FACTORS INFLUENCING COMMUNITY’S INTEREST IN BUYING JAMBI BATIK

The good support of City of Jambi Government had an impact on the rise of the number of Jambi batik craftsmen. However, this rise does not cause a significant influence on people's interest in buying Jambi batik. This study aims to determine the factors that affect people's interest in buying Jambi batik in the city of Jambi. By using factor analysis, this research found that the factors influencing people's interest in buying Batik Jambi are: comfort ability to wear, variety in design, filler ornaments, always update model, safe to wear, primary / main color, secondary color, main ornament, colors, durability, quality, pattern / motif, having characteristic, and privilege. We recommend that all concerned parties, through the local government to make a new breakthrough in order to increase the interest of Jambi people to Jambi batik.


Research Background
The beauty of Jambi batik was adopted from the inspiration of those who are art-minded and of course full of ideas about art itself which eventually poured into the form of patterns and or patterns of Jambi batik itself. The source of ideas from Jambi batik patterns can be in the form of nature, plants/flowers, animals, buildings, fruits and humans as well as other forms adapted to the needs of the people who use Jambi batik itself. Therefore the designs or patterns found on a piece of Jambi batik cloth are mostly from natural shades whose inspiration is lifted from nature, so batik is also considered a natural work of art. Jambi batik making can be done by: staining by using batik wax as a barrier, in the forms of hand print batik, stamp batik or a combination of hand print and stamp In the past times Jambi batik was only used as traditional clothing for the nobility/Jambi p-1412-3789 www.journalmabis.org e-2477-1783 25 Malay king. The use of Jambi batik patterns, basically since long ago was not associated with the division of caste according to adat, but as a product that is still exclusively used and still limited to the royal palace environment. But in line with the times, batik patterns which are usually only worn by the king and his family are now is not forbidden to be worn by ordinary people. This has an impact on the increasing development of batik business in Jambi which is done simply as a household craft business (Erw: 2009;1). However, the problem is based on the results of previous studies showing that the interest of the Jambi city community is still low to buy Jambi batik (Effiyaldi;2015: 39) The traditional Jambi batik patterns have reached approximately 40 patterns and currently have undergone many modifications/developments in accordance with market tastes and the development of the expansion area. In terms of meaning, there are 5 kinds of meanings of Jambi batik patterns, namely: Duren Pecah, Sanggat Ship, Kuao Berhias, Merak Ngeram and Tampok Manggis (Erw;2009: 7). In each region in Jambi province various kinds of Jambi batik patterns have also developed, namely: Batanghari, Sanggat Ship, Durian Pecah, Merak Ngeram (Jambi city), Encong Kerinci, Tea Leaf, Terung Pirus, Bungo Kopi (Kerinci), Squid, Shellfish, Crab (Tanjung Jabung Barat), Arrowhead, Citrus Leaves from variety decorative (Sarolangun), Elephants, Bungo Bangkai (Bungo), Pineapple, Muaro Jambi Temple (Muaro Jambi), Honey Bee, Rubber Leaves, Bungo Cabe, Sialang Raja, Serat Kayu Rengas (Tebo), Bungo Sawit, Punai Merindu, Pencalong Boat, Bungo Nago Sari (Batanghari), Sitawa, Sidingin (Merangin) (Ida Mariyanti dalam Erw;2009).
Several previous studies related to this study, among others; Yuafni (2012), states that there is a significant influence between capital variables on batik production, labor on batik production and tools and materials on batik production. Qibtiyah's (2008) research findings states that in the development of the Gedog print batik craftsmen business center, there exists supporting factor and inhibiting factor of the market development strategy, for example there are a lot of enthusiasts in batik products (supporting factor), but in the other hand people have difficulty to find production centers (inhibiting factor); there exists loyal customer (supporting factor), but in the other hand there is a raw material scarcity issue (inhibiting factor). It has also been found that the role of the government, especially in the fields of industry, trade and small and medium enterprises cooperatives has provided guidance and assistance. Ilmaya Research, (2011), found that: prices have an influence on buying decisions, product design has an influence on buying decisions, price and product design have an interaction effect on buying decisions. Arumsari's research (2012) shows that product quality variables have a positive and significant impact on purchasing decisions. Price variables have a positive and significant effect on purchasing decisions Furthermore, the study of Kraus and Popek (2013: 7) which examined the factors in determining the design and development of the quality of fruit juice products stated that, the analysis to (fruit juice) main component revealed four independent (orthogonal) regions that determined the quality of fruit juice. Every latent variable (main component) is a quality factor, where certain variables are most tied, that is, the highest factor loading value. Thus, each assessment of the quality of the fruit juice must consist mainly: the amount of sugar content, total solids, sensory quality and total acidity, because these factors are regions that combine to represent the quality of the fruit juice. The results of Sutanto and Kusuma's (2013: 73) study of product attributes in the swallow nest selection of Golden Swallow indicated that the attributes governing consumers' preference to choose Golden Swallow brand of swallow nest products are types of swallow nests based on white level of swallow nest, the weight size of the packaging based on 250-gram levels, and the shape of the swallow's nest based on bowl shape level. Hasan's research, et al. (2012: 156) examined the factors that influence the interest in buying environmentally friendly products. These factors are perceptions of attributes, personal characteristics and external factors. In this study a relationship model between these factors was developed through awareness, interest and desire to buy and then analyzed further. It is found p-1412-3789 www.journalmabis.org e-2477-1783 26 that external factors influence desire to buy environmentally friendly products. This influence is greater than other factors of personal characteristics and perceived attributes.
From the facts above, problems can be formulated in this study, namely; what factors influence people's interest in buying Jambi batik in Jambi city and what are the most dominant factors affecting the buying interest of the people of Jambi city towards Jambi batik. While the purpose of this study is to find out the most dominant factors and factors that influence the buying interest of the people of city of Jambi towards Jambi batik.
Based on the description above, researchers feel interested in lifting this phenomenon into a study as a continuation of previous research.

