The Mapping of Mosque Community to Improve Mosque Engagement in Community

The Mosque in the Prophet Muhammad SAW era had a strategic role. The role is to be a solution and provide prosperity for the Muslims in particular and the surrounding community in general. Currently, the mosque plays a narrower role. It is a provider of facilities for pilgrims to carry out routine worship. In order for this role to increase, the mosque administrator, called DKM (Mosque Prosperity Council), must know his congregation more closely so that he knows what is needed and then comes to provide solutions. This study aims to create and implement an information system to manage congregational data to improve the role of mosques in the community. The main material that was obtained and prepared was data on residents around the mosque and the stakeholder needs (leaders of organizations around the mosque such as the heads of hamlet (RW), neighbourhood (RT), and youth organizations). The citizen data and stakeholder needs are used to develop the system. Because the specifications of the requirements can change during system development, the development method chosen is the prototyping method. There are two main outputs of this activity, namely the availability of a congregational data mapping application, and the installation of internet network infrastructure at the mosque. The two outputs in their implementation have proven to be beneficial for the congregation and the surrounding community. The information system provides improved service quality to pilgrims and residents in various activities such as zakat and qurbani. Meanwhile, Internet infrastructure provides new hope in easing the burden of community quotas and bringing children closer to the mosque.

This is how we learn - A Best Practice Case of Qualification in SMEs for Work 4.0

Increasing digitalisation is fundamentally changing the understanding and possi-bilities of value creation as well as labour organisation. The systematic collection, storage and analysis of data is becoming a decisive competitive factor and is the basis for intelligent products, processes and production technology. This results in new competence requirements and roles in mechanical and plant engineering and in the manufacturing industry in general. Machine Learning in particular, as the basis of Artificial Intelligence, poses great challenges for companies, as the demand for experts, so-called Data Scientists, significantly exceeds the offer and furthermore, these experts rarely have the required domain knowledge - the core competences of manufacturing companies. In this context, the new job descrip-tion of the Citizen Data Scientist as a link between the most important disci-plines of information technology, domain knowledge and data science enters the focus of attention. The article presents a role model as a basis for team building and systematic development of required competences in the manufacturing in-dustry and combines the results of various research projects and industrial im-plementations. For this purpose, competences of the future are derived in sec-tion 1 and transferred into a transdisciplinary role model in section 2. Section 3 addresses the exemplary practical application in an industrial use case, while section 4 gives an outlook on the possibilities of target-oriented competence development for the individual roles and actors.

Implementasi Metode Multi Objective Optimization On The Basis Of Ratio Analysis (MOORA) Pada Sistem Pendukung Keputusan Penentuan Penerima Bantuan Iuran BPJS Kesehatan (Studi Kasus: Desa Loru Kabupaten Sigi)

Introduction: This study aims to build an application that can carry out the selection process for prospective recipients of contribution assistance so that it is easier and becomes an alternative choice for the Village Government in determining eligible residents for BPJS Health contribution assistance in Loru Village, Sigi Regency. Methods: This decision support system application is web-based using the Hypertext Prepocessor (PHP) programming language with the Multi Objective Optimization method On The Basis Of The Ratio Analysis (MOORA), using sublime text 3 software and also MySQL as the database. In this study, 444 households were used as data for heads of households. With the system, orders will be carried out objectively and in detail. To determine which residents are truly entitled to receive assistance, this is done by compiling citizen data by considering the value of the MOORA method formula for each of the specified criteria. Result: The results that have been carried out by this author are a solution to determine the recipients of BPJS Health contribution assistance in Loru Village, Sigi Regency, so that the selection process can be more effective in terms of time and operation. Conclutions: Based on manual calculations as a comparison with the calculation of the system built, the same results were obtained. This shows that the system built can process the selection of potential recipients of contribution assistance. The result of the system process using the MOORA method is the ranking of PBI candidates with the highest rank to the lowest rank.

AirKit: A Citizen-Sensing Toolkit for Monitoring Air Quality

Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility. In this paper, we present AirKit, which was developed as an integrated and open source “social IoT technology.” AirKit enables a comprehensive approach to citizen-sensing air quality through several integrated components: (1) the Dustbox 2.0, a particulate matter sensor; (2) Airsift, a data analysis platform; (3) a reliable and automatic remote firmware update system; (4) a “Data Stories” method and tool for communicating citizen data; and (5) an AirKit logbook that provides a guide for designing and running air quality projects, along with instructions for building and using AirKit components. Developed as a social technology toolkit to foster open processes of research co-creation and environmental action, Airkit has the potential to generate expanded engagements with IoT and air quality by improving the accuracy, legibility and use of sensors, data analysis and data communication.

