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Proper decision-making in a company requires a company to make decisions quickly, precisely, and relevant to the problem at hand. The ability to examine problems encountered necessitates the use of data from all areas of an organization. These data will be the basis for decision-making. Due to the significance of these data, data warehouse (DW) and analytics and business Intelligence (ABI) are necessary form of information technology. The DW and business intelligence requirements for each organization differ based on the industry. As a result, this case study of the Bedstead manufacturers intends to build a blueprint of the DW and ABI that can be used as the basis and reference in the future by this company and similar companies in creating DWs and business intelligence.

The purpose of this work is to develop and implement a disaster recovery plan (DRP) in stock exchange industry in Indonesia, in order to perform a system recovery in the event of a disaster. To develop a DRP, there are several steps that must be performed as a risk analysis to determine how much risk the company would receive when a disaster occurs, business impact analysis to identify critical business units and necessary resources for the recovery process to run smoothly, to identify recovery strategies to be used as a backup method and recovery site, the recovery procedure that needs to be done in order to make the recovery process run properly, testing and review, and documentation of the DRP. Based on the results of tests that have been done, the development of DRPs can be implemented at stock Exchange industry in Indonesia. With the DRP, the company is expected to have a plan to prepare for and recover resources and information systems in order to be able to walk back in the event of a disaster in order to minimize losses to the company.

Websites must assure web server availability in light of the worldwide increase in internet users. Web server monitoring is the process of examining web application server utilization by showing data in the form of statistics or graphs. Data about web server use will help server owners make decisions about server availability. The purpose of this study is to create a web monitoring program capable of retrieving and storing data from Java application server resources. The research methodology utilized in this study is divided into two phases: data gathering and software development. The data gathering step includes doing a literature study, conducting a survey, distributing questionnaires, and analyzing comparable apps. The development phase employs the waterfall methodology. The outcome of this study is a web application that can monitor the Java application server’s resource use and send email alerts when resource usage becomes excessive. To summarize, web application server monitoring may be utilized to alleviate developer workload.

XYZ is a company engaged in the port sector. To support the company’s business processes, XYZ uses two applications to carry out operational activities, namely the CARTOS application to manage invoices and the Finance application to record company costs and revenues. To produce a cost accounting report, XYZ is still processing and visualizing it manually with data sources from the two applications mentioned earlier. This resulted in quite a long time processing data into information. So that reporting to management cannot be done in real time. Therefore XYZ needs a system that can help management to analyze and manage data into information in real time. The Business Intelligence (BI) method is one of the solutions for company needs, especially in analyzing and providing access to data to help make better decisions.

This research aims to develop an integrated information system for pharmaceutical companies in Indonesia, which has separate business units in two different locations. An Integrated System is needed to provide the value of competence in the technology and information systems that companies use in their business processes. The development stage starts from the assessment and understanding of the current situation both in the business environment and the IS/IT environment. The business environment includes the internal business environment and external business environment.Similarly, the IS/IT environment which includes internal and external IS/IT environments. With a deep understanding of current conditions, it can be determined the Information System(IS) strategy, Information Technology(IT) strategy and future IS/IT strategies. This study reveals the following results: The absence of good system integration with the business units involved makes the company in a weak position. But in terms of opportunity is quite high so that the use of technology and information systems that fit business needs is recommended in this study. The results of this study recommends some applications that can solve problems commonly experienced by companies such as system integration and business process automation to achieve more efficient and effective business processes.

This study is aimed to analyze success of the Enterprise Resource Planning (ERP) System Merging in Chemical Company Singapore that acquired two companies. The success component of ERP system success is using DeLone and McLean success model with qualitative method. The research methodology used detail interview with project implementation team, ERP consultants (8 informants) to get more detail from ERP system merging with information and collected supporting data from the ERP system itself. The result shows that ERP System Merging succeed to increase the system quality of Chemical Company which acquired two companies into one ERP system. It was depicted by the increment of easiness on using the system. The information much more integrated and accurate after the ERP system merging. Meanwhile service quality was increased because of all incidents now monitored in one efficient log system and handled by experienced IT application support team.

