PEMBINAAN TEKNOLOGI INFORMASI DAN SISTEM OPERASIONAL BANK SYARIAH

Information technology is a knowledge that is always evolving from tools or communication which is a delivery of information through rapid communications, which relates to information problems in terms of all aspects ranging from data collection, data storage, data processing from information to the process of delivering information to people who need it. The purpose of fostering information technology and healthy internet use is an educational process by providing sufficient understanding of the current latest technology and being educated with the Islamic bank operating system, the owner of the fund invests his money so he can earn interest from the bank. If the profit sharing from the customer's funds is then distributed to those in need (eg venture capital), with a profit sharing agreement according to the agreement. Guidance on the Development of Information Technology and Bank Sariah Operational Systems at the Vocational High School Nang Nadim Batam to find out how to use good information technology and know the operating system of the Sariah bank. With this coaching, it is hoped that students will be helped in understanding the service that was carried out on January 15 and 16, 2019 at SMK Hang Nadim Batu Aji, Batam City.

Enhancing the Decision-Making Process through Industry 4.0 Technologies

In order to meet the increasingly complex expectations of customers, many companies must increase efficiency and agility. In this sense, Industry 4.0 technologies offer significant opportunities for improving both operational and decision-making processes. These developments make it possible to consider an increase in the level of operational systems and teams’ autonomy. However, the potential for strengthening the decision-making process by means of these new technologies remains unclear in the current literature. To fill this gap, a Delphi study using the Régnier Abacus technique was conducted with a representative panel of 24 experts. The novelty of this study was to identify and characterize the potential for enhancing the overall decision-making process with the main Industry 4.0 groups of technologies. Our results show that cloud computing appears as a backbone to enhance the entire decision-making process. However, certain technologies, such as IoT and simulation, have a strong potential for only specific steps within the decision-making process. This research also provides a first vision of the manager’s perspectives, expectations, and risks associated with implementing new modes of decision-making and cyber-autonomy supported by Industry 4.0 technologies.

Impact of Industry 4.0 on decision-making in an operational context

The implementation of Industry 4.0 technologies suggests significant impacts on production systems productivity and decision-making process improvements. However, many manufacturers have difficulty determining to what extent these various technologies can reinforce the autonomy of teams and operational systems. This article addresses this issue by proposing a model describing different types of autonomy and the contribution of 4.0 technologies in the various steps of the decision-making processes. The model was confronted with a set of application cases from the literature. It emerges that new technologies' improvements are significant from a decision-making point of view and may eventually favor implementing new modes of autonomy. Decision-makers can rely on the proposed model to better understand the opportunities linked to the fusion of cybernetic, physical, and social spaces made possible by Industry 4.0.