Literature Review
Schiffman and Kanuk (2007: 201) in Febiana (2014: 3) states that interest is one of the psychological aspects that have a considerable influence on attitude behavior. Lucas and Britt in Natali (2008: 87) and in Maghfiroh (2016), there are several indicators found in buying interest, among others: 1. Interest that shows the concentration and feeling of pleasure 2. Desire (desire) is shown by the urge to want to have 3. Confidence (conviction) is shown by the feeling of individual confidence in the quality, usability and benefits of the product to be purchased Consumer buying behavior occurs in a series of processes, started and influenced by the number of external stimuli; these stimuli can be in the form of marketing stimuli or surrounding environment stimuli. After obtaining a stimulus, it will then be processed by a person according to his characteristics. After that, a purchase decision will be taken. Therefore the process of being interested in a product or service will be experienced by every consumer before the purchase decision is made (Ambarwati et al. 2015: 4).

Population and Sample
In this study, the population that will be used are the people who are in the city of Jambi. The amount of the required sample is determined using the Slovin method (M. Amirin, Tatang) with the formula; n = N / (1 + Ne ^ 2). The size of population (in this case uses the 2010 population census data) is 529.188 people. (Jambi City Bappeda, in Demography: 2007 and Jambi City BPS 2010). The size of sample is calculated based on Proportionate Random Sampling method. It was obtained that the size of samples is 434 people.

Research Instrument
To get data from the research variables, the test instrument in the form of a questionnaire was used to obtain data. There are two types of data, namely primary data and secondary data. Primary data is data collected/obtained by providing a list of questions or questionnaires that have been provided to respondents while secondary data is data obtained through searching documentation and literature that exists and is related to research variables.
The data collection thru this questionnaire was carried out in real (not engineered) situations in accordance with what was perceived, seen and experienced by the respondents and not based on what they wanted. Questionnaires were designed and arranged in the form of statements of what they felt, they saw and experienced which were then responded by all respondents in this study. Each variable consists of several indicators that will serve as guidelines/references in developing the test instrument. And each questionnaire contains several statements relating to the factors of each variable.
To measure the variables in this study, a Likert scale is used. Likert scale is a method that can reveal the respondent's feelings about the work they do by selecting 5 (five) alternative p-1412-3789 www.journalmabis.org e-2477-1783 27 answers arranged in stages with an ordinal scale. The task of the respondent is to choose one alternative answer according to the tendency their feeling, experience and visual perception. The next step is for the researcher to make a score on the chosen data that the respondents have filled based on the normal distribution theory.