The implementation of an information system that supports company goals is the main strategy of an organization. But aligning business strategies with information system(IS) and information technology(IT) is not as easy as it seems, because there are several gaps of strategies between upper level and practical level. Often the focus in system development is only on the architecture of the future system, even though the study says that the engineering model of needs is the most important thing in the process of developing the company’s system. PT. SBS is a distributor and supplier company. Along with the development of its business, business processes also become more complex. The information system that was originally felt to be sufficient is considered to be no longer optimal so that it often results in delays in delivery with a fairly large percentage. Therefore, an Enterprise Resources Planning(ERP) system will be developed but it must be ensured that the business processes used are oriented towards organizational goals. The purpose of this study is to introduce and explain the stages of the Organization Goal-Oriented Requirement Engineering (OGORE) method as a requirement engineering method in a company’s business processes that focuses on organizational goals. The research method was done by collecting business process data and defining key performance indicators(KPIs) in a small discussion group with stakeholders in the company. The results of this method were Goal Tree Model (GTM) diagrams which was then used as a reference in describing new business processes and in preparing the requirements specification documents. The conclusion obtained that the stages of the OGORE method are able to eliminate needs according to the organization’s goals. It is also recommended to use the OGORE method as one of the requirements management steps in the Enterprise Architecture method to create new method as an agenda for the future.

In recent years, neural networks have attracted much attention in the machine learning and the deep learning technologies. Bio-inspired functions and intelligence are also expected to process efficiently and improve existing technologies. In the visual pathway, the prominent features consist of nonlinear characteristics of squaring and rectification functions observed in the retinal and visual cortex networks, respectively. Further, adaptation is an important feature to activate the biological systems, efficiently. Recently, to overcome short-comings of the deep learning techniques, orthogonality for the weights in the networks has been developed for the signal propagation and the efficient optimization of the learning. In this paper, bio-inspired asymmetric networks with nonlinear characteristics are proposed, which are derived from the retinal networks in the biological visual pathway. The asymmetric network proposed here was verified to detect the movement of the object, efficiently in our previous studies. This paper shows a new characteristic of the adaptive orthogonality in the asymmetric networks. First, it is shown that the asymmetric network with nonlinear characteristics is effective for generating orthogonality. Second, the proposed asymmetric network with Gabor filters is compared with the conventional energy model from the point of the orthogonality characteristics. Finally, the asymmetric networks with nonlinear characteristics can generate the extended orthogonal bases in independent subspaces, which are useful for classification and efficient learning. [ABSTRACT FROM AUTHOR]

Generation of useful variables and features is an important issue throughout the machine learning, artificial intelligence, and applied fields for their efficient computations. In this paper, the nearest neighbor relations are proposed for the minimal generation and the reduced variables of the functions in the threshold networks. First, the nearest neighbor relations are shown to be minimal and inherited for threshold functions and they play an important role in the iterative generation of the Chow parameters. Further, they give a solution for the Chow parameters problem. Second, convex cones are made of the nearest neighbor relations for the generation of the reduced variables. Then the edges of convex cones are compared for the discrimination of variables. Finally, the reduced variables based on the nearest neighbor relations are shown to be useful for documents classification. [ABSTRACT FROM AUTHOR]

XYZ is a company engaged in the port sector. To support the company's business processes, XYZ uses two applications to carry out operational activities, namely the CARTOS application to manage invoices and the Finance application to record company costs and revenues. To produce a cost accounting report, XYZ is still processing and visualizing it manually with data sources from the two applications mentioned earlier. This resulted in quite a long time processing data into information. So that reporting to management cannot be done in real time. Therefore XYZ needs a system that can help management to analyze and manage data into information in real time. The Business Intelligence (BI) method is one of the solutions for company needs, especially in analyzing and providing access to data to help make better decisions. This study discusses the design and implementation of business intelligence solutions ranging from architecture, data warehouse, ETL processes and visualization in the form of a dashboard in accordance with the needs of XYZ. The method used in developing business intelligence dashboards refers to the executive information system life cycle method which consists of justification, planning, business analysis, design, construction, and dissemination. The results of this research are dashboard visualization using the Power BI tool that displays information and knowledge needed in the monitoring process and becomes material to produce management decisions related to cost accounting reports. [ABSTRACT FROM AUTHOR]

