strategic intelligence on strategic flexibility is 0.127 (12.7%) and 87.3% of strategic flexibility is influenced by external factors other than the strategic intelligence factors studied.Meanwhile, strategic intelligence indirectly influences digital transformation through strategic flexibility with a value of 0.162 (16.2%).So the total influence of the strategic intelligence variable on digital transformation through strategic flexibility is 0.289 (28.9%).

The influence of workforce transformation, both directly and indirectly, on digital transformation through strategic flexibility.
The magnitude of the direct influence of workforce transformation on strategic flexibility is 0.173 (17.3%) and 83.7% of strategic flexibility is influenced by external factors other than the workforce transformation factors studied.Meanwhile, workforce transformation indirectly influences digital transformation through strategic flexibility with a value of 0.108 (10.8%).So the total influence of the workforce transformation variable on digital transformation through strategic flexibility is 0.281 (28.1%).

The influence of dynamic capabilities both directly and indirectly on digital transformation through strategic flexibility.
The magnitude of the direct influence of dynamic capabilities on strategic flexibility is 0.111 (11.1%) and 89.9% of strategic flexibility is influenced by external factors other than the dynamic capabilities factors studied.Meanwhile, dynamic capabilities indirectly influence digital transformation through strategic flexibility with a value of 0.156 (15.6%).So the total influence of the dynamic capability variable on digital transformation through strategic flexibility is 0.267 (26.7%).

Focus Group Discussion (FGD)
Limited FGD activities were carried out virtually to strengthen and complete the results of research analysis for discussion participants consisting of representatives of ministries/institutions, associations and related business actors Several things have been conveyed by relevant stakeholders in the FGD and summarized by researchers in order to complete and strengthen the results of this research analysis, namely: 1. Supports the results of hypothesis testing which proves that strategic intelligence has a positive and significant effect on strategic flexibility in automotive component SMEs in Indonesia.This influence exists because strategic intelligence is an important factor for automotive component SMEs to be able to predict consumers and competitors so that they can achieve strategic flexibility.2. Agree with the results of hypothesis testing which proves that workforce transformation has a positive and significant effect on strategic flexibility in automotive component SMEs in Indonesia.This influence occurs due to the ability to form human resources that respond more quickly and are adaptive to environmental changes, so that workforce transformation will become an important factor for automotive component SMEs in supporting strategic flexibility.3. Support the results of hypothesis testing which proves that dynamic capabilities have a positive and significant effect on strategic flexibility in automotive component SMEs in Indonesia.This influence occurs because dynamic capability is an important factor for automotive component SMEs to be able to innovate product development and detect changes in the dynamic business environment, in order to achieve strategic flexibility.4. Support the results of hypothesis testing which proves that strategic intelligence has a positive and significant effect on digital transformation in automotive component SMEs in Indonesia.This influence occurs because strategic intelligence is an important factor for automotive component SMEs to be able to realize digital transformation through exchanging information and collaborating in the use of technology with partners.5. Agree with the results of hypothesis testing which proves that workforce transformation has a positive and significant effect on digital transformation in automotive component SMEs in Indonesia.This influence occurs because workforce transformation is an important factor for automotive component SMEs in implementing digital transformation by upgrading workforce skills and increasing workforce productivity.6. Express his support for the results of hypothesis testing which proves that dynamic capabilities have a positive and significant effect on digital transformation in automotive component SMEs in Indonesia.This influence occurs because dynamic capabilities are an important factor for automotive component SMEs in realizing digital transformation by building supporting networks and transferring knowledge.7. States that it is in line with the results of hypothesis testing which proves that strategic flexibility has a positive and significant effect on digital transformation in automotive component SMEs in Indonesia.This influence occurs because strategic flexibility is an important factor for automotive component SMEs in realizing digital transformation through the ability to change production levels and adjust management to changing environmental conditions.8. Support the results of hypothesis testing which proves the existence of moderation from adaptive leadership on the relationship between strategic flexibility and digital transformation in automotive component SMEs in Indonesia.This influence occurs because adaptive leadership is an important factor for automotive component SMEs in increasing strategic flexibility to carry out digital transformation through the ability to solve problems of change and provide resources in a sustainable manner.

