Using the frameworks of the Theory of Use and Gratification (UGT) and the Unified Theory of Acceptance and Use of Technology (UTAUT2), this study explores the factors that influence individual behavior and behavioral goals in the adoption of digital banking. Partial Least Square-Structural Equation Modeling (PLS-SEM) is used in the analysis of research data using the program SmartPLS 3.2.9 professional. There are 432 people in the research sample that filled out questionnaires. The results show that behavioral intentions are strongly influenced by the integration of UGT-UTAUT2 by 60.3%. Performance and effort expectations are influenced by cognitive needs, effort expectations are influenced by affective needs, and social influence is impacted by social needs. Behavioral intentions for the use of digital banking are shaped by a combination of factors such as price value, hedonic motivation, habits, facilitating conditions, and effort expectations. The relationship between behavioral intentions, affective and cognitive needs is mediated by effort expectations. In the context of using digital banking, habits and behavioral intentions are important factors that influence behavior; in contrast, cognitive needs, affective needs, performance expectations, and social influence have no direct effect on behavioral intentions.

In the digital era the research study discusses the role of government policy, negative emotions and digital trust in cyber violence, therefore this research adds to the literature and provides references regarding the important role of government policy on cyber violence is very limited. This research aims to investigate the relationship between digital distrust and cyber violence, and the relationship between government policy and cyber violence. The research method used in this research is associative research. Associative research is research that aims to determine the relationship between the hubs of two or more variables. In this way, we can build a theory that functions to predict and control a phenomenon. The population in this study were all students who had studied using e-learning or digital platforms. In this study, the number of respondents was 543 high school students throughout Indonesia. The sampling technique used in this research is nonprobability sampling. In this research, the data collection method used was the questionnaire method. The instrument used to measure this research variable is a 5-point Likert scale. Data processing in this research uses SmartPLS software. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research are that digital distrust has a positive and significant relationship to cyber violence, negative emotions have a positive and significant relationship with cyber violence, and government policy has a positive and significant relationship with cyber violence. This research adds to the literature and provides references regarding the important role of government policy, digital distrust, and negative emotions in cyber violence. Indonesia, the government needs to implement and evaluate new regulations related to cybercrimes. The government must establish new regulations to combat cybercrime.

The IoT ecosystem faces increasingly complex security challenges due to the rapid growth of global IoT devices. Security risks related to device identification and credential compromise are on the rise, especially with the proliferation of IoT devices in various aspects of life. This research highlights the need to address these vulnerabilities through the development of robust security protocols, aiming to create a more secure IoT ecosystem and enhance user trust in this technology. The objective of the research is the development of an innovative IoT security protocol; High-Accuracy Device Identification and Resilience Against Credential Compromise (HADIRACC). This paper contributes significantly to enhancing the security and reliability of the IoT ecosystem. The research methods employed encompass the development of security protocols, the development of a proximity-based solution, and the classification of IoT devices using data processing techniques and machine learning-based classification. This study involves the collection and pre-processing of datasets, training different classifiers using 70% of the dataset, and testing the classifiers using the remaining 30%. The proposed protocol can effectively enhance the security of IoT devices by addressing various scenario-based attacks. Furthermore, the results of the analysis of the five classifiers used in this study indicate that Random Forest has the highest F1 score accuracy, reaching 88.8%. This suggests that Random Forest, as a classifier, can make the most accurate predictions compared to other classifiers.

In recent years, E-Commerce has experienced a very significant increase. E-commerce provides a broad overview of technology, processes and practices that can be carried out without using paper as a means of transactions. E-commerce can be a solution to the paper waste problem which is an environmental issue that can lead to social problems. Thus, e-commerce has a vital role in achieving business sustainability performance. E-commerce has had a big influence on the social and economic growth of today's society. Business management's ability to manage financial information is an important indicator in influencing Micro, Small and Medium Enterprises’ (MSME's) business performance. Good managements’ financial literacy equips MSMEs with knowledge and skill empowering MSMEs to make informed financial decisions, manage resources effectively and promote sustainable development. This research aims to analyze the relationship between E-Commerce and the sustainability performance of MSMEs and analyze the relationship between financial literacy and its positive and significant relationship with the sustainability performance of MSMEs. The research method uses a descriptive method with a quantitative approach. The population in this research are MSMEs managers in Indonesia who have comprehensive knowledge regarding the operations and performance of MSMEs. In this study, researchers used a simple random sampling technique with a sample size of 478 MSME managers. Data analysis in this research uses the Partial Least Square (PLS) technique which is an alternative method based on the variance of the variables used. The stages of data analysis are validity testing, reliability testing and hypothesis testing. The independent variables in this research are e-commerce and financial literacy, while the dependent variable is MSME sustainability performance. The results of this research show that e-commerce has a positive and significant relationship with MSME sustainability performance and financial literacy has a positive and significant relationship to MSME sustainability performance. In addition, e-commerce has a significant influence on the sustainability performance of MSMEs because the presence of e-commerce is one of the marketing alternatives used to reach more vendors and customers which can change the supply chain leads to social problem solution such as food distribution. Further, e-commerce may minimize traveling long distances for shopping resulting to the carbon footprint reduction. MSMEs have the same opportunity to use e-commerce as an alternative to maximize performance. However, not all MSMEs have the capability to use and utilize e-commerce optimally. After all, knowing good financial management will make it easier to make sustainable decisions since the higher the level of financial literacy, the MSME players can optimize their sustainability performance.