Implications of sensor technology on new product introduction requires critical decisions on divergent marketing and operational aspects. In this paper, we employed the Bass model for a new product that used the sensor technology diffusion from the perspective of the Wagner-Whitin lot-sizing model which discusses this matter related to suitability of sensor technology on the market and operational dimensions. The objective of this study is to propose an uncertain fuzzy approach to specify the new product that applied the sensor technology introduction's optimum time, price, production scheduling, and rate simultaneously. This model will be applied to analyze the impact of sensor technology diffusion on the market acceptance and some operational parameters, for instance, total customer population, price elasticities, startup and maintenance costs, the unit's variable cost and research and development costs on optimized benefit, and the product's optimized lifespan. In this experiment, we have inspiration from the version of the Sale et al. (2017) model which considers uncertainty by using fuzzy triangular numbers and performing the alpha cut method. Moreover, in this research, variable cost is considered as a Cobb-Douglas function. Initially, in Research Methodology, mathematical modeling is applied, wherein utilizing simulation and the experimental design method, data were generated. Eventually, using LINGO optimization software, the problem was solved, and for further examinations considering the existence of various parameters, design of experiment (DoE) by Design-Expert 8 software and response surface methodology was adopted to analyze and optimize the problem's parameters. The results indicated that the objective function's climax occurs when the higher limit of alpha being 0.7 is assumed; hence, the optimum state of demand belongs to this amount of alpha. [ABSTRACT FROM AUTHOR]

P systems with mitochondria enzymes layer computing is a recent version of P systems; it integrates a new feature inspired from the enzymes gate of a natural cell to the cell-like P systems. The model of a computational layer is well known as a problem of Non-Deterministic (NP-complete) in polynomial time. In this paper, we propose a P systems with enzymes to solve one of the most NP-hard problems, which is the determination of the maximal clique in a given undirected graph. In this context, the evolution strategy proposed is based on using objects under the control of enzymes placed on layers. [ABSTRACT FROM AUTHOR]

The Intelligent agent technology has been developing and makes a contribution to efficient trading of items. In this article, we define a hybrid trader as a type of new user who behaves as both the buyer and the seller. Also, we analyze the trading models and develop a trading mechanism. In the volume-discount trading scheme, hybrid traders form coalitions to purchase items, because a coalition has a greater budget for purchases than a single hybrid trader does. Therefore, we create an incentive for coalitions by using a side payment policy and propose a decision-making method for efficient side payment values. To analyze decisions about side payment value's, we consider two situations: one is a dynamic mechanism based on participation probability, and the other is a systematic mechanism based on the coalition's contribution. Also, in multiple-item trading, we discuss the strategy analyses. [ABSTRACT FROM PUBLISHER]

Group buying is seen as an effective form of electronic commerce and a promising field for applying agent technologies. In current volume discount mechanisms, items are not allocated efficiently to buyers. Namely, social surplus is not maximum in existing volume discount schemes. To solve this problem, we propose a volume discount mechanism based on the seller's reservation price and the payment adjustment value. First, a seller registers his/her items with the evaluation value functions. The seller's evaluation value is sealed and each buyer bids his/her evaluation value as sealed bid. After the deadline, the mechanism determines the allocation of bundles of items. A tentative price is decided and the payment adjustment value is calculated. Finally, the payment amount is calculated. Our mechanism has some key advantages. First, the mechanism is Pareto efficient. Second, our mechanism is a strategy-proof mechanism, that is, it has the incentive compatibility. Third, our mechanism provides individual rationality. Fourth, our mechanism is made based on the volume discount system where the seller can give a signal indicating a discount for buyers. Finally, our mechanism weakens the influence of false name bids. [ABSTRACT FROM AUTHOR]

