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All Journal Jurnal Keperawatan Jurnal Peduli Masyarakat Knowbase : International Journal of Knowledge in Database The Indonesian Journal of Computer Science
Guci, Asriwan
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Computer Science & IT Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Other

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Education model on SMS gateway on blood sugar levels of diabetes mellitus patients Febriyanti, Febriyanti; Yusri, Viki; Guci, Asriwan
Jurnal Keperawatan Vol. 14 No. 01 (2023): January
Publisher : University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jk.v14i01.23338

Abstract

Introduction: Diabetes has become a global epidemic over the last two decades, the prevalence has doubled, from 4.6% to 9.3% in the population aged 20-79 years. Based on data from the International Diabetes Federation (IDF) 2019, it is estimated that 463 million people in the above age group live with diabetes of which 90% Diabetes, Indonesia faces the same diabetes threat as the world, within five years. West Sumatra is at number 21 out of 34 provinces with diabetes cases. Based on data from the Padang City Health Office in 2020, from 23 health centers in Padang City, Andalas Health Center is the highest coverage of type 2 diabetes mellitus, which is 1017 people. Of the 10 sub-districts in the Andalas Community Health Center working area, Jati sub-district is the highest case of diabetes mellitus. Good blood sugar control is one of the important factors and has been shown to reduce the risk of complications in people with diabetes, to achieve good blood glucose control, holistic management is needed including education, education with an SMS gateway approach can provide continuous and continuous information. Objectives: see the effect of SMS gateway-based education model on blood sugar levels of diabetics. Methods:  Pre-experiment using the One Group Pretest-Posttest design approach. Data analysis using Paired T-test sample. Results: The results showed that there was an effect of education model based on sms gateway based education model on blood sugar levels of diabetics with p-value = 0.002. Conclusions: SMS gateway-based education model affects blood sugar levels of diabetics.
Implementasi Akupresur dan Digitalisasi Layanan Posyandu Lansia Desnita, Ria; Amelia, Weny; Guci, Asriwan; Efendi, Wulan Sani; Fatrisia, Ticy
Jurnal Peduli Masyarakat Vol 6 No 4 (2024): Jurnal Peduli Masyarakat: Desember 2024
Publisher : Global Health Science Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/jpm.v6i4.4735

Abstract

Upaya pemerintah dalam memberikan pelayanan kesehatan lansia adalah melalui Posyandu. Penyelenggaraan Posyandu lansia digerakkan oleh kader melalui Program Puskesmas. Tujuan kegiatan ini adalah untuk mengoptimalkan pelayanan Posyandu Lansia dan meningkatkan kesehatan lansia. Mitra dalam kegiatan Pengabdian kepada masyarakat ini adalah kader Posyandu Lansia di Kelurahan Korong Gadang, Kuranji, Padang. Permasalahan yang dihadapi mitra yaitu tingginya jumlah lansia dengan penyakit degeneratif di Posyandu, belum optimalnya peran kader dalam pelayanan Posyandu lansia, belum tersedianya fasilitas penunjang kegiatan Posyandu lansia dan pencatatan data lansia masih dilakukan secara manual. Pengendalian penyakit degeneratif pada lansia dapat dilakukan dengan pemberian asuhan mandiri akupresur. Solusi permasalahan yang diberikan adalan melalui pembuatan sistem aplikasi pencatatan data lansia, pelatihan kader, pemberian bantuan alat kesehatan serta pendampingan pada kader dalam memberikan pelayanan kesehatan lansia. Kegiatan pengabdian kepada masyakarak telah dilaksanakan pada tanggal 13 September – 29 Oktober 2024 dengan tatap muka langsung. Hasil dari evaluasi kegiatan menunjukkan bahwa tercapainya peningkatan pengetahuan dan keterampilan mitra, meningkatnya kemampuan manajemen mitra. Diharapkan kader dapat menjalankan peran sebagai garda utama dalam pelayanan kesehatan lansia di masyarakat.
Data Mining Analysis to Predict Student Skills Using Naïve Bayes Method Lizar, Yaslinda; Firrizqi, Alya Sahira; Guci, Asriwan; Sunadi, Joko
Knowbase : International Journal of Knowledge in Database Vol. 3 No. 2 (2023): December 2023
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v3i2.7481