Validity and Reliability of Instrument
Validity in general shows a measure that measures what will be measured (Ahiri: 2006: 1). Validity refers to the significance, correctness, usefulness, and conformity of the test score (Ahiri: 1). Validity is a concept related to the extent to which tests have measured what should be measured (Sumarna Supranata: 2004: 50). A good test instrument is a test instrument with good validity.
The next step is to test the reliability of the results of measuring the psychological scale. Tests are carried out when the items selected through a procedure for analyzing items have been compiled into one, or with another designation, that the reliability test is carried out only on the items that are considered valid. For the calculation of reliability, only the score item is considered valid. To determine whether or not valid item scores are obtained from the results of the product moment calculation.

Attribute / Factor
Based on the identification of variables of public buying interest in Jambi batik, the following is the formulation of the attributes of the buying interest variable: affordable price, competitive prices, attractive prices, price conformity with quality, different prices for different materials, safe to wear, quality, comfortable to wear, durable, unique, privilege, special characteristics, always updating models, variations in design, colors, patterns, attractive main ornaments, attractive fillers ornaments, beauty and attractive primary/main, secondary/additional colors adding to pattern beauty and attractiveness.
In general, factor analysis can be done if the KMO index is greater than 0,5. The Barttlet test is used to test whether the correlation matrix of the relationship between attributes/factors is the identity matrix. This is used to test the adequacy of the relationship between attributes/factors where the identity matrix contains a diagonal matrix of 1, while the other is 0. The hypothesis; H0: correlation matrix = identity matrix, H1: correlation identity matrix.
Based on the results of the KMO and Bartlett's Test (a) table above, it can be seen that the KMO value is 0,913652 (> 0,5) and Bartlett's Test p-value is 0,00 (< 0,05). Based on the table above, it can be seen that all MSA values are greater than 0.5. Therefore, a factor analysis can be done.

Anti-image Matrices
In addition to checking the KMO and Bartlett test, checking anti-image matrices is also conducted to determine whether the attributes are partially feasible for analysis and exclude from testing. Based on the results of the analysis on the output marked a in the anti-image correlation column, it can be seen that of the twenty attributes to be analyzed, all

Communalities
The Communalities table explains that the percentage of new factors or attributes formed from factor analysis can explain the variance of the variable. From all values in table of communalities, it is found that there are 13 (thirteen) attributes that have large communalities (> 0.5). This can be interpreted that the twenty attributes used have a strong relationship with the factors formed. In other words, the greater the value of communalities, the better the factor analysis, because the greater the characteristics of the origin variable can be represented by the factors formed.

Total Variance Explained
Total Variant Explained explains the percent value of the variant capable of being explained by the number of factors formed. This value is based on the value of Eigenvalue. Eigenvalue values describe the relative importance of each factor in calculating the variance of the 20 variables analyzed.
The Eigenvalue value can be seen in the analysis results table (due to page limitations, the Total Variance Explained table is not displayed) in the initial Eigenvalue column (total column). The Eigenvalue for attribute/factor 1 is 5,703; Eigenvalue value for factor 2 is 1,269; the Eigenvalue value for factor 3 is 1,098; and so if we add it, the 20 Eigenvalue will be worth 20 (equal to the number of attributes). The magnitude of the variant capable of being explained by the new factor formed if we only take one factor is 35.633% (Cumulative Column). The size of the variant capable of being explained by new attributes/factors is formed if we take two factors (factor 1 and factor 2), namely 43.561% (Cumulative Column) and so on. In general, p-1412-3789 www.journalmabis.org e-2477-1783 30 the number of factors that must be taken is based on the value of Eigenvalue > 1, so in this case we take 3 attributes/factors, namely; attribute 1 (5,703), attribute 2 (1,269).
Still based on the Total Variant Explained table, especially in the Extraction Sums of Squared Loadings column and the Rotation Sums of Squared Loadings column; The proportion of the data that is explained by each component after rotation is seen more evenly than before rotation. Attributes/Factors 1 explain the diversity of data with the largest proportion, namely 35,633 percent according to the extraction method with factor analysis (before rotation) and with factor analysis (after rotation). The diversity of initial data can be explained at 17,356 percent. Then for the second factor explain the diversity of initial data with the proportion of 7,928 percent according to the extraction method with factor analysis (before rotation) and with factor analysis (after rotation). The diversity of the initial data can be explained at 15,104 percent. Then for the third factor explained diversity by 6,861 percent before the rotation was carried out and rose to 13,497 percent after rotating. Whereas for the fourth factor, it explains the diversity of 5,773 percent before the rotation is carried out and rises to 10,239 percent after being rotated. The proportion of data that is more evenly distributed after rotation shows the uniformity of the initial data described by each factor to be maximum.