This paper proposes an effective lecture allocation method based on users' profiles and utilities in elective subjects. In many universities and colleges, elective subject systems are employed as a curriculum in which students make their own learning experiences. Students select multiple subjects based on their interests and preferences. Generally, each university determines members of elective subjects based on simple rules, such as the order of grade, random selection, and first arrival. Current determination systems have strong limitations in terms of reflecting users' multiple preferences. We propose a new determination algorithm and a user support system based on users' profiles and multi-attribute preferences. When users' preferences are not reflected in algorithm-based determination, a coordination agent decides lecture allocation cooperatively with each user's agent. Main advantage of our system is mainly that lectures are allocated effectively that reflected users' multiple preferences. [ABSTRACT FROM AUTHOR]

In electronic marketplaces, group buying is seen as an effective form of electronic commerce and a promising field for applying agent technologies. We study decision support systems for buyers in group buying. In group buying, when buyers cooperate with each other, a seller can discount the price of a good. In many existing group buying sites, some sellers deal in the same sort goods or their imitations. Buyers form coalitions for each item on sale. Buyers cannot always purchase goods at a lower price, because the buyers' subgroups are distributed. Buyers need to search hard to find goods they can purchase. In this paper, we propose a group buying marketplace on the Internet. In our marketplace, buyers can purchase goods at a lower price by forming coalitions. Our system can provide a service in which buyers are integrated based on their multiattribute preferences (utilities). Our system supports buyers' decision making by using the Analytic Hierarchy Process. We propose three methods for group integration. First, buyers trade in simple group buying. Second, all buyers are integrated. Third, some buyers are integrated. The advantages of our market are that buyers' multiattribute utilities are effectively expressed in group integration and buyers can purchase goods at a lower price. Buyers' payments are decided based on their degree of compromise. A successful seller can sell goods in their stock. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(10): 23–31, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10695 [ABSTRACT FROM AUTHOR]

Today, most studies of audience networks analyze the landscape of the news media on the web. However, media ecology has been drastically reconfigured by the emergence of social media. In this study, we use Twitter follower data to build an online news media network that represents the pattern of news consumption in Twitter. This study adopted a weighted network model proposed by Mukerjee et al. and implemented the Filter Disparity Method suggested by Majó-Vázquez et al. to identify the most significant overlaps in the network. The implementation result on news media outlets data in three countries, namely Indonesia, Malaysia, and Singapore, shows that network analysis of follower overlap data can offer relevant insights about media diet and the way readers navigate various news sources available on social media. [ABSTRACT FROM AUTHOR]

Customer reviews are valuable resources containing customer opinions and sentiments toward the product. The reviews are informative but can be quite lengthy or may contain repetitive information calling for opinion summarization systems that retain only the significant opinion information from the review. Abstractive summarization is a form of text summarization that generates a summary mimicking a human-written summary [1]. When pretrained language models are finetuned for abstractive review summarization, there usually occurs a problem known as the 'domain shift', because the source and target domains exhibit data from varying distributions [2]. This issue results in performance degradation of the model at the target end. This paper contributes a data package comprising of an annotated abstractive summarization dataset (annotated_abs_summ) of airline reviews having 500 reviews and abstractive summary pairs, a dataset (review_titles_data) consisting of 7079 reviews and review title pairs for review title generatioon or domain adaptive training [3] to address the domain shift problem for abstractive opinion summarization and, an annotated reviews dataset (annotated_sentiment) for rating-based sentiment classification. All datasets have been collected from the Skytrax Review Portal via web scraping using Python programming language. The datasets have several potential use cases. The abstractive summarization dataset can serve as a benchmark dataset for airline review summarization. The dataset for domain adaptive training can be used as a standalone dataset for review title generation. The dataset for sentiment analysis is multipurpose having columns like user rating and recommendation value, that can be used for statistical analysis like finding correlation between these data items as well as for other Natural Language Processing (NLP) tasks like predicting rating or recommendation value from the customer reviews. The datasets can be extended using various data augmentation techniques [4,5]. Moreover, the datasets are related and can be collectively used to develop a multi-task learning model [6] for better learning efficiency and improved performance., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)