The purpose of this study is to investigate the relationship between data skewness in the output variable and the accuracy of artificial neural network predictive model. The artificial neural network predictive model is built using multilayer perceptron and consist of one output variable and six input variable, and the algorithm used is back propagation. Data used in this study is generated by conducting the simulations in 1000 cycles. Three categories of skewness used in the output variables are positive skewness, neutral, and negative skewness. The results show that data skewness does not have a significant effect on the accuracy of the artificial neural network predictive model. These results imply that artificial neural network predictive model has a higher capability to cope with skewed data due to its complexity in the hidden layer.
Supply chain in textile industry requires an involvement of several other related industry therefore it divide into several sub-sector industry. The market dynamic and complexity of supply chain network are causing problem. This study aims to classify the market base on consumers behaviour through their preferences in textile product in East Java. Analysis of data using data mining approach. Algorithm K-means type clustering is use as clustering methods by integrating with Customer Relationship Management (CRM) concept. The simulation result of data set using five cluster depends on their variability value are Lumajang, Malang, Madura, Tulungagung, and Ponorogo. The clusters formed have the highest importance predictor in "way of purchase" and the lowest in "purchase flexibility". The result in this study is generally indicate that consumers of textile products in East Java prioritize values in customer value compared to product quality.
Abstrak: Tujuan penelitian ini menguji ketahanan luntur zat warna tekstilbatik yaitu reaktif dan azo pada uji pencucian menggunakan SNI ISO 105-C06: 2010 dan uji keringat pH asam dan pH basa menggunakan SNI ISO 105-E04: 2015 dengan penyesuaian DSTI. Sampel uji untuk zat warna reaktif adalah material katun dan sampel uji azo menggunakan sutera sebagai bahan baku utama untuk produk batik di Jawa Timur. Nilai perubahan warna dan penodaan warna dievaluasi pada konsentrasi larutan yang berbeda sesuai standar uji masing-masing. Hasil penelitian menunjukkan bahwa perbedaan konsentrasi larutan zat reaktif tidak menyebabkan perbedaan yang nyata pada skor perubahan warna dan perbedaan warna katun untuk semua pengujian. Sementara konsentrasi larutan zat azo yang berbeda menyebabkan perbedaan yang nyata pada skor perbedaan warna untuk pengujian sutera.Kata-kata Kunci: reaktif, azo,ketahanan luntur, pencucian, keringat Abstract: Colour Fastness Properties of Reactive and Azo Resistance on Batik Dyestuff for Small Enterprises in East Java.The study aims to test reactive and azo dyestuff base on colour fastness of washing based on SNI ISO 105-C06:2010 and perspiration on pH acid and pH alcaline based on SNI ISO 105-E04:2015 adjusted with DSTI. The testing sample for reactive substance is cotton and the testing sample for azo is silk, main raw material of batik used in East Java. Colour change and stains are evaluated on different concentrations of the solution according to each standart. The results show that different concentration of reactive solutions do not cause a significant different on colour change and cotton stain for all testing samples. On the other hand, different concentrations of azo solutions cause a significant difference on silk stains.
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