Today's Information Systems Research Articles

A Taxonomy of SETA Methods and Linkage to Delivery Preferences

Cybersecurity threats targeting users are common in today's information systems. Threat actors exploit human behavior to gain unauthorized access to systems and data. The common suggestion for addressing this problem is to train users to behave better using SETA programs. The notion of training users is old, and several SETA methods are described in scientific literature. Yet, incidents stemming from insecure user behavior continue to happen and are reported as one of the most common types of incidents. Researchers argue that empirically proven SETA programs are needed and point out focus on knowledge rather than behavior, along with poor user adoption, as problems with existing programs. The present study aims to research user preferences regarding SETA methods, with the motivation that a user is more likely to adopt a program perceived positively. A qualitative approach is used to identify existing SETA methods, and a quantitative approach is used to measure user preferences regarding SETA delivery. We show that users prefer SETA methods to be effortless and flexible and outline how existing methods meet that preference. The results outline how SETA methods respond to user preferences and how different SETA methods can be implemented to maximize user perception, thereby supporting user adoption.

Future pHealth Ecosystem-Holistic View on Privacy and Trust.

Modern pHealth is an emerging approach to collecting and using personal health information (PHI) for personalized healthcare and personalized health management. For its products and services, it deploys advanced technologies such as sensors, actuators, computers, mobile phones, etc. Researchers have shown that today's networked information systems, such as pHealth ecosystems, miss appropriate privacy solutions, and trust is only an illusion. In the future, the situation will be even more challenging because pHealth ecosystems will be highly distributed, dynamic, increasingly autonomous, and multi-stakeholder, with the ability to monitor the person's regular life, movements, emotions, and health-related behavior in real time. In this paper, the authors demonstrate that privacy and trust in ecosystems are system-level problems that need a holistic, system-focused solution. To make future pHealth ethically acceptable, privacy-enabled, and trustworthy, the authors have developed a conceptual five-level privacy and trust model as well as a formula that describes the impact of privacy and trust factors on the level of privacy and trust. Furthermore, the authors have analyzed privacy and trust challenges and possible solutions at each level of the model. Based on the analysis performed, a proposal for future ethically acceptable, trustworthy, and privacy-enabled pHealth is developed. The solution combines privacy as personal property and trust as legally binding fiducial duty approaches and uses a blockchain-based smart contract agreement to store people's privacy and trust requirements and service providers' promises.

Supplier Evaluation at Small-Medium Enterprise Using Simple Additive Weighting

This study focuses on the importance of information systems in today's intensely competitive business landscape. Companies of all sizes rely on information systems to stay afloat, streamline operations, and make informed decisions based on accurate data. To remain competitive, a medium-sized company specializing in vending motorcycle accessories and spare parts faced various challenges, including determining the best supplier for each item. To address this issue, a decision support system was developed using the Simple Additive Weighting technique. This method calculates the weighted sum of performance evaluations for each option based on all qualities. The system underwent user acceptance testing and achieved a flawless success rate of 100%. Overall, this study highlights the crucial role of decision support systems in enabling businesses to make strategic decisions based on accurate and reliable data.

SISTEM INFORMASI UNIT KEGIATAN MAHASISWA DAN HIMPUNAN MAHASISWA JURUSAN POLITEKNIK NEGERI FAKFAK

Today's information systems are inseparable because they demand a company to create an integrated system that allows others to access the information they need from the company. The Student Activity Unit or UKM organization and the Departmental Student Association (HMJ) are two that are affected, making it simpler for students to obtain information, which is one of the most crucial requirements that must be met. Numerous student organizations are supervised by the Fakfak State Polytechnic and are grouped under the Student Activity Unit (UKM). Student activity units and major student associations at the Fakfak State Polytechnic currently do not have an integrated information system that explains management profiles, vision and mission, and work programs. This has an impact on the lack of information obtained by students and the public regarding UKM and HMJ at the Fakfak State Polytechnic. Therefore, efforts are needed to build and improve an information exchange system in the form of a website-based application for student activity units and departmental student associations that can manage information from each organization in an integrated manner to be able to overcome these problems. The information system that will be built and developed is a web-based application that makes it easier for users to access information and also acts as a promotional medium.