This research aims to investigate the role of internet marketing, word-of-mouth and brand awareness on purchasing decisions in online stores. The respondent sampling technique used in this research is a non-probability sampling technique, which uses a purposive sampling technique. The responses to this research were from 468 online store consumers. Measurements of “Internet Marketing”, “Word of Mouth Communication”, “Brand Awareness” and “Purchasing Decisions” were carried out using a seven-point Likert scale, ranging from strongly agree (1) to strongly disagree (7). In this research, the data was analyzed using the Partial Least Square (PLS) method with SmartPLS version 3.0 software. The stages of research data analysis are outer model testing, namely unified validity and reliability, inner model testing and hypothesis testing. Based on the results of data analysis, it is concluded that internet marketing, word-of-mouth and brand awareness had positive and significant effects on purchasing decisions. Better internet marketing will improve consumer purchasing decisions, brand awareness plays an important role in consumer purchasing decisions, and consumers will carry out word-of-mouth activities and tell other people about consumer experiences after consuming products, electronic word of mouth can help consumers in making buying decisions. Based on the results of data analysis, the study provides managerial implications as follows: online stores should evaluate the Internet marketing strategy used by the company by looking for information about what is currently trending among the public and forming a special team to carry out Internet marketing strategies to make them more attractive and creative and provide more complete information regarding products are marketed so that they attract consumers to make purchasing decisions.

This study aims to identify the factors that contribute to the formation of Net interest income (NII) for commercial banks in Indonesia in the short and long-term using the Vector Error Correction Model (VECM). The results showed that in the short term all variables in each period tend to adjust to achieve long-term balance. In the short term, the variables that affect NII are credit and NPL of large and retail trade, construction credit, transportation credit and NPL warehousing and communication, as well as lending rate facility. While in the variable length figures that affect NII are credit variables and NPL large and retail trade, Credit and NPL Transportation, warehousing and communication, other credit and Third-Party Funds (Deposit) collected. The analysis of Impulse Response Function can be proven that NII most quickly achieves stability when dealing with the shocks of large trade and retail NPL. Meanwhile, in the Forecasting Variance Decomposition analysis, it can be concluded that the variable that gives the greatest contribution to NII is the amount of construction credit.

This study discusses the variables that can determine the growth of bank credit in Indonesia. The selected independent variables are the control of third-party funds and operating costs on credit growth. The analytical method used is multiple regression with Probit analysis to see the lag-1 and lag-2 data categories. The results obtained that the Control of Third Parties Funds and Operational Costs on Credit Growth obtained significant results according to the simultaneous hypothesis testing. It means that the third-party funds and the operating costs affect credit growth. Meanwhile, the third-party funds partially influence the dependent variable, namely credit growth. Finally, the operational costs partially influence the dependent variable, namely credit growth.

This research aims to find out the significant difference between added value on sustainable competitive advantage and unsustainable competitive advantage of Islamic banks in Indonesia. The population in this study is Islamic banking units in Indonesia, the sampling technique used purposive sampling and the data is used from annual financial reports from 2015 to 2019. The results of this research support the resource-based theory that companies that can maintain their competitive advantage have added value and can also manage their strategic assets in the form of VRIN (Valuable, Rare, Inimitable, non-substitutable) more efficiently. The results also indicate that companies that can maintain competitive advantage are those that can provide added value for the stakeholders. The test results support the RBT hypothesis, as evidenced by the finding that it is possible to use VRIN assets to offer added value for stakeholders.

This research examines the effects of role conflict and role ambiguity on internal auditor's work stress and the quality of audit recommendations. These relationships were tested based on the survey taken from 96 internal auditors who served at several state universities in Indonesia. The hypothesis testing technique used SmartPLS analysis. The results showed that role conflict has a positive effect on the quality of audit recommendations while role ambiguity has a negative effect. Role conflict and role ambiguity have a positive and significant effect on work stress. Other test results show that internal auditor work stress does not show an effect on the quality of audit recommendations. The practical implication of this research is that to reduce ambiguity in carrying out audit tasks and to improve the quality of audit recommendations, it is necessary to consider an adequate work environment, especially the availability and adequacy of information needed by internal auditors in completing monitoring tasks. The role of conflict due to the presence of more than one task can cause work stress, although it does not interfere with the quality of audit recommendations. Therefore, it is necessary to pay attention to the allocation of work time that is not carried out at the same time so that the workload causes work stress.

This paper characterizes the routing problems arising in distribution of rice-for-the-poor in a district and presents a generic mathematical formulation of vehicle routing problems (VRP) for solving the problems. The proposed generic model, framed as a mixed integer linear programming, is formulated in such a way to encompass three distinct features; namely multiple depots (MD) establishment, multiple trips (MT) transportation, and split delivery (SD) mechanism. This model is implemented for a real-world problem of rice-for-the-poor distribution in the Ponorogo district of Indonesia, involved for deliveries among 3 depots—8, 17, and 23 villages depended on the distribution period—using a fleet of 5 vehicles of homogeneous capacity. Three types of distribution model are identified as MD-MT-VRP, MD-VRP-SD and MD-MT-VRP-SD.