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All Journal International Journal of Quantitative Research and Modeling UNM Journal of Technology and Vocational
Muh. Yahya
Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Physics Social Sciences Other

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EFEKTIVITAS MEDIA PEMBELAJARAN BERBASIS GOOGLE SITESPADA MATERI PEMELIHARAAN KELISTRIKAN KENDARAAN RINGAN DI SMK Ahmad Akbar; Muh. Yahya; Darmawang
UNM Journal of Technology and Vocational Volume 10, Issue 2, May (2026)
Publisher : Program Studi S2 Pendidikan Teknologi dan Kejuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/rb5k6443

Abstract

Penelitian kuasi-eksperimen ini menguji efektivitas media pembelajaran berbasis Google Sites (https://sites.google.com/guru.smk.belajar.id/gearuplearning/home) dalam meningkatkan hasil belajar siswa pada materi pemeliharaan kelistrikan otomotif di SMK Negeri Campalagian, Sulawesi Barat. Menggunakan desain nonequivalent pretest-posttest control group, 67 siswa kelas XI Program Keahlian Teknik Kendaraan Ringan dibagi menjadi kelompok eksperimen (n=33, Google Sites) dan kontrol (n=34, PowerPoint konvensional). Instrumen tes pilihan ganda 25 butir yang mencakup tujuh area kompetensi (kelistrikan dasar otomotif, sistem pengapian, sistem pengisian, sistem starter, sistem penerangan dan sinyal, sistem instrumen dan aksesori, sistem kontrol elektronik) diberikan sebagai pretest dan posttest. Uji independent samples t-test menunjukkan perbedaan yang signifikan secara statistik pada skor posttest (t=9,294, df=65, p<0,001), dengan kelompok eksperimen mencapai rerata skor jauh lebih tinggi (M=79,39, SD=6,08) dibandingkan kelompok kontrol (M=65,38, SD=8,64). Analisis normalized gain menunjukkan peningkatan sedang pada kelompok eksperimen (N-gain=0,58) versus kelompok kontrol (N-gain=0,51). Evaluasi guru mengindikasikan penerimaan sangat positif pada lima dimensi: manfaat pembelajaran (4,99/5,00), kolaborasi (4,95/5,00), integrasi Google (4,89/5,00), aksesibilitas (4,89/5,00), dan kualitas teknis (4,81/5,00). Temuan ini menunjukkan bahwa Google Sites secara signifikan meningkatkan hasil belajar dalam pendidikan teknik otomotif, mendukung Multimedia Learning Theory (Mayer, 2009) dan Connectivism (Siemens, 2005) melalui presentasi konten multimodal, pembelajaran mandiri, asesmen interaktif, dan integrasi mulus dengan ekosistem Google Workspace. Platform ini mengatasi tantangan kunci dalam pendidikan kejuruan: konsep teknis abstrak, waktu praktik terbatas, dan kebutuhan akan sumber belajar yang aksesibel dan fleksibel.
Analysis of Stock Return Volatility of PT Asuransi Multi Artha Guna Tbk Using the GARCH-M Model Muh. Yahya; Kalfin Kalfin; Hisyam Ihsan; Atikafairuq Selviana; Andi Widya Pratiwi Anas
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1334

Abstract

This study aims to analyze the volatility of stock returns of PT Asuransi Multi Artha Guna Tbk using the Generalized Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) model during the 2019–2024 period. The data used in this study are secondary data in the form of daily closing stock prices of AMAG.JK obtained from Yahoo Finance, with a total of 1,466 observations. The analytical stages include the calculation of log returns, stationarity testing using the Augmented Dickey-Fuller (ADF) test, Ljung-Box autocorrelation test, ARCH-LM test, selection of the best GARCH model based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), estimation of the GARCH-M model, conditional volatility analysis, and volatility forecasting. The results indicate that the stock return data of AMAG.JK are stationary and contain ARCH effects, making them appropriate for analysis using the GARCH model. Based on the AIC and BIC criteria, the best model selected is GARCH(1,2). The estimation results of the GARCH(1,2)-M model show that the ARCH and GARCH parameters are statistically significant, indicating the presence of volatility clustering and volatility persistence phenomena in the stock returns of AMAG.JK. However, the risk premium parameter in the GARCH-M model is not statistically significant, implying that conditional volatility does not significantly affect expected stock returns. The volatility forecasting results show that the volatility level of AMAG.JK stock tends to increase gradually in future periods. Overall, the GARCH(1,2)-M model is capable of describing the dynamics of volatility in AMAG.JK stock returns during the research period effectively.
Co-Authors Ahmad Akbar Andi Widya Pratiwi Anas Atikafairuq Selviana Darmawang, Darmawang Hisyam Ihsan Kalfin Kalfin