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Pengelolaan data di dalam Buku Induk Siswa merupakan suatu hal yang sangat penting bagi setiap sekolah karena menunjang kelancaran dalam memberikan informasi. Buku Induk Siswa juga merupakan bagian penting dan termasuk kedalam elemen penunjang akreditasi sebuah sekolah. Banyak sekolah yang masih mengelola Buku Induk Siswa secara manual dan tidak efektif. Dalam hal ini dikarenakan sistem administrasi pendidikan yang ada disetiap sekolah masih menggunakan metode administrasi data belum terkomputerisasi. Buku Induk Siswa membutuhkan pengerjaan yang lama karena staff atau guru harus menualis secara manual, Buku Induk Siswa juga rentan rusak dan hilang. Oleh karena itu tujuan penelitian ini adalah membangun sebuah Aplikasi Buku Induk Siswa Berbasis Web yang diharapkan dapat membantu staff tata usaha, guru dan siswa. Metode penelitian yang penyusun buat dengan menggunakan metide deskriptif yang menggambarkan suatu keadaan atau permasalahan yang sedang terjadi berdasarkan fakta dan data-data yang diperoleh dan dikumpulkan pada saat melakukan penelitian. Metode waterfall diimplementasikan dalam membangun aplikasi supaya aplikasi yang dihasilkan lebih baik dan berkualitas. Berdasarkan pada hasil pembahasan dan kesimpulan yang dilakukan terhadap Aplikasi Buku Induk Siswa Berbasis Web dengan framework Laravel, bahwa aplikasi buku induk siswa sudah dibuat dan dapat digunakan serta dapat membantu sekolah dalam pengelolaan data buku induk siswa bagi guru serta kemudahan akses informasi siswa dan orang tua atau wali murid.

Administrative data in health can contain some important information, such as the identity of patients, doctors, and even health facilities. Data security is needed to maintain confidentiality and prevent parties who do not misuse the data. The purpose of this study is to answer the gap that exists with the use of QR Code Documents. Then the QR Code is divided for Administrative Management. In previous studies using QR codes based on Cryptography for administrative data systems in the health sector. In this study, confidential information data messages are embedded into a Cryptographic-based QR code using the AES Advanced Encryption Standard Method. The QR code will correct the error generated by the secret embedding procedure into the document, then the QR code can validate to display the data. The author conducted testing with brute force and AES methods to ensure the security of the application running properly in the data. The result of this research is that the QR code can enter Medical Record Administration data documents using the AES method. With this, it is expected to significantly reduce the potential for data leakage from the Medical Record Administration. The conclusion of the authors in this study aims to perform data administration by using a QR Code based on Cryptography. The author has presented an approach to accessing data using the storage technology used for authentication when performing data administration requests. The use of this AES Advanced Encryption Standard security method provides the advantages of ease of use and efficient use of resources

Data-science-driven development projects are increasingly gaining the attention of small and medium sized enterprises. Since SME are often lacking the necessary competencies in data science, cooperation with other companies or universities is required. The efficient handling of data is one of the main challenges in joint cross-enterprise development projects. Actual cost driver is the development of data by labeling and classifying the data by domain experts, which is very time-consuming and labor-intensive with large amounts of data. Furthermore, clearance processes also have a high potential to cause delays before data can be shared with project partners. Moreover, before the actual work can begin, it is often necessary to clean up and repair incomplete or noisy data. The concept of Data Administration Shell presented in this paper addresses the challenge of structured information sharing and information management in joint cross-enterprise engineering. The Data Administration Shell links data sets to information regarding data origin and already performed analyses including their results and program scripts. Adding relations and documentation facilitates the reuse of data sets for subsequent projects. For this purpose, the Data Administration Shell adapts the concepts serving the information sharing in the research field of manufacturing and Digital Twin. The evaluation of the Data Administration Shell was based on time-series measurement data from a production process optimization scenario. Here, the Data Administration Shell manages the data sets of time series data and facilitates the joint cross-enterprise engineering of data-driven solutions.