Detection of Network Attacks Based on Multiprocessing and Trace Back Methods

The way of thinking of traffic observing for discovery of system assaults is predicated on a “gained information” viewpoint: current methods recognize either the notable assaults which they’re customized to alarm on, or those strange occasions that veer off from a known typical activity profile. These philosophies depend on an expert structure which gives the ideal data, either with respect to “marks” of the striking attacks or as anomaly free traffic datasets, adequately rich to make delegate profiles for commonplace movement traffic. The theory talks about the limitations of current information-based system to recognize organize assaults in an inexorably unpredictable and advancing Web, Described by ever-rising applications and an ever-expanding number of most recent system assaults. In an oppositely inverse viewpoint, we place the weight on the occasion of solo recognition strategies, fit for distinguishing obscure system assaults during a unique situation with none past information, neither on the attributes of the assault nor on the gauge traffic conduct. In view of the perception that an outsized portion of system assaults are contained during a little division of traffic flows, the proposition exhibits an approach to join basic bunching strategies to precisely distinguish and portray malignant flows. to bring up the practicality of such an information autonomous methodology, a solid multi-bunching-based location technique is created and assess its capacity to recognize and portray arrange assaults with none past information, utilizing bundle follows from two genuine operational systems. The methodology is acclimated identify and describe obscure vindictive flows, and spotlights on the identification and portrayal of ordinary and notable assaults, which encourages the translation of results. When contrasted with the predominant DDoS traceback techniques, the proposed system has assortment of favorable circumstances—it is memory no concentrated, proficiently adaptable, vigorous against parcel contamination, and free of assault traffic designs. The consequences of inside and out test and reenactment considers are introduced to exhibit the adequacy and effectiveness of the proposed strategy. It’s an uncommon test to traceback the wellspring of Circulated Disavowal of-Administration (DDoS) assaults inside the Web. In DDoS assaults, aggressors create a lot of solicitations to casualties through undermined PCs (zombies), with the point of keeping ordinary help or debasing from getting the norm of administrations. Because of this fundamental change, the proposed system conquers the acquired downsides of parcel stamping strategies, similar to weakness to bundle contaminations. The execution of the proposed strategy welcomes no changes on current steering programming. Moreover, this work builds up a hypothetical structure for assessing the insurance of IDS against mimicry assaults. It shows an approach to break the wellbeing of 1 distributed IDS with these strategies, and it tentatively affirms the capacity of various assaults by giving a worked model. The Project is intended by using Java 1.6 as face and MS SQL Server 2000 as backside. The IDE used is Net Beans 6.8.

Nudging Drivers to Safety: Evidence from a Field Experiment

Driving is an integral component of many operational systems, and any small improvement in driving quality can have a significant effect on accidents, traffic, pollution, and the economy in general. However, making improvements is challenging given the complexity and multidimensionality of driving as a task. In this paper, we investigate the effectiveness of nudging to improve driving performance. In particular, we leverage a smartphone application launched by our industry partners to send three types of nudges through notifications to drivers, indicating how they performed on the current trip with respect to their personal best, personal average, and latest driving performance. We measure the resulting driving performance using telematics technology (i.e., real-time sensor data from an accelerometer, Global Positioning System (GPS), and gyroscope in a mobile device). Compared with the “no-nudge” control group, we find that personal best and personal average nudges improve driving performance by approximately 18% standard deviations of the performance scores calculated by the application. In addition, these nudges improve interaccident times (by nearly 1.8 years) and driving performance consistency, as measured by the standard deviation of the performance score. Noting that driving abilities and feedback seeking may vary across individuals, we adopt a generalized random forest approach, which shows that high-performing drivers who are not frequent feedback seekers benefit the most from personal best nudges, whereas low-performing drivers who are also frequent feedback seekers benefit the most from the personal average nudges. Finally, we investigate the potential mechanism behind the results by conducting an online experiment in a nondriving context. The experiment shows that the performance improvements are directly driven by the changes in participants’ effort in response to different nudges and that our key findings are robust in alternative (nondriving) settings. Our analysis further shows that nudges are effective when the variability in reference points is low, which explains why the personal best and personal average nudges are effective, whereas the last score nudge is not. This paper was accepted by Vishal Gaur, operations management.

“Racing” to the IBOR transition finish line

Purpose Summarize and review the key developments during 2021 relating to transition of the London InterBank Offered Rate (LIBOR) to alternative risk-free rates, in accordance with the guidance of global regulators and market participants. Design/methodology/approach Outlines and explains four key events to date during 2021 that are instrumental to the success of LIBOR transition, including the ISDA 2020 IBOR Protocol and Supplement, the 5 March 2021 announcements by ICE Benchmark Administration and the Financial Conduct Authority, the transition of interdealer swap conventions from LIBOR to SOFR, and the ARRC endorsement of the CME Group SOFR term rate. Findings The global adherence to the ISDA Protocol and Supplement, the successful launch of “SOFR First” and other “RFR First” swaps convention transitions, and the ARRC’s endorsement of CME’s SOFR term rate have given the market the clarity and tools that it needs to complete the transition away from LIBOR by the deadlines fixed by the 5 March 2021 benchmark transition event. Practical implications It now is clear that market participants globally have the resources to, and must, move to adopt alternative reference rates and related operational systems and other infrastructure to cease origination of new LIBOR-linked contracts after 31 December 2021. The ARRC’s endorsement of the SOFR term rate for business loans and related derivatives and securitizations is a critical positive development for the structured finance market. Originality/value Expert analysis and guidance from experienced finance lawyers.

