As in agriculture, fisheries sector faces long list of uncertainty and unsustainability in supply of the products. This is due to the great possibility of natural disaster and moral hazard by the actors in fisheries which lead to the instability of value chain on fisheries commodity from downstream to upstream. Thus, a study must be done in order to explore and minimize the disturbance of the stream of value chain in fisheries. This study aims to investigate the attributes playing big role on affecting value chain cooperation among actors in fisheries commodity in Kei Islands. Data mining is used on the study to determine factors playing major roles in smoothing cooperation in value chain of fisheries commodity, with 220 datasets obtained from actors in fisheries micro-enterprises in Kei Islands taken from August to November, 2019. The result shows that, on average, weights of four data mining techniques; namely support vector machine, fast large margin, logistic regression, naïve bayes and generalized linear model all appear to put management as the leading factor that contributes the most for the cooperation of value chain of fisheries commodity in Kei Islands. This finding implicates that management on all micro-enterprises of fisheries business in Kei Islands has to be the main focus, which is mainly related to basic knowledge on conducting cooperation and maintaining relationship among all actors in fisheries sector, therefore, NGO and local government need to step in and play role on educating all actors for better good governance of the business to obtain the great sustainability in the value chain of fisheries commodity in the region.

This research discusses an integer batch scheduling problems for a single-machine with position-dependent batch processing time due to the simultaneous effect of learning and forgetting. The decision variables are the number of batches, batch sizes, and the sequence of the resulting batches. The objective is to minimize total actual flow time, defined as total interval time between the arrival times of parts in all respective batches and their common due date. There are two proposed algorithms to solve the problems. The first is developed by using the Integer Composition method, and it produces an optimal solution. Since the problems can be solved by the first algorithm in a worst-case time complexity O(n2n-1), this research proposes the second algorithm. It is a heuristic algorithm based on the Lagrange Relaxation method. Numerical experiments show that the heuristic algorithm gives outstanding results.

In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the properties of Markov chains are fulfilled. In this case, the tweets that are received by followers only depend on the tweets from the previous followers. Knowledge Discovery in Database (KDD) in Data Mining is used to be research methodology including pre-processing, data mining process using homogeneous CTMC, and post-processing to get the influencers using visualization that predicts the number of affected users. We assume the number of affected users follows a logarithmic function. Our study examines the Indonesian Twitter data users with tweets about covid19 vaccination resulted in dynamic influencer rankings over time. From these results, it can also be seen that the users with the highest number of followers are not necessarily the top influencer.

This study is to analyze the influence of the quality of information on the decision to choose CNNIndonesia.com media either directly or through the mediation of trust variables. The tremendous growth of cyber media in Indonesia, followed by the development of online media, has made people more careful in choosing online media. Meanwhile, the use and gratification theory states that the most important role of media is to meet people's needs and motivations, how certain media are sought and selected to meet their needs. This study uses a survey method through a quantitative approach positivistic. The sample was determined by an accidental sampling technique with a sample of 115 respondents. Data analysis was performed using Partial Least Square analysis with the SmartPLS version 3 program. The data analysis shows that the quality of information has a significant effect on increasing trust in CNNIndonesia.com media, the quality of information has a significant effect in increasing the decision to choose CNNIndonesia.com media, and trust has a significant effect in increasing the decision to choose CNNIndonesia.com media. This study also found that the trust variable was able to mediate the effect of information quality on the decision to choose CNNIndonesia.com media.

The aim of this study is to determine stakeholder acceptance of the blockchain and to investigate a suitable model using a Technology Acceptance Model with specific reference to corporate governance through cryptography in solving decades of financial record-keeping problems. Stakeholders in corporate governance, namely customers, creditors, suppliers, communities, employees, owners, investors, trade unions and social activists, can benefit in different ways. Investors can benefit from buying equity at a lower price and selling it on a market with greater liquidity, but they will find it difficult to disguise their trades. This study argues that almost all aspects of corporate governance can be improved through the application of this technology, which results in greater transparency, increases liquidity, and lowers costs. Corporate governance will also be better because blockchain technology uses the concept of a distributed ledger which allows data to be distributed at every connected point in an efficient and accountable manner, so that all parties in the blockchain can exchange data in real time.

The goal of this research was to see how network site marketing (SNS marketing) affected marketing performance in terms of customer relationship management (CRM) and marketing capabilities. This research was conducted with a quantitative approach. The population in this study are all female entrepreneurs who use SNS marketing in Bali. The sample is 260 MSMEs taken by purposive sampling. The data will be analyzed descriptively and inferentially. The inferential statistic used is Structural Equation Modeling (SEM) based on variance, namely Partial Least Square (SEM PLS) with SmartPLS 3.0 program. The research findings are that SNS marketing use has a positive and significant effect on CRM capability and marketing capability, CRM capability and marketing capability have a positive and significant effect on business performance, CRM capability and marketing capability as partial mediation influences SNS marketing use on business performance. This research implies that it is expected to help MSMEs in making decisions regarding the use of SNS marketing.