The Internet-of-Healthcare Systems is a highly distributed special emulation of the Internet of Things technology. Patient medical data sourced from the participating hospitals are integrated with a decentralized storage system using blockchain technology to provide the highest level of storage and access security possible, overcoming the security and data administration problems that may occur at the local hospital level where the patient data is stored within the hospital’s central server, especially if that data is subjected to external threats. The Internet-of-Healthcare Systems, currently implemented in over 350 hospitals, utilises software agents, accessed using the Message Queueing Telemetry Transport protocol, which efficiently handles potentially thousands of participating local systems without loss of network timeliness. Also, the system works with the wide variety of health information systems used in the participating hospitals. This makes the system a worthwhile candidate for a nationwide integrated health records system, and is an exemplar for many different types of secure networks that could be generically called an Internet of Special Things; a network of software agents programmed for a special purpose. Mobile device apps enable secure direct access to patient data in a central blockchain with download capability to a mobile device, under strict and fully managed access control using Amazon Web Services, with permissions controlled by the Key Management System. Feedback from participating medical staff indicates a high level of satisfaction with all aspects of the system: ease of use, ease of installation, maintenance and update, and, importantly, the security of the system.

With the rapid development of information technologies and information economy ingeneral, effective information management determines the success of almost every business operation, and the choice of information and management decisions in general relieson IT managers. However, it is rather difficult for functional or line managers decidewhether it is important to participate in the formation of information strategy of their own business and whether they need to know what tools are available to turn a large array of information into business intelligence. This article is intended to reveal the important role of information and information resources in the activities of modern enterprises. The concepts of “data” and “information” are described. The data model and data types used by business information systems are described. The role of the database in the business process management system is revealed. It is indicated how important it is to form the information space of the enterprise correctly and choose the necessary software product for a particular enterprise. It is determined that the information system of the enterprise is based on the integrated use of potential and available information resources, taking into account their main features. The connections between the component of management systems are investigated and it is noted that the business process management system of the enterprise covers all levels of the enterprise. It is said that the enterprise may face different problems without data administration procedures. The types of information support using different levels of management are given. The internal and external information which his taken into account during making management decisions is characterized. It is proposed to invest in the management practice of developing an information strategy that significantly improves the management process and increases its efficiency. The typical structure of the proposed document and the role of information strategy regarding the levels of enterprise management are given.

PurposeBig data has raised challenges and opportunities for business, the information technology (IT) industry and research communities. Nowadays, small and medium-sized enterprises (SME) are dealing with big data using their limited resources. The purpose of this paper is to describe the synergistic relationship between big data and knowledge management (KM), analyze the challenges and IT solutions of big data for SME and derives a KM model of big data for SME based on the collected real-world business cases.Design/methodology/approachThe study collects eight well-documented cases of successful big data analytics in SME and conducts a qualitative data analysis of these cases in the context of KM. The qualitative data analysis of the multiple cases reveals a KM model of big data for SME.FindingsThe proposed model portrays the synergistic relationship between big data and KM. It indicates that strategic use of data, knowledge guided big data project planning, IT solutions for SME and new knowledge products are the major constructs of KM of big data for SME. These constructs form a loop through the causal relationships between them.Research limitations/implicationsThe number of cases used for the derivation of the KM model is not large. The coding of these qualitative data could involve biases and errors. Consequently, the conceptual KM model proposed in this paper is subject to further verification and validation.Practical implicationsThe proposed model can guide SME to exploit big data for business by placing emphasis on KM instead of sophisticated IT techniques or the magnitude of data.Originality/valueThe study contributes to the KM literature by developing a theoretical model of KM of big data for SME based on underlying dimensions of strategic use of data, knowledge guided big data project planning, IT solutions for SME and new knowledge products.

