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Peningkatan Kompetensi AKM Numerasi Guru SMAN 6 Surabaya Melalui Pembelajaran Interaktif sebagai Upaya Mendukung Kualitas Pembelajaran di Kelas Elly Pusporani; Idrus Syahzaqi; Sediono Sediono; Elly Ana; Adinda Tries Melati; Ailsa Shafa Salsabila; Aufa Muhammad Yogi Riyanto; Azizah Dewi Ariyani; Bagas Maulana; Deby Victoria; Ferissa Maulida Ismi; Nurul Fajriah Deswani Sangadji; Rahmat Agung Ibrahim; Sasy Okti Karima
I-Com: Indonesian Community Journal Vol 5 No 3 (2025): I-Com: Indonesian Community Journal (September 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i3.8022

Abstract

Perubahan kurikulum di Indonesia belum memberikan dampak signifikan terhadap peningkatan kompetensi siswa, sehingga pemerintah meluncurkan Asesmen Kompetensi Minimum (AKM) dengan fokus literasi dan numerasi. Di SMAN 6 Surabaya, siswa mengalami kejenuhan dalam pembelajaran numerik sehingga diperlukan upaya pendukung melalui program pengabdian masyarakat. Kegiatan ini bertujuan meningkatkan kompetensi guru dalam merancang pembelajaran numerasi kontekstual berbasis AKM. Metode pelaksanaan meliputi sosialisasi, pelatihan, pendampingan, serta publikasi dan keberlanjutan program selama satu bulan dengan peserta 40 guru. Hasil evaluasi menunjukkan peningkatan skor rata-rata dari 45 (pre-test) menjadi 64 (post-test), serta tersusunnya modul pembelajaran interaktif dan soal AKM Numerasi. Kegiatan ini terbukti mampu meningkatkan kapasitas guru dalam mengimplementasikan strategi pembelajaran numerasi. Ke depannya, guru diharapkan terus mengembangkan kreativitas penyusunan soal, sekolah membentuk community of practice sebagai wadah berkelanjutan, serta dukungan pemerintah diperlukan melalui fasilitas dan kebijakan strategis.
Association Between Serum IL-8 Concentrations and Severity of Knee Osteoarthritis: An Exploratory Cross-Sectional Study Iskak, Iskak; Dewanta, Tunggul Bagus; Santoso, Anna Lewi; Aryanti, Novina; Syahzaqi, Idrus; Njoto, Ibrahim
Jambura Medical and Health Science Journal Vol 5, No 1 (2026): Jambura Medical and Health Science Journal
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jmhsj.v5i1.37399

Abstract

Introduction: Osteoarthritis (OA) is a chronic degenerative disorder of the joints that progresses over time, with inflammation playing a key role in its underlying mechanisms. Interleukin-8 (IL-8), a pro-inflammatory cytokine that participates in immune responses and neutrophil migration, has been associated with the process of cartilage breakdown in OA. This study was conducted to analyze the association between serum IL-8 concentrations and the radiographic severity of knee OA as exploratory evidence to enhance understanding of OA pathophysiology.Method: This exploratory observational research applied a cross-sectional approach in patients diagnosed with knee OA. Seven participants were enrolled through total sampling at the Larasati Pondok Osteoarthritis Elderly Health Center, Faculty of Medicine, Wijaya Kusuma University, Surabaya. Radiographic severity of OA was determined using the Kellgren–Lawrence grading system. Venous blood specimens were obtained to determine serum IL-8 concentrations as an indicator of systemic inflammation.Results: Statistical analysis demonstrated a significant inverse correlation between serum IL-8 concentrations and OA severity (r = −0.866, P = 0.012). These results indicate that IL-8 concentrations in serum are relatively elevated in the early phase of OA and tend to decline as the disease progresses.Conclusion: The findings of this exploratory study indicate that serum IL-8 may represent systemic inflammatory activity during the early stages of knee OA and holds potential as a biomarker candidate for future investigation. Further longitudinal studies involving larger sample sizes are necessary to validate its clinical relevance for OA detection and disease monitoring. Keywords: Cartilage, inflammation, interleukin-8, joint diseases, osteoarthritis, risk factors 
Peran Mahasiswa Pada Program Asistensi Mengajar: Analisis Pemahaman Siswa Kelas 11 Pada Mata Pelajaran Matematika dengan Menggunakan Uji Kruskal-Wallis dan Uji Mann-Whitney Ilham Al Hasri; Idrus Syahzaqi
Jurnal Pendidikan Matematika Vol. 3 No. 1 (2025): November
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v3i1.2199

