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Cyber Security Analysis of Academic Services based on Domain Delivery Services and Support using Indonesian E-Government Ratings (PEGI) Riadi, Imam; Riyadi Yanto, Iwan Tti; Handoyo, Eko
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1083

Abstract

Safe academic services are the most important part of universities. The security of academic services is very important to maintain information optimally and safely. Along with the development of technology, academic information services are often misused by some irresponsible parties that can cause threats. To prevent these things from happening, it is necessary to know the extent of governance of higher education academic information system security by evaluating. So the research was conducted to determine the maturity of the security of Higher Education academic information service security by using the COBIT 5 framework in the DSS05 domain. The DSS05 domain in COBIT 5 is a good framework for use in implementing and evaluating the security of academic information services. Meanwhile, to determine the achievement of the evaluation of the security level of academic information systems, the Indonesian e-government ranking (PEGI) method is required. The combination of the COBIT 5 framework in the DSS05 domain using the PEGI method in academic information security service is able to provide a level of achievement in the form of Customer Value. The results of the COBIT 5 framework analysis of the DSS05 domain using the PEGI method get a score of 3.50 so that the quality of academic information service security evaluation achievement is at a very good level. At this level, universities are increasingly open to technological development. Higher education has applied the concept of quantification in every process, and has always been monitored and controlled for its performance in the security of academic information systems.
PENERAPAN MODEL-MODEL PEMBELAJARAN DAN TEKNOLOGI DI ERA INDUSTRI 4.0 DI SEKOLAH DASAR Sumargiyani, Sumargiyani; Yanto, Iwan Tri Riyadi; Hamzah, Romelan
Jurnal Berdaya Mandiri Vol 3, No 1 (2021): Jurnal Berdaya Mandiri (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (230.447 KB) | DOI: 10.31316/jbm.v3i1.1264

Abstract

Era revolusi industri 4.0 mengalihkan peralatan yang bersifat tradisional menuju alat – alat yang serba digital. Penyuluhan mengenai model –model pembelajaran dan teknologi dalam pembelajaran dilakukan di SD Muhammadiyah Mertosanan yang  bertujuan untuk memberi wawasan kepada guru-guru SD Muhammadiyah Mertosanan mengenai berbagai macam model pembelajaran dan berbagai teknologi yang berkaitan dengan pembelajaran. Metode yang digunakan untuk mencapai tujuan tersebut adalah penyuluhan yang dilakukan secara on line. Hasil yang diperoleh dari pelaksanaan kegiatan ini adalah mendapat respon yang positip dari para peserta pengabdian dengan banyaknya pertanyaan-pertanyaan yang diajukan dan adanya masukan untuk diadakan kegiatan pengabdian lanjutan.
Fast Building Identification Using Fuzzy Soft Set Based on Rapid Visual Building (RVS) Sari, Sely Novita; Prastowo, Rizqi; Yanto, Iwan Tri Riyadi; Cengiz, Korhan; Ozyurt, Basak; Topac, Tuna
International Journal of Hydrological and Environmental for Sustainability Vol 1, No 2 (2022): International Journal of Hydrological and Environmental for Sustainability
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1249.556 KB) | DOI: 10.58524/ijhes.v1i2.87

Abstract

Building damage can be caused by disasters such as earthquakes, landslides, etc. To minimize the fatality, the identification of buildings is needed to know the condition of buildings and whether the construction of buildings is able to endure if the disasters happen. This research uses the Rapid Visual Building (RVS) method to identify the building condition. The data are collected from  Kalirejo, Kulon Progo. The survey is conducted by taking a simple building evaluation form (typical of the walls ) based on RVS data. The field assessment results are distinguished into several factors that affect the condition of typical building walls: the foundations, structures, walls, and roofs of the 11 categories on the assessment form. From the data obtained, it is used to classify the building condition using Fuzzy Soft Set. The results show that the classification has been made with good performance in terms of accuracy, precision and time response. The accuracy and recall are close to 100% with above 50% of prevision average and time response is quite 0.0051 second. Thus, it can be used to  predict the condition of buildings accurately.