National Agency of Ukraine for finding, tracing and management of assets derived from corruption and other crimes (abbr. – Asset Recovery and Management Agency or ARMA) is a special governmental body, authorized to formulate and implement state policy in the sphere of tracing, finding of assets that are subject to seizure and that are aimed to be seized, as well as management of seized assets in criminal proceedings.In the article are analyzed the principles of legal support for the implementation and functioning of modern information processes in the institutional and administrative activities of the ARMA. Internal and external preconditions for establishment of the National Agency are the following: to improve mechanisms for tracing and finding of assets which illegally withdrawn from Ukraine as a result of corruption and other crimes, and development of transparent and effective mechanisms for managing of seized assets; obligations within Visa Liberalization Action Plan, obligatory recommendations within OECD dialog, and other inter-national obligations of Ukraine. The mechanism of detection, search and management of assets are public functions, the implementation of which is impossible without the following processes of information activity: creation, exchange and dissemina-tion of information; protection of information and data protected by law; data administration, data digitization; analysis and statistics, etc. ARMA is one of the key elements of the anti-corruption mechanism both to counteract corruption and to eliminate its negative effects. Asset detection, search and asset management procedures are carried out within the framework of an integral information activity, which at the same time accompanies interdepartmental management processes. One of the key principles of the implementation of the state policy of management of corrupt assets in the activities of ARMA is wide powers of: obtain, process and disclose information about assets; access to information resources, including those held by entities of foreign jurisdiction; providing relevant responsibilities of authorities, local governments, individuals and legal entities to provide information, as well as coercive mechanisms in case of failure to provide information; wide publicity of the facts and procedures for the seizure of assets in criminal proceedings; processing of other criminal information requiring security and safety; generalization and rapid exchange of information on assets obtained by crime. ARMA information activity includes: accumulation, structuring of information; selecting the necessary data in the context of a specific search criteria; monitoring of data entry, correction and publication; control and comparison of performance of the department, contractors; automation of the formation of certificates, reports maintenance of statistics and accounting of correspondence; ensuring the integrity and reliability of information, etc.Administering the Register of seized assets is a special type of complex information work that requires special regulatory support in the form of a separate Regulation on the Unified Register of Arrested Assets.

Edge intelligence (EI), as an emerging technology, has been attracting significant attention. It pushes the frontier of artificial intelligence (AI) from the cloud to the network edge, aiming to embrace and support the next-generation communications while unleashing AI services. However, it faces challenges in its decentralized management and security, which limit its capabilities to support services with numerous requirements. On the other side, blockchain (BC), as a promising decentralized technology, is beneficial to tackle the above issues. However, there exist some technical challenges for BC, such as transaction capacity, scalability, and fault tolerance. Motivated by significant current interest around EI and BC, this survey examines whether the synergy of EI and BC can make a powerful network with combined functionalities of both cutting-edge technologies. Accordingly, we develop EI-chain and Chain-intelligence to realize reliable computing-power management, data administration, and model optimization at the edges, while improving the functions of BC by leveraging complementary characteristics of EI and BC, further making up for their own limitations. In this survey, a wide spectrum of literature is carefully reviewed to enable the EI-chain and Chain-intelligence. Moreover, we cover the technological aspects of EI-chain and Chain-intelligence: overview, motivations, and frameworks. Finally, some challenges and future directions are explored. We believe this survey will provide developers and researchers a comprehensive view on the synergy of EI and BC, while accelerating the design of a powerful integrated network.

Purpose The purpose of this paper is to apply link prediction to community mining and to clarify the role of link prediction in improving the performance of social network analysis. Design/methodology/approach In this study, the 2009 version of Enron e-mail data set provided by Carnegie Mellon University was selected as the research object first, and bibliometric analysis method and citation analysis method were adopted to compare the differences between various studies. Second, based on the impact of various interpersonal relationships, the link model was adopted to analyze the relationship among people. Finally, the factorization of the matrix was further adopted to obtain the characteristics of the research object, so as to predict the unknown relationship. Findings The experimental results show that the prediction results obtained by considering multiple relationships are more accurate than those obtained by considering only one relationship. Research limitations/implications Due to the limited number of objects in the data set, the link prediction method has not been tested on the large-scale data set, and the validity and correctness of the method need to be further verified with larger data. In addition, the research on algorithm complexity and algorithm optimization, including the storage of sparse matrix, also need to be further studied. At the same time, in the case of extremely sparse data, the accuracy of the link prediction method will decline a lot, and further research and discussion should be carried out on the sparse data. Practical implications The focus of this research is on link prediction in social network analysis. The traditional prediction model is based on a certain relationship between the objects to predict and analyze, but in real life, the relationship between people is diverse, and different relationships are interactive. Therefore, in this study, the graph model is used to express different kinds of relations, and the influence between different kinds of relations is considered in the actual prediction process. Finally, experiments on real data sets prove the effectiveness and accuracy of this method. In addition, link prediction, as an important part of social network analysis, is also of great significance for other applications of social network analysis. This study attempts to prove that link prediction is helpful to the improvement of performance analysis of social network by applying link prediction to community mining. Originality/value This study adopts a variety of methods, such as link prediction, data mining, literature analysis and citation analysis. The research direction is relatively new, and the experimental results obtained have a certain degree of credibility, which is of certain reference value for the following related research.