Abstract

The possession of specific skills by students not only has a positive impact on the students themselves but also on the Study Program within a Faculty and the University as a whole. However, Study Programs sometimes face difficulties in determining the skills of numerous students even after they have completed 7 semesters of study. Therefore, a method to extract available data in order to determine student skills quickly and accurately is essential. This research aims to apply a data mining method to predict student skills in the Information Systems Study Program at UIN Imam Bonjol Padang. The study focuses solely on predicting student skills in the fields of data processing and programming. The method employed in this data mining analysis is the Naïve Bayes method. Data will be collected from student course grades related to data processing and programming. The data will be processed using an application and subsequently tested using a Confusion Matrix. The research results indicate that predicting the determination of student skills in the Information Systems Study Program at UIN Imam Bonjol can be achieved using the Naïve Bayes algorithm, which yielded a Naïve Bayes model accuracy of 93%, precision of 81%, and recall of 81%. The obtained model can be implemented in the form of an application to determine decision-making strategies for students.
Tren Global Penelitian Tentang Digital Twin: Analisis Bibliometrik Lizar, Yaslinda; Mal Novizam, Defa; Butar-Butar, Mhd Sufiananda; Guci, Asriwan
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3513

Abstract

Penelitian ini bertujuan untuk menganalisis perkembangan publikasi ilmiah bidang digital twin. Metode penelitian adalah kajian bibliometrik terhadap 16.504 artikel jurnal internasional terindeks Scopus periode 2014-2023. Hasil menunjukkan terjadi peningkatan publikasi yang signifikan dalam satu dekade terakhir, didominasi oleh Tiongkok, Jerman, Amerika Serikat, Inggris dan Italia. Sebagian besar publikasi adalah conference papers dan articles di bidang Engineering dan Computer Science. Berdasarkan analisis kata kunci, tema utama meliputi smart systems, machine learning, cloud computing, augmented reality, automation, dan big data. Kesimpulannya, antusiasme peneliti terhadap digital twin tercermin dari lonjakan publikasi global. Hal ini diperkirakan mendorong perluasan riset digital twin ke berbagai disiplin di masa depan.
Data Mining Analysis to Predict Student Skills Using Naïve Bayes Method Lizar, Yaslinda; Firrizqi, Alya Sahira; Guci, Asriwan; Sunadi, Joko
Knowbase : International Journal of Knowledge in Database Vol. 3 No. 2 (2023): December 2023
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v3i2.7481

Abstract

The possession of specific skills by students not only has a positive impact on the students themselves but also on the Study Program within a Faculty and the University as a whole. However, Study Programs sometimes face difficulties in determining the skills of numerous students even after they have completed 7 semesters of study. Therefore, a method to extract available data in order to determine student skills quickly and accurately is essential. This research aims to apply a data mining method to predict student skills in the Information Systems Study Program at UIN Imam Bonjol Padang. The study focuses solely on predicting student skills in the fields of data processing and programming. The method employed in this data mining analysis is the Naïve Bayes method. Data will be collected from student course grades related to data processing and programming. The data will be processed using an application and subsequently tested using a Confusion Matrix. The research results indicate that predicting the determination of student skills in the Information Systems Study Program at UIN Imam Bonjol can be achieved using the Naïve Bayes algorithm, which yielded a Naïve Bayes model accuracy of 93%, precision of 81%, and recall of 81%. The obtained model can be implemented in the form of an application to determine decision-making strategies for students.
Co-Authors Butar-Butar, Mhd Sufiananda Efendi, Wulan Sani Fatrisia, Ticy Febriyanti Febriyanti febriyanti febriyanti Firrizqi, Alya Sahira Lizar, Yaslinda Mal Novizam, Defa Ria Desnita Sunadi, Joko Weny Amelia, Weny