Berdasarkan sumber informasi dari Badan Pusat Statistik (BPS), kita dapat mengetahui persentase kemiskinan yang ada di seluruh provinsi Indonesia. Namun didalam data yang tersaji di BPS tersebut, kategori persentase kemiskinan yang disajikan hanya berdasarkan provinsi sedangkan dalam upaya untuk memberantas kemiskinan yang ada, pemerintah perlu mengetahui daerah manakah yang memiliki tingkat kemiskinan tinggi, sedang atau rendah sehingga pemerintah dapat menetapkan skala prioritas untuk menanggulangi kemiskinan tersebut. Oleh karena itu, perlu dilakukan pengelompokan provinsi yang ada di Indonesia berdasarkan tingkat kemiskinannya agar pemerintah dapat memberikan kebijakan atau pendekatan yang tepat dan cepat untuk mengatasi kemiskinan yang terjadi berdasarkan tingkat kemiskinan masing-masing provinsi. Pada penelitian ini digunakan metode clustering dengan algoritma K-Means untuk mengelompokan provinsi berdasarkan tingkat kemiskinannya dengan bantuan software Weka. Hasil penelitian menunjukkan terdapat 3 cluster provinsi di Indonesia berdasarkan tingkat kemiskinannya yaitu Cluster 0 (provinsi dengan tingkat kemiskinan rendah), Cluster 1 (provinsi tingkat kemiskinan sedang), dan Cluster 2 (provinsi dengan tingkat kemiskinan tinggi). Provinsi yang termasuk dalam kategori provinsi dengan tingkat kemiskinan tinggi yaitu Maluku, Papua Barat dan Papua.

The result of the analysis of the studyshows the lack of educational condition related to Information Technology (IT) especially for orphanage children. Community service activities aim to provide computer training as a form of character development in the field of education. The subjects of community service activities are the children at the Mujahidin Orphanage in Anjir Serapat Village, Kapuas Timur Sub-District, Kapuas District, with 11 members. Training activities are supported by lecture methods, frequently asked questions and direct practice of using computer applications with the help of training modules provided to the participants as a tool in practice. The results showed that computer training can give knowledge and understanding for orphaned children in computer skills in the mastery of Microsoft Word, Microsoft Excel, and Microsoft Powerpoint and can foster the values of educational characters in themselves such as curiosity, creative, hard work, and communicative.

Referring to the widespread problem of diploma forgery in Indonesian educational institutions as the impetus for UNTIRTA’s latest vision as an “Integrated, Smart, and Green University,” UNTIRTA intends to use blockchain technology to prevent diploma forgery and overcome issues related to existing platforms at UNTIRTA, such as frequent connection interruptions when accessed by a large number of users simultaneously. Before using blockchain technology, UNTIRTA must evaluate several readiness issues. This study presented the interpretative structural modeling (ISM) method to assess the primary preparedness elements for adopting blockchain technology in universities and sought to provide pertinent strategy ideas for UNTIRTA’s blockchain technology application. The results reveal sixteen major parameters that influence the adoption readiness of blockchain technology at UNTIRTA. The primary variables impacting the adoption and deployment of blockchain technology at UNTIRTA are management and employee support and a grasp of the technology. To realize UNTIRTA’s mission as an “Integrated, Smart, and Green University”, the proposed method entails determining an initial agreement in which all stakeholders have a shared understanding and commitment to Blockchain technology implementation at UNTIRTA. The objective of the tactical proposal is to establish each unit’s mission in the blockchain implementation program. The objective of the technical proposal is to construct a planning document that will serve as a coordination tool between the chairman and members, as well as all parties interested in the adoption of Blockchain technology at UNTIRTA.

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