CONCLUSION
The development of a model of the influence of strategic intelligence on strategic flexibility in automotive component SMEs in Indonesia shows a positive and significant relationship.Automotive component SMEs who can predict consumers, competitors and technology; and has a vision to become an IKM that has a good reputation, grows quickly and is continuously sustainable, will achieve higher strategic intelligence, so that strategic intelligence becomes an important factor for automotive component IKM players in Indonesia which can have an impact on improving ability to build strategic flexibility.The development of a model of the influence of workforce transformation on strategic flexibility in automotive component SMEs in Indonesia shows a positive and significant relationship.Automotive components SMEs who can form human resources that are flexible and effective, easily adapt to change, have a fluid attitude, always respond more quickly to changes in digital technology, are agile to achieve organizational goals, and are always more adaptive in responding to organizational changes, will achieve energy transformation higher levels of work, so that workforce transformation becomes an important factor for automotive component SMEs in Indonesia which can have an impact on increasing capabilities in designing strategic flexibility shows a positive and significant relationship.Automotive components SMEs who can discover new products, carry out product development, make process improvements, detect periodic changes in the business environment, track customer wants and needs, and identify organizational changes, will achieve higher dynamic capabilities.The development of a model of the influence of strategic intelligence on digital transformation in automotive component SMEs in Indonesia shows a positive and significant relationship.Automotive component SMEs who can build good relationships with customers, exchange information with partners, collaborate in the use of technology, implement positive competition, provide incentives, and use effective communication, will achieve higher strategic intelligence, so that strategic intelligence becomes one of the important factors for automotive component SMEs in Indonesia.The development of a model of the influence of workforce transformation on digital transformation in automotive component SMEs in Indonesia shows a positive and significant relationship.Automotive component IKM players who are able to upgrade workforce skills, implement improvements in workforce quality, increase workforce productivity, identify new social values in society, socialize the introduction of new social values in the workplace, and implement new social values in the workplace, will achieve higher levels of workforce transformation.The development of a model of the influence of dynamic capabilities on digital transformation in automotive component SMEs in Indonesia shows a positive and significant relationship.Automotive component SMEs who are able to form social networks, build support networks, create networks between companies, have high managerial commitment, encourage openness and experimentation, and carry out knowledge transfer and integration, will achieve higher dynamic capabilities, so that dynamic capabilities become one an important factor for automotive component SMEs in Indonesia which can have an impact on increasing capabilities in implementing digital transformation.The development of a model of the influence of strategic flexibility on digital transformation in automotive component SMEs in Indonesia shows a positive and significant relationship.Automotive component SMEs are able to change production levels, change production capacity, have strategies for using other organizational capacities, communicate dynamically, make management adjustments to different conditions and workers.And this research proves the development of a model of the moderating influence of adaptive leadership on the relationship between strategic flexibility and digital transformation in automotive component SMEs in Indonesia.Through the role of a leader who is able to solve change problems, create solutions and change strategies, convey information on business process changes, provide resources on an ongoing basis, build support systems to support change, and strive for the development of new skills and competencies.

International
. The development of a Journal homepage: https://bajangjournal.com/index.php/IJSSmodel of the influence of dynamic capabilities on strategic flexibility in automotive component SMEs in Indonesia

IJSS Reliability Test The
reliability test was carried out by looking at the Cronbach's alpha and composite reliability values.The Cronbach's alpha or composite reliability value must be greater than 0.7 and is said to have a good reliability value, but a value of 0.6-0.7 is still acceptable for explanatory research (Ghozali, 2014).The results of testing the reliability construct values are shown in the following table.

Table 4
In the table above, the R Square value for the strategic flexibility variable obtained is 0.783 or 78.3%, which indicates a good model because the R Square is greater than 0.75 (Hair et al, 2011).These results show that the variables strategic intelligence, workforce transformation, and dynamic capabilities together have an influence of 78.3% on strategic flexibility, while the remaining 22.7% is (1-R Square) the magnitude of the influence contribution provided by other factors not studied.