Plot Scree
Scree Plot is one alternative that can be used to help researchers determine how many factors are formed that can represent the diversity of variables. Scree plots explain the relationship between the number of factors formed with Eigenvalue values in the form of Graphs. If the curve is still steep, there will be instructions to add components. When the curve is sloping, there will be instructions for stopping the addition of components, although the steep/gentle slope is subjective to the researcher.

Figure 2. Scree plot of Relationship between the Number of Factors Formed
From the scree plot above, it can be seen that when one component is formed, the curve still shows steepness when there is the 2nd point. After passing the 2nd point, the curve line has begun to slope, getting to the right will be more sloping. From the explanation above, it can be concluded that there are three components or factors formed.

Factors that influence people's buying interest in Jambi batik in Jambi city
To find out the factors that influence people's buying interest in Jambi batik in Jambi city, we can see Table 3, the rotated component matrix. Rotated Component matrix is the value of factor loading of each variable. Loading factor is the magnitude of the correlation between the score factor and the variable After a factor rotation with the varimax method, a table is obtained as shown above, namely Rotated Component Matrix. There is a difference in the value of the variable correlation with each factor before (Raw) and after (Rescaled) rotating the varimax. It appears that loading rotated factors has given the intended meaning and each factor can be clearly interpreted. Regardless of the sign of loading factor (+/-), it is also seen that each variable only correlates strongly with one factor only (no correlation variable <0.5 in all three factors). Thus, it is more appropriate to use the loading factor that has been rotated because each factor has been able to explain the diversity of the initial variables correctly and the results are as follows; Thus, based on the table and description above, it can be concluded that the factors that influence people's buying interest in Jambi batik in Jambi city are; Comfortable to wear, design variations, filler ornaments, secondary colors/additions, always updating the model, safe to use, primary/main color, main ornaments, colors, durable, quality, patterns, have characteristics and special.

The most dominant factor influences people's buying interest in Jambi batik in Jambi city
To find out the most dominant factors affecting people's buying interest in Jambi batik in Jambi city by looking at Table 3 Rotated Component Matrix (a) and Table 4 Component Transformation Matrix, in Table 3 Rotated Component Matrix (a), the attribute that most dominantly influences people's buying interest in Jambi batik is attribute 8 (Comfortable to use) with a value = 0.801). Furthermore, to find out the most dominant factors affecting people's buying interest in batik Jambi by looking at  Transformation Matrix table, the correlation values found in the main diagonal are above 0,5, which is 0,599; -0,802; -0,843 and 0,859. This shows that the four factors formed are correct because they have a high correlation on the main diagonals.
Based on Table 4 Component Transformation Matrix above, it can be concluded, that the most dominant factor influencing people's buying interest in Jambi batik in Jambi city is at factor 1 with a value of 0,599.

Figure 3. Component Plot in Rotation Space
If each loading factor is plotted in 4 dimensions, it will appear in the chart component plot as above where the fourteen attributes are close together in an adjacent position. Instead the other six attributes move away from these fourteen attributes.
After the number of factors formed is known, then the next step is to name each factor formed. Factor 1 consists of; privileges, have characteristics, patterns / motifs, main ornaments, filler ornaments, primary / main colors, secondary colors / additions. Factor 2 consists of; Safe to use, quality, comfortable to wear and durable. Factor 3 consists of; always updating models, design and color variations .

Conclusion
Based on the results of the analysis above, it can be concluded that the factors that influence people's buying interest in Jambi batik in Jambi city are; Comfortable to wear, design variations, filler ornaments, secondary colors/additions, always updating the model, safe to use, primary/main colors, main ornaments, colors, durable, quality, patterns, have characteristics, privileges. While the most dominant influence on people's buying interest in Jambi batik is; comfortable to wear.
The results of this study at least produce several strategic implications: first, because there are as many as fourteen factors that influence people's buying interest in Jambi batik, strategic efforts are needed to increase people's buying interest. Second, there must be an effort that must be made so that there is an improvement in public interest in buying and using Jambi batik.
The suggestion are first, it is better for all parties involved from the regional government to make a new breakthrough in order to increase the interest of the Jambi community towards Jambi batik. Second, need to do a kind of benchmarking and/or collaboratation with other regions that have been successful in lifting their batik to national markets and international markets. Third, efforts are needed to improve the quality of Jambi batik products so as to increase public confidence in Jambi batik.