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The most attractive problem in campus asset management is academic room monitoring and management. Academic rooms consist of classroom, seminar/conference room, laboratory, studio, workshop room and other room. Limited academic room is a main constraint in room scheduling problem and potentially arise scheduling collision. Another problem is improvement to room monitoring and management especially room assets. This paper will introduce and investigate a framework of improvement to academic room monitoring and management in campus intelligently. Framework will consist of global business process, common information model and academic room system architecture.

[Id]Manajemen resiko merupakan bidang penting pada manajemen proyek secara keseluruhan, dan manajemen proyek sistem informasi secara khusus. Melalui manajemen resiko yang baik, pimpinan dan stakeholder proyek berharap bahwa resiko terhadap kegagalan proyek dapat diminimalisir dengan usaha yang rasional. Manajemen resiko sendiri meliputi banyak kegiatan, salah satunya adalah analisis dan perencanaan mitigasi resiko. Aspek penting pada analisis dan perencanaan mitigasi resiko yaitu melakukan penilaian atau estimasi atas resiko untuk menentukan prioritas serta dampak setiap mitigasi yang diambil. Pada umumnya, hal yang paling mudah diterima stakeholder dalam menyajikan resiko adalah menghitung biaya akibat resiko tersebut. Untuk melakukan perhitungan biaya untuk memitigasi resiko, dapat digunakan salah satu pendekatan yaitu Expected Monetary Value (EVM). Melalui pendekatan EVM, dapat ditentukan pilihan tindakan mitigasi yang paling optimal, dengan estimasi biaya paling minimal[En] Risk management is an important area of overall project management, and information systems project management in particular. Through good risk management, project leaders and stakeholders expect that the risks to project failure can be minimized by rational efforts. Risk management itself includes many activities, one of which is risk mitigation analysis and planning. An important aspect of risk mitigation analysis and planning is to assess or estimate the risks to determine the priorities and impacts of each mitigation. In general, the easiest thing a stakeholder receives in presenting risk is to calculate the cost of the risk. To perform cost calculation to mitigate risk, one of the approaches is Expected Monetary Value (EVM). Through the EVM approach, the most optimal mitigation options can be determined, with the least cost estimate

Single Sign-On (SSO) is a mechanism that allows users to access various services using a single set of login credentials. However, in SSO implementations, there are still challenges related to security and authentication management, particularly attacks targeting the Identity Provider (IDP). To address this, the use of Non-Fungible Tokens (NFTs) as proof of IDP ownership has been proposed as a solution to enhance security in the authentication mechanism. The utilization of NFTs in SSO with OpenID Connect and OAuth 2.0 has the potential to improve security and convenience in the authentication process due to the unique and non-duplicable nature of NFTs. The results of this research present a model and design of SSO with NFTs on OpenID Connect and OAuth 2.0. An SSO application with login, register, and password recovery features was also developed to provide convenience to users during the login process. The findings conclude that the utilization of NFTs in SSO with OpenID Connect and OAuth 2.0 has the potential to enhance security and convenience in the authentication mechanism. Further research is needed to explore aspects such as scalability, in-depth security analysis, testing in real-world scenarios, improvement of integration and interoperability, as well as comparative analysis with other SSO technologies.

The examination of complaints of labor violations is part of the main activity of the labor inspection section within the Department of Manpower. Monitors will examine companies that are considered to have violated labor laws based on a letter of complaint sent by the relevant union organization or legal aid agency. The easy way to communicate at this time, making the submission of complaint letters can be directly sent in the form of images through electronic media such as whatsapp or email. This makes it difficult for administrative staff to recapitulate incoming complaints because they have to read and enter data manually into the system. Therefore, this research was conducted to create a system that utilizes OCR technology and text feature extraction to be able to input complaints data automatically. This research resulted in a prototype of letter input and a database of letter storage that can be further utilized for Data Mining and Business Intelligent. OCR implementation is done by using the Tesseract library while the text feature selection utilizes the Natural Language Toolkit (NLTK) library. The results of testing of the prototype showed an accuracy of 66.7% of the OCR results and 91.67% of the manually typed letters.