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SOSIALISASI ANIMASI UPIN IPIN VERSI BAHASA INGGRIS DI SD IT ALBIRRU PEKANBARU Indah Muzdalifah; Susi Handayani; Rizki Novedra
J-ABDI: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 12: Mei 2023
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/jabdi.v2i12.5575

Abstract

Di televisi ada tayangan animasi Upin Ipin di salah satu stasiun swasta berbahasa Melayu. Sedangkan di YouTube animasi Upin dan Ipin dalam bahasa Inggris. Pengabdian Masyarakat ini mencoba menjadikan animasi youtube Upin Ipin sebagai media pembelajaran bahasa Inggris khususnya di SD Al Birru. Permasalahan yang ditemukan adalah penggunaan gadget yang belum mengandung unsur edukatif pada anak dan remaja. Solusi dari permasalahan tersebut adalah penggunaan gadget sebagai media pembelajaran bahasa Inggris di rumah. Dengan demikian, orang tua dan guru bisa bersinergi agar kecocokan anak dengan gadget bisa diterapkan ke arah yang lebih positif. Kegiatan ini mengandung unsur penggunaan gadget yang dipegang anak di rumah untuk menonton video animasi Upin Ipin versi bahasa Inggris karena sifat anak adalah meniru pengucapan. Ketika anak-anak mendengar percakapan ringan dan kosakata bahasa Inggris yang biasa ditemukan dalam kehidupan sehari-hari, maka pembiasaan ini akan menjadi kebiasaan sehingga bahasa Inggris bukan sesuatu yang asing lagi. Adapun hasil dari kegiatan ini 94% orang tua menyatakan penggunaan aplikasi youtube yang dapat mendownload video animasi upin ipin versi bahasa inggris dapat membantu anak dalam prosesnya.
Feature Selection in Naïve Bayes for Predicting ICU Needs of COVID-19 Patients Taslim Malano Taslim; fajrizal; Susi Handayani; Dafwen Toresa
Indonesian Journal of Computer Science Vol. 12 No. 3 (2023): Indonesian Journal of Computer Science Volume 12. No. 3 (2023)
Publisher : STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i3.3211

Abstract

COVID-19 is a global pandemic that requires a coordinated global response in all healthcare and national healthcare systems. Identifying patients at high risk of contracting the COVID-19 virus is crucial to increasing awareness before patients become further infected by the virus, which can cause severe respiratory illnesses requiring specialized care in intensive care units (ICUs). This study aims to predict the need for ICUs in patients infected with the COVID-19 virus. The predicted ICU requirements serve as a reference for hospitals to meet the ICU needs of COVID-19 patients. The prediction of ICU requirements for COVID-19 patients is performed using the Naïve Bayes algorithm, and particle swarm optimization (PSO) used to obtain the best accuracy values from Naïve Bayes. In the initial testing, Naïve Bayes without feature selection resulted in an accuracy rate of 74.75%. Testing Naïve Bayes+PSO by increasing the number of PSO generations shows that as the number of generations in PSO increases, the accuracy rate also increases. Testing Naïve Bayes+PSO with 3000 generations and a population size of 20 shows an increase in the accuracy rate to 80.95%. Testing Naïve Bayes+PSO by increasing the population size to 40 with 1000 generations for each population size shows an increase in the accuracy rate to 80.70%.
Digitalisasi Pengelolaan Pustaka Sekolah Dafwen Toresa; Taslim; Susi Handayani; Edriyansyah; Rometdo Muzawi
SATIN - Sains dan Teknologi Informasi Vol 9 No 1 (2023): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (513.877 KB) | DOI: 10.33372/stn.v9i1.989

Abstract

Along with the development of science and the globalization of information that demands the creation of an all-computerized state. At SMA Negeri 4 Tualang, Siak Regency, the process of processing library data to making reports still uses manual bookkeeping. This can cause the process of searching for book data, member data and book borrowing data to take a long time and not to mention if the data is lost so it cannot be used again. Library applications are made according to user needs using the PHP programming language with MySQL database storage and Waterfall modeling. This library application has been tested with the black box method with 100% results then implemented and measured with values and measuring indicators as follows: User Satisfaction = 94%, Data Accuracy = 93%, Speed and convenience = 96%, Application and information security = 93 % and Support = 96%. Thus the digitization of library management is very beneficial for library managers and students as users at SMAN 4 Tualang