Abstract

Kegiatan Asistensi Mengajar merupakan bagian dari MBKM yang bertujuan untuk meningkatkan kualitas pendidikan di satuan pendidikan yang dilakukan oleh mahasiswa serta evaluasi hasil pembelajaran dengan tujuan penyusunan strategi pembelajaran berdasarkan tingkat pemahaman siswa. Program Asistensi Mengajar dilakukan pada SMAN 1 Driyorejo dengan beberapa tahapan, yaitu tahap persiapan, pelaksanaan, dan evaluasi. Tahap persiapan meliputi penentuan sekolah mitra dan pengenalan lingkungan sekolah. Tahap pelaksanaan meliputi kegiatan mengajar, non mengajar, dan adminitrasi sekolah. Kegiatan mengajar dilakukan pada ruang kelas dengan pemaparan materi, latihan soal, dan sesi diskusi. Berikutnya, kegiatan non mengajar adalah kegiatan siswa di luar kelas pada lingkup sekolah, seperti upacara dan lomba menyambut hari kemerdekaan. Selanjutnya, kegiatan administratif yang dilakukan adalah melakukan rekap absensi hingga nilai ujian siswa. Tahap evaluasi dilakukan dengan melakukan analisis pada hasil ujian matematika dengan pendekatan nonparametrik dengan menggunakan uji Kruskal-Wallis dan uji Mann-Whitney. Berdasarkan hasil yang diperoleh dari uji Kruskal-Wallis, terdapat perbedaan signifikan pada hasil ujian matematika antar kelas sehingga dilakukan uji lanjutan dengan uji Mann-Whitney. Dari hasil evaluasi, diperlukan beberapa strategi agar materi dapat diterima oleh siswa secara optimal, seperti menyesuaikan tingkat kesulitan materi hingga metode pembelajaran berbasis diskusi.
Analysis of Student Learning Outcomes on Polynomial Topic in Grade XI During the Teaching Assistance Program Idrus Syahzaqi; Syifa Gunawan
Jurnal Pendidikan Matematika Vol. 3 No. 1 (2025): November
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v3i1.2281

Abstract

This study aims to analyze students’ learning outcomes on the polynomial topic during the Teaching Assistance Program conducted in Grade XI. As polynomials represent a foundational concept in upper secondary mathematics, understanding students’ performance provides valuable insights into the effectiveness of instructional practices. This descriptive quantitative research analyzed daily assessment scores from 33 students using statistical measures including minimum, maximum, mean, median, mode, range, and standard deviation. The findings show a moderate performance with an average score of 67.7, a median of 70, and a standard deviation of 7.7. A total of 54.5% of students achieved the minimum mastery criterion, while 45.5% did not, indicating a substantial variation in conceptual understanding. The score distribution also demonstrated clustering around the 68–72 range, suggesting that many students possessed partial comprehension but struggled with deeper algebraic reasoning. These results highlight the need for differentiated instruction, scaffolded learning, and improved feedback mechanisms. The Teaching Assistance Program contributed significantly to the reflective development of teaching skills and provided authentic classroom experience for the pre-service teacher. Overall, this study emphasizes the importance of varied teaching approaches to enhance student mastery of polynomial concepts.
Forecasting Rupiah Exchange Rate Volatility using a Hybrid ARIMA–SVR Model as an Early Warning System to Address Global Dynamics Idrus Syahzaqi; Selvina Cindy Kusumaningrum; Naufal Ainul Hayat; M. Fariz Fadillah Mardianto
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 3 (2026): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i3.38570

Abstract

Exchange rate volatility of the Indonesian Rupiah against the US Dollar has increased due to global uncertainty. This study addresses the limitation of prior research that predominantly relies on single linear or nonlinear models in emerging markets by developing a Hybrid ARIMA SVR approach, thereby enhancing exchange rate predictability to support macroeconomic stability. This study contributing to the advancement of quantitative forecasting methods aligned with SDG 8 and SDG 16 through enhanced financial predictability. This research uses a univariate time-series dataset of weekly Rupiah US Dollar exchange rates obtained from Bank Indonesia, comprising 150 observations from March 2023 to January 2026. Novelty from this research is ARIMA model selected to capture linear temporal dependencies, while SVR is employed to model nonlinear patterns in residuals justifying the hybrid approach as a complementary integration of statistical and machine learning methods. Data preprocessing includes Box-Cox transformation and second order differencing to ensure stationarity, followed by diagnostic tests (Ljung Box, Kolmogorov Smirnov, and ARCH LM). SVR parameters are optimized using grid search to ensure robust model performance. The analysis included visualization, Box–Cox transformation (λ = −1), and second-order differencing to achieve stationarity. Diagnostic tests (Ljung Box, Kolmogorov Smirnov, ARCH LM) confirmed that ARIMA (3,2,0) met model assumptions. ARIMA residuals were subsequently model using SVR, with parameters optimized through grid search, forming the Hybrid ARIMA–SVR model. Results show that the Hybrid ARIMA SVR model outperformed the standalone ARIMA, achieving a lower MAPE. The best performance (MAPE = 0.56%) was obtained using the Radial kernel with ε = 0.2, C = 23, and γ = 28. These findings indicate that integrating linear and nonlinear models improves forecasting accuracy.
MODELING AND SEGMENTATION OF FACTORS AFFECTING HUMAN DEVELOPMENT IN ISLANDS OF JAVA USING FIMIX PLS METHOD WITH MEDIATION EFFECT Muhammad Rosyid Ridho Az Zuhro; Ardi Kurniawan; Dita Amelia; Idrus Syahzaqi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0397-0412