Application of Big data to configuration management in a PLM context

The emergence of information and communication technologies (ICT) in the early 1990s, particularly the Internet, made it easy to produce data and distribute it to the rest of the world. Today's business information systems contain data that is more massive, complex and heterogeneous. The increase in complexity, globalization and collaborative work mean that an industrial project (product design) requires the participation and collaboration of actors who come from several fields and workplaces. Information retrieval is an essential function for any information system. However, the latter is never easy as it always represents a major bottleneck for all organizations. In the environment of complex, heterogeneous and multi-use data, providing all users with easy and simple access to data becomes more difficult due to lack of technical skills or different user perspectives.
 PLM (Product Lifecycle Management) being a business strategy that aims to create, manage and share all the definition, manufacturing, maintenance and recycling information of an industrial product, throughout its life cycle. life, from preliminary studies to end of life and Big data, the collection of large data sets that are complex and difficult to analyze by traditional data processing methods.
 In this context, this article proposes to establish the main obstacles to the deployment of Big data in PLM systems (the collection of data from the PLM system, the storage and transfer of data in the PLM, the processing of data based on industrialization knowledge and experience, data security and visualization, etc.). The objective is to apply methodologies related to Big data to the management of product configurations (management of product diversity in connection with the development of mass customization (mass customization)).

Implementasi Algoritma Adaptive Huffman Code Dalam Kompresi File Teks Terenkripsi Algoritma Loki97

Data security and confidentiality is one of the most important aspects in today's information systems. Due to the rapid development of science and technology that allows the emergence of new techniques, which are misused by certain parties that threaten the security of the information system. The fall of information into the hands of other parties can cause harm to the owner of the information. Therefore we need a way that can provide security for the data, one of which is using cryptographic techniques. Cryptography technique is a science or art in fulfilling security aspects in communicating by changing the content of information into incomprehensible information. One of the algorithms that can be used is the Loki97 algorithm, which is a cryptographic algorithm that uses the Feistel network system. The process carried out in this study is to first encrypt the text file using the Loki97 algorithm, then the results of the encrypted file will be compressed using the Adaptive Huffman Code algorithm, resulting in an encrypted and compressed file.

Expected and Achieved Benefits of ERP Systems Implementation over Time

Today information systems are an inseparable part of all companies. This study deals with the non-financial implications occurring while implementing the enterprise resource planning software called AROP in 3 manufacturing companies being in different implementation phases. The work was based on semi-structured interviews, which were supplemented by a questionnaire survey with the management and the employees of the companies. The primary goal was to determine both the expected and the real impacts associated with the introduction of AROP software in the companies. The secondary goal was to determine satisfaction with AROP training in individual companies and to propose countermeasures. It was found that the company using AROP software in the full version confirmed a number of impacts that the companies had expected in the testing phase and in the phase just before the start of the testing phase. Examples of the confirmed impacts are following: merging all information into one system, obtaining previously unknown information or simplifying the work of employees. During the training, some weaknesses were identified, such as the length of the training or the form of the training. Therefore, several recommendations were proposed in order to streamline the implementation of AROP software and improve the training of this system.

Penerapan Algoritma Decision Tree C4.5 Untuk Memprediksi Kelayakan Calon Pendonor Melakukan Donor Darah Dengan Klasifikasi Data Mining

Based on data from UDD PMI Kampar Regency, many donors must have provisions to become blood donors. So far, blood donor selection has been made manually to determine whether potential donors can donate blood or not. Meanwhile, today's information system has not yet explored further information from the large amount of data stored as knowledge. There is a need for organizational consolidation and continuous evaluation of the performance that has been carried out by PMI in dealing with social and humanitarian problems. By making a data mining application with a classification method using the Decision Tree C4.5 Algorithm in predicting someone worthy or not to donate blood, it can be calculated from the results of variables that are continuous or critical, such as variables of age, body weight, hemoglobin (HB) levels, blood pressure. (systolic and diastolic), The data that enters the information system is calculated using the Decision Tree C4.5 Algorithm formula, which results in detailed results and can produce valid and more accurate values. With the data mining application using the Decision Tree Algorithm C4.5 method, potential blood donors' eligibility can be classified based on age, body weight, hemoglobin, and blood pressure. Hemoglobin with the highest gain value (0.861212618) is the variable that most determines blood donation success.