DATA SOURCES FOR BUSINESS INTELLIGENCE

As organizations' desire for data grows, so does their search for data sources that are both usable and reliable.Businesses can obtain and collect big data in a variety of locations, both inside and outside their own walls.This study aims to investigate the various data sources for business intelligence. For business intelligence,there are three types of data: internal data, external data, and personal data. Internal data is mostly kept indatabases, which serve as the backbone of an enterprise information system and are known as transactionalsystems or operational systems. This information, however, is not always sufficient. If the company wants toanswer market and industry questions or better understand future customers, the analytics team may need to look beyond the company's own data sources. Organizations must have access to a variety of data sources in order to answer the key questions that guide their initiatives. Internal sources, external public sources, andcollaboration with a big data expert could all be beneficial. Companies who are able to extract relevant datafrom their mountain of data acquire new perspectives on their business, allowing them to become morecompetitive

The Effect of Technological Complexity (KT) and Compatibility (KOM) on The Sustainability of The Green and Smart Port Concept (CTU): TAM Extended Approach Case Study at Teluk Lamong Terminal, A Subsidiary of PT Pelindo III

This study examines and analyzes the relationship between the technological complexity (KT) and compatibility (KOM), to a continuance to use (CTU) of green and smart port concepts using TAM theory extended. Adding technological complexity and compatibility as an external factor into TAM in terms of perceived usefulness (PU) and perceived ease of use (PEOU) that affect continuance to use green and smart concepts. This study uses a survey method. It is distributed to owners/operational/invoicing managers of Terminal Teluk Lamong (TTL) Customers (Shipping Company, Forwarding, Trucking Company) in Surabaya, Indonesia. The sampling technique is using Slovin's formula with 304 respondents. The data analysis technique uses SEM (Structural Equation Modelling) with SMART PLS 3.0. Both KT and KOM have a significant effect on PU and PEOU. Both PU and PEOU have a significant effect on CTU, and PEOU has a significant effect on PU. This research was conducted at TTL, the only terminal in Indonesia that uses the green and smart port concept. There is no comparison with other terminals in Indonesia on the implementation of the green and smart port concept. Especially for shipping companies, respondents cannot reach owner/principal/shareholders due to Indonesian government policy that international Shipping Companies are not allowed to open branches independently. However, they have to cooperate with local companies (agents). Port Industries (TTL) can develop an appropriate marketing strategy based on this research's results. Technological complexity and compatibility have a significant effect on the continuance to use GSP. Management of TTL has to consider technology and operational systems development with a low-level complexity and according to customer's needs. This research contributes to enrichment and extending TAM theory in terms of green and smart port concept sustainability. Not only affected by PU and PEOU but technological complexity (KT) and Compatibility (KOM) factors are important.

Design of a Data Management Reference Architecture for Sustainable Agriculture

Effective and efficient data management is crucial for smart farming and precision agriculture. To realize operational efficiency, full automation, and high productivity in agricultural systems, different kinds of data are collected from operational systems using different sensors, stored in different systems, and processed using advanced techniques, such as machine learning and deep learning. Due to the complexity of data management operations, a data management reference architecture is required. While there are different initiatives to design data management reference architectures, a data management reference architecture for sustainable agriculture is missing. In this study, we follow domain scoping, domain modeling, and reference architecture design stages to design the reference architecture for sustainable agriculture. Four case studies were performed to demonstrate the applicability of the reference architecture. This study shows that the proposed data management reference architecture is practical and effective for sustainable agriculture.