Petra Christian University

About: Petra Christian University is a education organization based out in Surabaya, Indonesia. It is known for research contribution in the topics: Population & Customer satisfaction. The organization has 2412 authors who have published 2893 publications receiving 10429 citations.

PENTINGNYA KARYAWAN DALAM PEMBENTUKAN KEPERCAYAAN KONSUMEN TERHADAP PERUSAHAAN JASA: (Suatu kajian dan Proposisi)

Abstract: Employee has important role in gaining success for the organization. Successful organization that is able to fulfill the consumer expectation. The Question ofhow consumer trusting all their expectation to the service organization still remains as an interesting question to be answered. Various previous researches, have been proved that trust is the key to maintain long term relationship between the organization and consumer. In this paper we propose that employee dimension has a role in forming consumer trust toward organization especially in service industry. Abstract in Bahasa Indonesia : Karyawan memiliki peran yang penting bagi keberhasilan organisasi. Organisasi yang berhasil adalah organisasi yang mampu memenuhi harapan konsumen. Namun bagaimana konsumen akan mempercayakan segala harapannya pada organisasi jasa masih menjadi pertanyaan yang menarik untuk dijawab. Berbagai riset trdahulu membuktikan bahwa kepercayaan merupakan kunci untuk mempertahankan hubungan jangka panjang antara organisasi dengan konsumen. Dalam kajian ini kami memproposisikan bahwa dimensi karyawan berperan dalam membentuk kepercayaan konsumen trhadap organisasi khususnya dalam bidang jasa. Kata kunci : jasa, karyawan, kepercayaan.

Taxpayer Compliance Model Based On Transparency, Ethics and Trust

Abstract: The effort to develop the taxpayer compliance model is an effective way to understand taxpayers’ motivation in paying tax, which affects tax-compliant behavior. This study uses transparency, ethics, and trust, as factors to predict taxpayers’ compliance. Based on this background, the study aims to test the role of trust and ethics in mediating the factors of transparency and tax compliance. The respondent of this research is Individual Taxpayers running a business in the sector of trade, services, and others. Structural Equation Modelling-Partial Least Square (SEM-PLS) is used to analyze data. Based on empirical data collected from a survey of 113 individual taxpayers in Surabaya, the result shows that transparency and ethics are factors that partially affect tax compliance. The result of the mediating effect also demonstrates that ethics and trust are capable of affecting the role of transparency to increase tax compliance. Taxpayers’ trust and ethical behavior will increase along with the government’s ability to create transparency while governing the tax system and government’s finance, which in return will influence taxpayer’s compliance. Upaya untuk mengembangkan model kepatuhan pajak menjadi cara efektif dalam memahami motivasi wajib pajak dalam membayar pajak yang berdampak pada perilaku kepatuhan pajak. Penelitian ini menggunakan faktor transparansi, etika, dan kepercayaan untuk memprediksi perilaku kepatuhan wajib pajak. Berdasarkan latar belakang di atas, penelitian ini bertujuan untuk menguji peran kepercayaan dan etika dalam memediasi faktor transparansi terhadap kepatuhan pajak. Responden penelitian ini adalah Wajib Pajak Orang Pribadi yang menjalankan usaha pada sektor perdagangan, jasa, dan lainnya. Structural Equation Modelling-Partial Least Square (SEM-PLS) adalah alat yang digunakan untuk menganalisis data. Berdasarakan data empiris yang di kumpulkan melalui survei terhadap 113 wajib pajak orang pribadi di Surabaya, hasil penelitian ini menunjukkan bahwa transparansi dan etika secara parsial merupakan faktor yang mempengaruhi kepatuhan pajak. Hasil uji mediasi penelitian ini menemukan bahwa etika dan kepercayaan mampu mempengaruhi peran transparasi untuk meningkatkan kepatuhan pajak. Kepercayaan dan perilaku etis wajib pajak akan meningkat seiring dengan kemampuan pemerintah menciptakan transparansi dalam tata kelola sistem perpajakan dan keuangan pemerintah yang kemudian berdampak pada kepatuhan wajib pajak.

A Proposal of Probability of Rough Event Based on Probability of Fuzzy Event

Abstract: Probability and fuzziness are different measures for dealing with different uncertainties in which they be able tob e combined and considered as a complementary tool. In this paper, the relationship between probability and fuzziness are discussed based on the process of perception. In probability, set theory is used to provide a language for modeling and describing random experiments. Here, as a generalization of crisp set, fuzzy set is used to model fuzzy event as defined by Zadeh. Similarly, rough set can be also used to represent rough event in terms of probability measure. Special attention will be given to conditional probability of fuzzy event as well as conditional probability of rough event. Their several combinations of formulation and properties are defined.

Multilabel land cover aerial image classification using convolutional neural networks

Abstract: Classifying the remote sensing images requires a deeper understanding of remote sensing imagery, machine learning classification algorithms, and a profound insight into satellite images’ know-how properties. In this paper, a convolutional neural network (CNN) is designed to classify the multispectral SAT-4 images into four classes: trees, grassland, barren land, and others. SAT-4 is an airborne dataset that captures the images in 4 bands (R, G, B, infrared). The proposed CNN classifier learns the image’s spectral and spatial properties from the ground truth samples provided. The contribution of this paper is three-fold. (1) A classification framework for feature extraction and normalization is built. (2) Nine different architectures of CNN models are built, and multiple experiments are conducted to classify the images. (3) A deeper understanding of the image structure and resolution is captured by varying different optimizers in CNN. The correlation between images of varying classes is identified. The experimental study shows that vegetation health is predicted most accurately by the proposed CNN models. It significantly differentiates the grassland vegetation from tree vegetation, which is better than other classical methods. The tabulated results show that a state-of-the-art analysis is done to learn varying land cover classification models.

Market Integration and Financial Crisis: New Evidence from Asian Paciic Markets

Abstract: We investigated the stock market integration among national equity indices in eight countries from the period of 1995 to 2009, which was then clustered into four sub-sample periods. The multivariate time series analyses were employed to observe the degree and the existence of the integration. We found a cointegrating vector in each of three sub-sample periods. Interestingly, in the 1997 inancial crisis, we found that there was no indication of cointegration relationship among the equity indices. The results of block causality tests and the accounting innovation analysis indicate that the short run dynamic interactions among the stock indices became more intense during the current inancial crisis, and that the U.S. stock market played dominant role in the regional markets. ");} // --> activate javascript