Theoretical approach to solving the problem of detecting malicious processes based on the analysis of the states of the entity of the information system

Today information systems of organizations operate in conditions of vulnerabilities and their exploitation by hackers. This is evidenced by the reports of global companies on the analysis of information on threats, as well as proposals for the implementation of appropriate cybersecurity measures. Despite the measures taken to ensure the cybersecurity of these systems, the number of identified vulnerabilities is constantly increasing. One of the ways to solve this problem is to monitor the security status of the functional components of information systems during data processing and exchange. The reasons for the occurrence of malicious processes in the functioning of information systems of organizations have been established. The main reason for the presence of vulnerabilities is the properties of the functional components of this information system. The analysis of existing methods for detecting intrusions into information systems of organizations is carried out. The application of the discovery method based on the analysis of protocol states makes it possible to determine and monitor the state of network, transport and application protocols that have state concepts. A theoretical approach to solving the problem of detecting malicious processes is proposed, based on the analysis of the states of the entity of an information system as part of the cybersecurity system of an organization's information system. The implementation of this theoretical approach will make it possible to correctly formulate and solve the problem of detecting malicious processes based on the analysis of the states of the entity of the information system in real time. And in the event of a change in security, the state of this entity, when it is affected by destructive non-target processes, react to such events and restore its safe state.

A Survey on Blockchain for Information Systems Management and Security

Blockchain technologies have grown in prominence in recent years, with many experts citing the potential applications of the technology in regard to different aspects of any industry, market, agency, or governmental organizations. In the brief history of blockchain, an incredible number of achievements have been made regarding how blockchain can be utilized and the impacts it might have on several industries. The sheer number and complexity of these aspects can make it difficult to address blockchain potentials and complexities, especially when trying to address its purpose and fitness for a specific task. In this survey, we provide a comprehensive review of applying blockchain as a service for applications within today’s information systems. The survey gives the reader a deeper perspective on how blockchain helps to secure and manage today information systems. The survey contains a comprehensive reporting on different instances of blockchain studies and applications proposed by the research community and their respective impacts on blockchain and its use across other applications or scenarios. Some of the most important findings this survey highlights include the fact that blockchain’s structure and modern cloud- and edge-computing paradigms are crucial in enabling a widespread adaption and development of blockchain technologies for new players in today unprecedented vibrant global market. Ensuring that blockchain is widely available through public and open-source code libraries and tools will help to ensure that the full potential of the technology is reached and that further developments can be made concerning the long-term goals of blockchain enthusiasts.

Privacy Is Dead - Solutions for Privacy-Enabled Collections and Use of Personal Health Information in Digital Era.

Today's digital information systems and applications collect every day a huge amount of personal health information (PHI) from sensor and surveillance systems, and every time we use personal computers or mobile phones. Collected data is processed in clouds, platforms and ecosystems by digital algorithms and machine learning. Pervasive technology, insufficient and ineffective privacy legislation, strong ICT industry and low political will to protect data subject's privacy have together made it almost impossible for a user to know what PHI is collected, how it is used and to whom it is disclosed. Service providers' and organizations' privacy policy documents are cumbersome and they do not guarantee that PHI is not misused. Instead, service users are expected to blindly trust in privacy promises made. In spite of that, majority of individuals are concerned of their privacy, and governments' assurance that they meet the responsibility to protect citizens in real life privacy is actually dead. Because PHI is probably the most sensitive data we have, and the authors claim it cannot be a commodity or public good, they have studied novel privacy approaches to find a way out from the current unsatisfactory situation. Based on findings got, the authors have developed a promising solution for privacy-enabled use of PHI. It is a combination of the concept of information fiduciary duty, Privacy as Trust approach, and privacy by smart contract. This approach shifts the onus of privacy protection onto data collectors and service providers. A specific information fiduciary duty law is needed to harmonize privacy requirements and force the acceptance of proposed solutions. Furthermore, the authors have studied strengths and weaknesses of existing or emerging solutions.