Abstract

Human development is a key indicator used to assess the quality of a country's human resources. Although Indonesia's HDI has experienced a significant increase of 75.02 in 2024, inequality is still a pressing issue, especially in terms of gender representation in the workforce. This study aims to identify the influence of poverty, economic, health, employment and education factors on human development in Java Island by considering gender equality as a mediating variable. The data used in the study is limited to 119 districts/cities in Java Island and sourced from BPS publications, the Health Office and the Education Office. The novelty of this study lies in the use of the Finite Mixture Partial Least Square (FIMIX-PLS) approach with mediation effects which is rarely applied in human development research in Indonesia, as well as allowing the identification of latent population heterogeneity and region-based segmentation. The results of this method reveal two distinct district/city segments in Java, with Segment 1 dominated by the variables in this study that have significant direct and indirect effects through the mediation of gender equality on human development, while Segment 2 has characteristics that emphasize the effect of gender equality. Given these differences in characteristics, it is important that contextual and regional segmentation-based development policies are designed by local and central governments. Statistical segmentation approaches such as FIMIX-PLS make a significant contribution to more targeted policy making. By changing the type of intervention according to specific problems, the government can allocate resources more effectively. This supports the achievement of SDG-10 in reducing inequality.
Prediksi dengan Support Vector Regression dan analisis kelayakan investasi pada harga saham Spotify Mardianto, M. Fariz Fadillah; Ismi, Ferissa Maulida; Nariswari, Anggita; Fatihah, Amelia; Syahzaqi, Idrus
Jurnal Kebijakan Ekonomi dan Keuangan Volume 5 Issue 1, Juni 2026
Publisher : Jurusan Ilmu Ekonomi, Fakultas Bisnis dan Ekonomika, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/JKEK.vol5.iss1.art2

Abstract

Purpose – This study aims to predict the weekly stock price of Spotify Technology SA (SPOT) using Support Vector Regression (SVR) and to evaluate investment feasibility based on Net Present Value (NPV), Internal Rate of Return (IRR), Sharpe Ratio, and Sortino Ratio.Methods – Weekly stock price data from October 2022 to May 2026 (190 observations) were analyzed using SVR with lag selection based on PACF and kernel optimization through two-stage grid search. Investment feasibility was evaluated using NPV, IRR, Sharpe Ratio, and Sortin o Ratio.Findings – The linear kernel SVR achieved the best performance with MAPE of 5.44% (training) and 4.61% (testing). The NPV was positive at USD 19,685.86. However, the IRR of 1.197% per week, Sharpe Ratio of 0.3703, and Sortino Ratio of 17.77 consistently indicate that Spotify stock during the prediction period is not financially viable for investment.Implication – The findings emphasize the importance of combining return- and risk-based measures when evaluating investment feasibility, particularly for high-volatility assets. Originality – Unlike prior studies that focus mainly on forecasting accuracy, this study integrates SVR-based prediction and investment feasibility analysis using NPV, IRR, Sharpe, and Sortino ratios within within a unified framework. AbstrakTujuan – Penelitian ini bertujuan untuk memprediksi harga saham mingguan Spotify Technology SA (SPOT) menggunakan metode Support Vector Regression (SVR) serta mengevaluasi kelayakan investasi berdasarkan Net Present Value (NPV), Internal Rate of Return (IRR), Sharpe Ratio, dan Sortino Ratio. Metode – Data harga saham mingguan periode Oktober 2022 hingga Mei 2026 (190 observasi) dianalisis menggunakan SVR dengan pemilihan lag berdasarkan PACF dan optimasi kernel melalui grid search dua tahap. Temuan – Kernel linear SVR menghasilkan performa terbaik dengan MAPE sebesar 5,44% pada data pelatihan dan 4,61% pada data pengujian. NPV bernilai positif sebesar USD 19.685,86. Namun, IRR sebesar 1,197% per minggu, Sharpe Ratio sebesar 0,3703, dan Sortino Ratio sebesar 17,77 secara konsisten menunjukkan bahwa saham Spotify pada periode prediksi tidak layak secara finansial untuk diinvestasikan.Implikasi – Temuan penelitian menekankan pentingnya mengombinasikan indikator berbasis imbal hasil dan risiko dalam mengevaluasi kelayakan investasi, khususnya pada aset dengan volatilitas tinggi.Orisinalitas – Berbeda dengan penelitian sebelumnya yang terutama berfokus pada akurasi peramalan, penelitian ini mengintegrasikan prediksi berbasis SVR dan analisis kelayakan investasi menggunakan NPV, IRR, Sharpe Ratio, dan Sortino Ratio dalam satu kerangka yang terpadu.