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All Journal MUST: Journal of Mathematics Education, Science and Technology Jurnal Varian SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
Naufal Ramadhan Al Akhwal Siregar
Universitas Airlangga
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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Mask Compliance Modeling Related COVID-19 in Indonesia Using Spline Nonparametric Regression Citra Imama; M. Haykal Adriansyah; Hadi Prayogi; Ferdiana Friska Rahmana Putri; Naufal Ramadhan Al Akhwal Siregar; Alfredi Yoani; Fariz Mardianto
Jurnal Varian Vol 5 No 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i2.1895

Abstract

Until now, Coronavirus disease (COVID-19) has become a concern for Indonesia because of its significant development and impact on various sectors of life and hampering the target of achieving Sustainable Development Goals (SDGs). The achievements targeted in the SDGs, such as reducing poverty, hunger, and many more are very difficult to realize in the current pandemic conditions. The uncertain conditions of the pandemic made the government need some new ideas for consideration in creating policies to encourage sustainable development in this situation. This article covers modeling the effect of achieving the second dose of vaccination and the total cases of COVID-19 cases, which are often considered the reason for general negligence in complying with health protocols, especially wearing masks. This research was conducted using spline nonparametric regression because of its flexibility to handle uncertain data patterns. The results of this study are truncated spline nonparametric regression with 3 knots that produce a R-sq equal to 69.952%. Based on the results, the second dose vaccination coverage variables and the total COVID-19 cases together affect mask compliance. This result is expected to be a benchmark for the government to handle COVID-19 and efforts to achieve the SDGs.
Peningkatan Kualitas Guru SMP di Kabupaten Kediri dalam Penyusunan Soal AKM melalui Pendampingan Intensif Sediono Sediono; M. Fariz Fadillah Mardianto; Siti Maghfrotul Ulyah; Christopher Andreas; Helda Urbhani Rosa; Naufal Ramadhan Al Akhwal Siregar
MUST: Journal of Mathematics Education, Science and Technology Vol 6, No 2 (2021): DECEMBER
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v6i2.10178

Abstract

Riset yang dilakukan Organization for Economic Cooperation and Development (OECD) pada tahun 2018 menunjukkan bahwa kemampuan literasi dan matematika siswa di Indonesia cukup rendah. Kebijakan Ujian Nasional (UN) sebagai alat ukur evaluasi kualitas pendidikan di Indonesia dinilai perlu dievaluasi. Untuk itu, pemerintah menetapkan kebijakan baru pengganti UN yaitu Asesmen Kompetensi Minimum (AKM) dan survei karakter yang mulai diterapkan tahun 2021. Namun, sebagian besar guru belum memiliki wawasan yang cukup mengenai AKM dan survei karakter. Oleh karena itu, diadakan kegiatan workshop dan pendampingan intensif mengenai peningkatan kompetensi guru dalam memahami dan merancang soal berbasis AKM kategori literasi, numerasi, dan survei karakter. Dalam hal ini, sasaran kegiatan tersebut adalah guru Matematika dan IPA tingkat SMP di Kabupaten Kediri. Lebih lanjut, kemampuan seluruh guru diukur sebelum dan sesudah mengikuti kegiatan. Melalui pengujian hipotesis median dengan uji Wilcoxon pada dua sampel berpasangan, diperoleh kesimpulan bahwa terjadi peningkatan kompetensi yang signifikan pada seluruh peserta kegiatan dalam hal pemahaman, perancangan soal AKM kategori literasi, numerasi, dan survei karakter yang masing – masing meningkat sebesar 1.5; 31.5; 25.5; dan 26.5 poin. Melalui kegiatan ini, diharapkan kompetensi guru bertambah guna mendukung peningkatan kualitas pendidikan di Indonesia yang merupakan target Sustainable Development Goals (SDGs).
Modelling Of Coronary Heart Disease Risk Using Penalized Spline Semiparametric Logistic Regression Based On Hypertension History And Fatty Food Consumption Naufal Ramadhan Al Akhwal Siregar; Nur Chamidah; Marisa Rifada
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol. 15 No. 1 (2026): Volume 15 Nomor 1 (Maret 2026)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/ja9m9g46

Abstract

Coronary heart disease (CHD) remains a critical global health challenge, necessitating precise statistical modeling to unravel its complex risk factors. This study applies a binary semiparametric logistic regression model with a penalized spline estimator (SLR-PS) to investigate these determinants effectively. The model achieved a classification accuracy of 70.45% and a promising sensitivity of 77.8%. In clinical settings, this sensitivity is paramount as it ensures the accurate identification of true positive cases, minimizing the risk of undiagnosed severe conditions. The findings unveil a significant nonlinear effect of fatty food intake on CHD risk, emphasizing the critical role of dietary control. Parametrically, individuals with a history of hypertension are found to be 4.641 times more likely to experience CHD compared to their counterparts, while each incremental unit of fatty food intake is associated with a 1.8% increase in CHD odds. These results highlight the urgency of managing hypertension and reducing dietary fat to mitigate cardiovascular risks, directly contributing to the advancement of Sustainable Development Goal (SDG) 3: Good Health and Well-Being. Future research is recommended to expand this framework by incorporating physical activity, genetic predisposition, and stress to further enhance predictive accuracy and support evidence-based preventive strategies.
Co-Authors Alfredi Yoani Andreas, Christopher Citra Imama Fariz Mardianto Ferdiana Friska Rahmana Putri Hadi Prayogi Helda Urbhani Rosa M. Fariz Fadillah Mardianto M. Haykal Adriansyah Marisa Rifada Nur Chamidah Sediono, Sediono Siti Maghfrotul Ulyah