Top-Down Process Mining From Multi-Source Running Logs Based on Refinement of Petri Nets

Today's information systems of enterprises are incredibly complex and typically composed of a large number of participants. Running logs are a valuable source of information about the actual execution of the distributed information systems. In this paper, a top-down process mining approach is proposed to construct the structural model for a complex workflow from its multi-source and heterogeneous logs collected from its distributed environment. The discovered top-level process model is represented by an extended Petri net with abstract transitions while the obtained bottom-level process models are represented using classical Petri nets. The Petri net refinement operation is used to integrate these models (both top-level and bottom-level ones) to an integrated one for the whole complex workflow. A multi-modal transportation business process is used as a typical case to display the proposed approach. By evaluating the discovered process model in terms of different quality metrics, we argue that the proposed approach is readily applicable for real-life business scenario.

Managing digital infrastructures: negotiating control and drift in service provisioning

The digital infrastructure literature provides important perspectives on the intrinsic relations between information systems in today's organisations. However, little attention has been paid to the challenges involved in providing requisite digital infrastructure services to organisations. In this paper, we argue digital infrastructure service providers operate in highly complex and uncertain environments. Rather than adopting a traditional approach to control, providers must therefore continuously negotiate a balance between control and drift as two complementary strategies. Our argument is based on a retrospective longitudinal case study of a Swedish infrastructure service team within a large international firm. Using the encounter-episode process model as structuring principle and focusing on the tension between control and drift, we analyse the evolution of the provider's efforts to manage a portfolio of digital infrastructure services over a period of ten years. Based on these analyses, we uncover the involved complexities and dynamics, how control efforts and drift were constituted and how the infrastructure services were managed by continuously balancing control and drift. In conclusion, we relate the findings to extant literature to discuss new insights into provider management of digital infrastructure services.

Managing Digital Infrastructures: Negotiating Control and Drift in Service Provisioning

The digital infrastructure literature provides important perspectives on the intrinsic relations between information systems in today's organisations. However, little attention has been paid to the challenges involved in providing requisite digital infrastructure services to organisations. In this paper, we argue digital infrastructure service providers operate in highly complex and uncertain environments. Rather than adopting a traditional approach to control, providers must therefore continuously negotiate a balance between control and drift as two complementary strategies. Our argument is based on a retrospective longitudinal case study of a Swedish infrastructure service team within a large international firm. Using the encounter-episode process model as structuring principle and focusing on the tension between control and drift, we analyse the evolution of the provider's efforts to manage a portfolio of digital infrastructure services over a period of ten years. Based on these analyses, we uncover the involved complexities and dynamics, how control efforts and drift were constituted and how the infrastructure services were managed by continuously balancing control and drift. In conclusion, we relate the findings to extant literature to discuss new insights into provider management of digital infrastructure services.

Analytical Intelligence in Processes: Data Science for Business

The recent attention for Big Data illustrates that organizations are aware of the potential of the torrents of data generated by today's information systems. Despite increasing interest regarding to Big Data and analytics tools, to the best of our knowledge, there are no studies cover and classify the types of research being published specifically on analytical intelligence in processes associated with data science tools. As a first step towards bridging this gap, we carried out a systematic mapping to synthesize an overview of the area. We went through 351 papers on theme. Among them, 63 were related to analytical intelligence in processes and only 38 met the criteria for inclusion and exclusion of articles defined in this study. These 38 papers were selected and categorized according to their contribution. As a result, a chart of the area was developed and the most investigated topics were identified indicating that most studies focus on investigating how analytical intelligence in processes can be used to discovery, conformance checking, model repair and enrich, role discovery, bottleneck analysis, monitoring of events, frauds audit, predicting the remaining flow time, and recommending next steps.