The focus of this study is to investigate and analyze the different factors of inter-household conflicts over farmland. The study further sought to assess the human security implications on the community of the study area. It has been found that farmers in the study area are suffering from land-related conflicts and its associated impacts. Descriptive-case study was employed in the study. In-depth interviews with key informants and FGDs were data collection instruments used in the study. Secondary data drawn from archival documents and government reports were also used. The major study finding indicated that inter-household conflicts over farmland occurred with the interface of underlined and risk factors. Boundary encroachment, land eviction, inherited land conflict, contract breaching conflict are among the most common. The divisive land administration institutions, individuals’ unproductive competition over farmland, poorly implemented land administration programs, and cultural attachment to land identified as underlined factors for the farmland conflicts have continued to happen. The culture of violence, availability of small arms and light weapons, and prevalence of other forms of social conflicts are also risk factors which have created fragile peace among the members of the community. The conflict has affected the economic, social, political, and psychological wellbeing of the study area residents, as well as human security threats. It was found to be imperative to revise and harmonize land administration laws and even to amend some of the faulty legislated articles. Above all digital land registration and data administration should be considered by governmental organizations and NGOs who are working on land administration sector. Key words: Household, farmland, conflict, human security, Jamma woreda.

IoT-based applications have developed as a significant sector for designers and scientists, exemplifying the size and effect of information relevant issues to be resolved in voguish merchandise associations especially in dispersed computing. The paper presented here basically gives a utilitarian system that distinguishes the securing, the executives, managing and mining zones of large Internet of Things info, and distinct parallel functional subjects are individualized and portrayed as much as their pivotal qualities and abilities Wang and Chu (Data management for Internet of things: challenges and opportunities, pp. 1144–1151, 2013 [1]). At that point of ebb and flow look into Web of things, usance is examined, in addition, the complications and operations related with large IoT-based information are recognized. We additionally communique an investigation of basic IoT-based application productions and research proposals dependent on similar erudite and commerce distributions. At last, some open issues and challenges what is more, some run of the mill models are delivered under the prospective IoT-based research structure Hasan, E. Curry (Internet Technol. (TOIT), 14(1):2, 2014 [2]).

Data collection and management is a tedious and time consuming activity. With CHORT (Cardiac HOspital ReporT), the authors have designed a new approach to integrating all data related to a specific patient. CHORT allows interactive data input or data acquisition from external systems. CHORT is able to access other local databases. CHORT can initiate REGAL, a report generator, at any time during a patient's hospital stay. All information is converted into fluent French text before being integrated into the report and merged with free text. REGAL is an interpreted language permitting flexibility in data selection and control over data display and page lay-out. CHORT improves and speeds up medical file access, suppresses typed report output, and provides a database for clinical and scientific purposes. >

Creation of information technologies becomes especially actual when the accessible information is interpreted as a major and unique resource, a stock, a reserve, as an element of economic potential of the business entity, which should be used effectively for achievement of a competitive position in the market. Thereupon there is necessary a decision of some actual scientific problems: formation of the major concepts, development of theoretical bases of data resource management, creations of typical models of information systems for the enterprises, corporations and regional economy. In the framework of e-Governance the conception of decision making support system is offered on the base of the aggregated opinions of public observers. All estimations of these recipients are realized by fuzzy inference system and aggregated by structured neural network model. The neural network model combining two types three-layer feedforward neural networks, allows rather quickly reacting to possible changes in a conjuncture of recipients’ priorities.

In order to solve the problems of low efficiency of management information systems and low utilization rate of the information resources, this research paper proposes the designs of an exhibition management information system by using a B/S structure (Browser/Server mode). The proposed system is aimed at the analysis of functions and types of exhibitions. The system is comprised of the following three components: the browser-side, server-side, and middle layer. Among them, the browser includes a user management module and exhibition environment visualization module. The server includes an upper computer control module and human-computer interaction module. The middle layer includes the data resource management module, document information management module, exhibition project audit approval and management module, and information scheduling module. Experimental results show that the lowest management efficiency of the system is 96.19%, the highest can reach 98.39%, and the utilization rate of information resources is above 94%, indicating that the system has achieved the design expectation.