Indonesia is a country dominated by rural areas. Addressing rural poverty is a priority of the Indonesian government work program and an effort to achieve the Sustainable Development Goals (SDGs). One of the actual programs dealing with poverty is a digital village which is implemented in a smart village ecosystem. Since 2018, Indonesia has initiated various pilots of smart village projects. The success of a smart village is closely related to citizen science. The purpose of this research was to build a citizen science prospect model for a smart economy in a smart village ecosystem using Structural Equation Model – Partial Least Square (SEM-PLS) approach. This study proposes a novelty of measuring villagers' readiness to build a smart economy in a smart village ecosystem based on the strength of community support. We propose an assessment of the prospect of developing a smart economy in a smart village through the citizen science level that integrates exogenous variables of community support for the environment, citizen character, empowerment, entrepreneurship, innovation, and the smart economy. The citizen science model towards a smart economy showed a high level of predictive relevance, which was 87,2%. The citizen science model towards a smart economy can also explain empirical data with a GoF value of 0,488. This research showed that the indicators of Information Communication Technology (ICT), ICT literacy, access to education and research and development (R & D) facilitation, motivation for smart villages, and innovation in villages were driven by family participation. The collaboration with the private sector, local government, and communities drive the village's smart economy. The SEM PLS approach has not been widely used in research on the smart village component, especially the relationship between citizen science and the smart economy. Therefore, this research can fill the gap in smart village research, which is still dominated by a descriptive approach.

In online shopping, it is currently an alternative place for shopping where this method is starting to be widely used by consumers. Various online shopping applications have sprung up, but several factors that influence consumer shopping decisions of course vary. In this study, researchers examined the effect of the accepted model of technology (ease of use and usefulness) and risk variables on consumer decisions to shop at online stores. In this study, the researcher used four variables, sixteen dimensions where each dimension was represented by two indicators so that in this study there were thirty-two indicators which would later be changed in the form of questions to respondents. In this study, the population used is consumers who have shopped online and since the population is very large, then with the quota sampling method the researchers determine the number of samples as much as five times the number of indicators so that the number of samples is 160 respondents, which would later be processed with AMOS SEM analysis tools. From the results of this study, it was found that the variables of ease of use, usefulness and risk had a significant and significant effect on consumer decisions to buy online. And the ease-of-use variable also affects the usefulness variable. The usefulness variable is found to have the greatest influence on consumer decisions, then the risk variable and finally the ease of use.

Small industries tend to achieve marketing performance harder than their bigger counterparts, constrained by limited resources when compared to large businesses, especially during the Covid-19 pandemic. These constraints seem to still be relatively difficult to find a way out and result in low marketing performance including small industries in Denpasar. The purpose of the study is to explain the influence of entrepreneurial personality on marketing performance and to investigate the role of digitalization of marketing as a moderation of the influence of entrepreneurial personality on the marketing performance of small industries in Denpasar. The subject of the study was a small industry in Denpasar, represented by the owner / manager as a source. The sample size was set at 150 respondents. Analysis techniques use Moderated Regression Analysis (MRA). The results found that entrepreneurial personality has a significant influence on marketing performance, and digitalization of marketing acts as a quasi-moderation of the influence of entrepreneurial personality on the marketing performance. Small industries should be more active in exploring paid online media since it has a wider reach, such as existing market places or utilizing government-provided facilities, be careful about setting production targets and setting targets for special forces on marketing performance.

This study investigates the application of the technology acceptance model (TAM) on the digital payment using social media platforms with the extended inclusion of perceived ease of use, perceived security, perceived usefulness, and trust in enhancing consumer behavioral intention. This work has surveyed 250 consumer films on the digital social media platform. Data collection used a questionnaire designed with a five-point Likert scale. The questionnaire was created using a Google Form, and questionnaire distribution was performed by sending the link through social media to the respondents. As many as 300 questionnaires were distributed, and 258 questionnaires were considered valid for further analysis. Data analysis used smartPLS software version 3.0. The result revealed that nine hypotheses were empirically supported while the others two were not supported. Perceived security directly affects trust and consumer behavioral intention. Perceived ease of use directly affects perceived usefulness and consumer behavioral intention. Perceived security indirectly influences consumer behavioral intention through trust and perceived usefulness. Furthermore, perceived usefulness directly affects trust and consumer behavioral intention. Besides, trust directly affects consumer behavioral intentions. Perceived ease of use indirectly affects behavioral intention through perceived usefulness. Moreover, perceived security affects consumer behavioral intentions indirectly through trust. Perceived ease of use influences perceived usefulness. However, perceived usefulness did not indirectly influence behavioral intention through trust. Finally, perceived ease of use did not affect consumer behavioral intention through perceived usefulness and trust. These findings extended the application of the technology acceptance model in using digital payment platforms in Indonesia. These findings reinforced current research on user adoption of new technology. Furthermore, this result provides a managerial implication for digital payment platforms providers to improve consumer behavioral intentions.