True random bit generators based on current time series of contact glow discharge electrolysis

Random bit generators (RBGs) in today's digital information and communication systems employ a high rate physical entropy sources such as electronic, photonic, or thermal time series signals. However, the proper functioning of such physical systems is bound by specific constrains that make them in some cases weak and susceptible to external attacks. In this study, we show that the electrical current time series of contact glow discharge electrolysis, which is a dc voltage-powered micro-plasma in liquids, can be used for generating random bit sequences in a wide range of high dc voltages. The current signal is quantized into a binary stream by first using a simple moving average function which makes the distribution centered around zero, and then applying logical operations which enables the binarized data to pass all tests in industry-standard randomness test suite by the National Institute of Standard Technology. Furthermore, the robustness of this RBG against power supply attacks has been examined and verified.

The state-of-the-art of business process mining challenges

Business process mining is a new method that amalgamates business process modelling and analysis with data mining and machine learning techniques, whereby knowledge from event logs stored in today's information system is extracted to automatically construct business process models, identify bottlenecks, and improve the business processes. Since process mining has recently received attention among the research community, there are many challenges. The most important issues have been defined in the process mining manifesto. However, none of the published works investigated, or the defined challenges, have been solved and are still being encountered. Therefore, this paper provides a comprehensive and critical review of the literature in the context of process mining challenges. The contribution of this paper is to increase the maturity of the field of process mining by providing researchers with the state-of-the-art of the most important challenges of process mining.

The state-of-the-art of business process mining challenges

Business process mining is a new method that amalgamates business process modelling and analysis with data mining and machine learning techniques, whereby knowledge from event logs stored in today's information system is extracted to automatically construct business process models, identify bottlenecks, and improve the business processes. Since process mining has recently received attention among the research community, there are many challenges. The most important issues have been defined in the process mining manifesto. However, none of the published works investigated, or the defined challenges, have been solved and are still being encountered. Therefore, this paper provides a comprehensive and critical review of the literature in the context of process mining challenges. The contribution of this paper is to increase the maturity of the field of process mining by providing researchers with the state-of-the-art of the most important challenges of process mining.

Rule- and context-based dynamic business process modelling and simulation

The traditional approach used to implement a business process (BP) in today's information systems (IS) no longer covers the actual needs of the dynamically changing business. Therefore, a necessity for a new approach of dynamic business process (DBP) modelling and simulation has arisen. To date, existing approaches to DBP modelling and simulation have been incomplete, i.e. they lack theory or a case study or both. Furthermore, there is no commonly accepted definition of BDP. Current BP modelling tools are suitable almost solely for the modelling and simulation of a static BP that strictly prescribes which activities, and in which sequence, to execute. Usually, a DBP is not defined strictly at the beginning of its execution, and it changes under new conditions at runtime. In our paper, we propose six requirements of DBP and an approach for rule- and context-based DBP modelling and simulation. The approach is based on changing BP rules, BP actions and their sequences at process instance runtime, according to the new business system context. Based on the proposed approach, a reference architecture and prototype of a DBP simulation tool were developed. Modelling and simulation were carried out using this prototype, and the case study shows correspondence to the needs of dynamically changing business, as well as possibilities for modelling and simulating DBP.

A Study on the Conceptual Model for Service-Oriented Architecture based on Common Services

Recently, form of domestic industries is undergoing changes composite of goods and services and enlargement. These changes in the industry requires that react quickly to changes while still increasing the structural complexity of IT. Therefore, today's information system and a structure could lead to a small and simple components and structures that are continuous in a service-oriented integration needs, flexibility, integrity, reusability and the like is necessary. In this paper, we propose the application of these into one integrated IT in ways that reflect the structural changes service oriented architecture-based integrated business architecture model. These are business architecture with distinctive characteristics can bring the effect of such new business and agile response of the product, improving the consistency and flexibility of the business.