Background: Maternal and child health (MCH) routine data is essential in making a good health-relatedpolicy. However, the quality of MCH routine data in Indonesia is doubted, and thus the Indonesian governmentrelies heavily on the survey data for policymaking. This condition raises questions about where the problemsexist in routine data recording stages. This study aims to explore the barriers and strategies of MCH routinedata recording by the administrators in the primary healthcare center.Method: This study was qualitativeresearch conducted in Buru Regency, Ambon City, Purworejo Regency, and Surakarta City from May toNovember 2020. The data collections were intended to understand administrators’ efforts to deal with the datarecording problems. Data triangulation was performed through in-depth interviews with primary healthcarecenter staff and observations on daily routine data administration practices.Results: The study demonstratedchallenges in the MCH routine data administration context. The first problem is behavioral contexts lead toincorrect input and delay data submission. Second, technical determinant shows the lack of integration thatleads to repetitive data recording and data fragmentation. The third was the organizational problem suchas lack of inter and intra-departmental coordination in data sharing, infrastructure, and human resourceshortage.Conclusion: The findings elucidate the problem of administrative structures in the implementationof routine data policy. A comprehensive response to cope with routine data policy implementation contextis needed. Existing maternal and child healthcare routine data requires structural administration refinementthat provides a context for implementing reliable routine data recording of maternal and child health.

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Automated observations of natural occurrences play a key role in monitoring biodiversity worldwide. With the development of affordable hardware like the AudioMoth (Hill et al. 2019) acoustic logger, large scale and long-term monitoring has come within reach. However, data management and dissemination of monitoring data remain challenging, as the development of software and the infrastructure for the management of monitoring data lag behind. We want to fill this gap, providing a complete audio monitoring solution from affordable audio monitoring hardware, custom data management tools and storage infrastructure based on open source hard- and software, biodiversity information standards and integrable interfaces. The Scientific Monitoring Data Management and Online Repository (SIMON) consists of a portable data collector and a connected online repository. The data collector, a device for the automated extraction of the audio data from the audio loggers in the field, stores the data and metadata in an internal cache. Once connected to the internet via WiFi or a cable connection, the data are automatically uploaded to an online repository for automated analysis, annotation, data management and dissemination. To prevent SIMON from becoming yet another proprietary storage, the FAIR principles (Findable, Accessible, Interoperable, and Re-usable) Wilkinson et al. (2016) are at the very core of data managed in the online repository. We plan to offer an API (application programming interface) to disseminate data to established data infrastructures. A second API will allow the use of external services for data enrichment. While in the planning phase, we would like to take the opportunity to discuss with domain experts the requirements and implementation of different standards—namely ABCD (Access to Biological Collections Data task group, Biodiversity Information Standards (TDWG) 2007), Darwin Core (Darwin Core Task Group, Biodiversity Information Standards (TDWG) 2009) and Darwin Core Archive (Remsen et al. 2017)—connecting to external services and targeting data infrastructures.

This chapter discusses various challenges related to Internet of Things (IoT) implementation into the healthcare sector, namely, data resource management, security, loss of privacy, access control, and stakeholder collaboration. IoT is going to be an integral part of the patient’s diagnosis, treatment, recovery, and monitoring process in the near future. It is evident that a large number of objects will be connected to the IoT network. All these devices will generate unstructured data; these data must be processed in a time-critical manner. Otherwise, it becomes inadequate for real-time monitoring and decision-making, which requires immense infrastructure, computation, networking, storage capacity, etc. For monitoring purposes, it is critical to process and deliver data in synchronization to the stakeholders like treating physician’s panel, analytics platforms, healthcare providers, and insurance companies.