Cancer-Net SCa: Tailored Deep Neural Network Designs for Detection of Skin Cancer from Dermoscopy Images

Background: Skin cancer continues to be the most frequently diagnosed form of cancer in the U.S., with not only significant effects on health and well-being but also significant economic costs associated with treatment. A crucial step to the treatment and management of skin cancer is effective early detection with key screening approaches such as dermoscopy examinations, leading to stronger recovery prognoses. Motivated by the advances of deep learning and inspired by the open source initiatives in the research community, in this study we introduce Cancer-Net SCa, a suite of deep neural network designs tailored for the detection of skin cancer from dermoscopy images that is open source and available to the general public. To the best of the authors' knowledge, Cancer-Net SCa comprises the first machine-driven design of deep neural network architectures tailored specifically for skin cancer detection, one of which leverages attention condensers for an efficient self-attention design.Results: We investigate and audit the behaviour of Cancer-Net SCa in a responsible and transparent manner through explainability-driven performance validation. All the proposed designs achieved improved accuracy when compared to the ResNet-50 architecture while also achieving significantly reduced architectural and computational complexity. In addition, when evaluating the decision making process of the networks, it can be seen that diagnostically relevant critical factors are leveraged rather than irrelevant visual indicators and imaging artifacts. Conclusion: The proposed Cancer-Net SCa designs achieve strong skin cancer detection performance on the International Skin Imaging Collaboration (ISIC) dataset, while providing a strong balance between computation and architectural efficiency and accuracy. While Cancer-Net SCa is not a production-ready screening solution, the hope is that the release of Cancer-Net SCa in open source, open access form will encourage researchers, clinicians, and citizen data scientists alike to leverage and build upon them.

DESIGNING THE INFORMATION SYSTEM FOR DATA COLLECTION OF COVID-19 SYMPTOMS FOR INDONESIAN CITIZENS

Information systems are the result of rapidly emerging technological developments because human needs as information users of technology are very strong and rapid. Begin with the very rapid growth of computer technology, computers such as smartphones, tablets, notebooks and others are limited in scale. This small computer device must be connected to the Internet so that it can be used properly. And the information system plays its role as a provider of information that computer users want to access when the computer device is linked to the Internet. The information system developed in this paper is the Citizen Data Collection Information System, this system was created using the YII Framework. The YII framework uses the MVC method which makes it easier to develop a Citizen Data Collection Information System. With this Information System, information about the latest condition of the residents can be easily accessed. So that the Kelurahan, Kecamatan, RW, and RT will have the latest information about their residents and easily anticipate if needed. In the development of this system, it has staged such as literature study, observation, interviews, analysis, design, testing, and implementation. The conclusion is that this information system can carry out the desired function when it is implemented.

Sistem Pengelolaan Data Warga, Informasi Kegiatan dan Informasi Penggunaan Iuran pada Lingkungan Rukun Tetangga (RT) Berbasis Web

Rukun Tetangga is an organization led by the chairman of RT, rt's duties and functions are to provide services, maintain the harmony of the environment of its citizens, as well as a medium of community liaison with the local government in conveying aspirations. In observation activities and interviews directly with the chairman of RT and citizens, there are problems that are often faced by management members and citizens, the problem is the process of managing citizen data, information activities and contribution reports, the problems such as the process of recording repeatedly and the use of paper media that can cause the search process is quite time consuming and has a risk of being vulnerable to damage or loss. To overcome this, RT needs to develop data management system in Rukun Tetangga by using Waterfall as its development method and Unified Modeling Language (UML), and for the implementation process, researchers use PHP and MySQL. This research produces web-based applications for which provides management of citizen data, activity information and contribution management reports that can speed up the service process for citizens.

How can traditional statistical relationships be redefined through citizen to government partnerships?

The post-2015 Development Agenda proposes to produce much more statistics and data than currently available in the official arena through advanced methods and innovative partnerships. By associating governments and data producers of all kinds it aims to monitor the Sustainable Development Goals (SDGs). The objective of this paper is to explore and analyse one of the 2030 Agenda greatest challenges, i.e. to redefine traditional statistical relationships and processes to associate citizenry as an active stakeholder in the monitoring of SDGs. It proposes innovative ideas linking citizen-to-government and government-to-citizen data partnerships (C2G dp and G2C dp) to the SDG requirements. The paper portrays and analyses the benefits for parties of alternative projects from Uganda, Canada and Uruguay. The C2Gdp Stats Up program is featured as an additional case study, describing its achievements and shortcomings. This contribution constitutes a valuable co-creation case to fill the gap of lack of partnering skills. In sum, the paper presents the added value of a constructive socio-technical approach to SDG 17. Final conclusions propose a roadmap to support the work of National Statistical Offices to address complex challenges to walk the talk of the 2030 Agenda harnessing the crucial role of civil society in their plans.