In future IoT (Internet of Things), big-data administration & machine learning disclosure for expansive scale modern robotization application, the significance of mechanical internet is expanding step by step. The interconnection by means of the Internet of computing gadgets installed in ordinary items, empowering them to send and get information. BD is informational collections that are so voluminous and complex that customary information preparing application programming are insufficient to manage them. ML is a subset of artificial intelligence that regularly utilizes measurable procedures to enable PCs to "learn" with information, without being expressly modified. A few differentiated advancements, for example, IoT, computational intelligence, machine type communication, BD, & sensor technology can be fused together to enhance the data administration & information revelation effectiveness of expansive scale robotization applications. An expanding measure of significant data sources, propels in IoT & Big Data (BD) advances & also the accessibility of an extensive variety of machine learning (ML) calculations offers new potential to convey logical administrations to nationals & urban chiefs. In any case, there is as yet a hole in joining the present best in class in an incorporated system that would help lessening improvement costs & empower new sort of administrations. Voluminous measures of data have been created, since the previous decade as the scaling down of IoT gadgets increments. Be that as it may, such data are not valuable without scientific power. Various BD, IoT, & investigation arrangements have empowered individuals to acquire profitable knowledge into extensive information created by IoT gadgets. However, these arrangements are still in their earliest stages, & the domain does not have a thorough review on this. Here we endeavored to give a reasonable more profound understanding about the IoT in BD structure alongside its different issues & challenges & concentrated on giving conceivable arrangement by ML strategy.

International audience; In view of the changes taking place in society, social progress and the achievements of science and technology, the protection of fundamental rights must be strengthened. The aim of the article is to analyse the principles and peculiarities of safe management of the personal data in social networks. In this scientific article, methods of document analysis, scientific literature review, case study and generalization are used. Consumers themselves decide how much and what kind of information to publicize on the Facebook social network. In order to use the third-party applications, users at the time of authorization must confirm that they agree to give access to their personal data otherwise the service will not be provided. Personal data of the Facebook user comprise his/her public profile including user's photo, age, gender, and other public information; a list of friends; e-mail mail; time zone records; birthday; photos; hobbies, etc. Which personal data will be requested from the user depends on the third-party application. Analysis of the legal protection of personal data in the internet social networks reveals that it is limited to the international and European Union legal regulation on protection of the personal data in the online social networks. Users who make publicly available a large amount of personal information on the Facebook social network should decide on the issue if they want to share that information with third parties for the use of their services (applications). This article presents a model for user and third party application interaction, and an analysis of risks and recommendations to ensure the security of personal data of the user.

This volume is the second one of the 16th East-European Conference on Advances in Databases and Information Systems (ADBIS 2012), held on September 18-21, 2012, in Pozna, Poland. The first one has been published in the LNCS series. This volume includes 27 research contributions, selected out of 90. The contributions cover a wide spectrum of topics in the database and information systems field, including: database foundation and theory, data modeling and database design, business process modeling, query optimization in relational and object databases, materialized view selection algorithms, index data structures, distributed systems, system and data integration, semi-structured data and databases, semantic data management, information retrieval, data mining techniques, data stream processing, trust and reputation in the Internet, and social networks. Thus, the content of this volume covers the research areas from fundamentals of databases, through still hot topic research problems (e.g., data mining, XML data processing), to novel research areas (e.g., social networks, trust and reputation, and data stream processing). The editors of this volume believe that its content will inspire the researchers with new ideas for future development. It may also serve as an overview of the ongoing work in the field of databases and information systems.

This article discusses a comparison of various numbers of islands in Indonesia; and it addresses a valid method of accounting or enumerating numbers of islands in Indonesia. Methodology used is an analysis to compare the different number of islands from various sources. First, some numbers of Indonesian islands were derived from: (i) Centre for Survey and Mapping- Indonesian Arm Forces (Pussurta ABRI) recorded as 17,508 islands; (ii) Agency for Geospatial Information (BIG) previously known as National Coordinating Agency for Surveys and Mapping (Bakosurtanal) as national mapping authority reported with 17,506 islands (after loosing islands of Sipadan and Ligitan); (iii) Ministry of Internal Affair published 17,504 islands. Many parties have referred the number of 17,504 islands even though it has not yet been supported by back-up documents; (iv) Hidrographic Office of Indonesian Navy has released with numbers of 17,499; (v) Other sources indicated different numbers of islands, and indeed will imply to people confusion. In the other hand, the number of 13,466 named islands has a strong document (Gazetteer). Second, enumerating the total number of islands in Indonesia can be proposed by three ways: (i) island census through toponimic survey, (ii) using map, and (iii) applying remote sensing images. Third, the procedures of searching valid result in number of islands is by remote sensing approach - high resolution satellite images. The result of this work implies the needs of one geospatial data source (including total numbers of islands) in the form of ‘One Map Policy’ that will impact in the improvement of Indonesian geographic data administration.