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Faktor Faktor Mempengaruhi Keberhasilan Intelegensi Febrianti, Annisa; Auni, Khofifah Al; Hasibuan, Muhammad Basir; Putri, Saskia Amanda; Sabiru, Tri; Panggabean, Hadi Saputra
Journal of Humanities Education Management Accounting and Transportation Vol 2, No 1 (2025): Februari 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/hemat.v2i1.5049

Abstract

Keberhasilan intelegensi individu dipengaruhi oleh berbagai faktor eksternal dan internal yang saling berinteraksi. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor utama yang memengaruhi keberhasilan intelegensi, yaitu lingkungan, motivasi, dan pengalaman hidup. Penelitian ini dilakukan dengan pendekatan kualitatif menggunakan metode studi pustaka (library research). Sumber data berasal dari buku, jurnal ilmiah, dan artikel yang relevan dengan topik penelitian. Analisis data dilakukan secara deskriptif-kualitatif untuk mengeksplorasi interaksi antara faktor-faktor tersebut. Hasil penelitian menunjukkan bahwa lingkungan sosial, dukungan keluarga, akses terhadap pendidikan, serta motivasi intrinsik dan ekstrinsik memiliki peran signifikan dalam keberhasilan intelegensi. Pengalaman hidup, baik positif maupun negatif, turut memengaruhi pola pikir individu dalam menghadapi tantangan dan mencapai tujuan. Kesimpulannya, keberhasilan intelegensi bersifat multifaset dan dipengaruhi oleh interaksi dinamis dari faktor-faktor tersebut.
Uji Signifikansi Distribusi T Sabiru, Tri; Al ‘Auni, Khofifah; Panggabean, Hadi Saputra
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 2 (2025): July 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i2.6756

Abstract

The t-Student distribution is an important tool in statistical analysis, especially for hypothesis testing and determining confidence intervals on small samples. Introduced by William Sealy Gosset, this distribution excels at accommodating greater uncertainty than the normal distribution, making it ideal when the population standard deviation is unknown. This research uses the literature study method to explore the characteristics of the t distribution and its applications in various fields, including psychology, medical, and education. The t-test procedure involves setting the hypothesis, calculating the t value, and determining the critical value, which helps the researcher in making statistical decisions. The t-test results provide significant insights into the differences between groups and relevance in designing more effective teaching strategies. Further research is needed to explore the potential of the t distribution in wider applications and develop more innovative methods of analysis.
Uji Signifikansi Distribusi T Sabiru, Tri; Al ‘Auni, Khofifah; Panggabean, Hadi Saputra
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 2 (2025): July 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i2.6756

Abstract

The t-Student distribution is an important tool in statistical analysis, especially for hypothesis testing and determining confidence intervals on small samples. Introduced by William Sealy Gosset, this distribution excels at accommodating greater uncertainty than the normal distribution, making it ideal when the population standard deviation is unknown. This research uses the literature study method to explore the characteristics of the t distribution and its applications in various fields, including psychology, medical, and education. The t-test procedure involves setting the hypothesis, calculating the t value, and determining the critical value, which helps the researcher in making statistical decisions. The t-test results provide significant insights into the differences between groups and relevance in designing more effective teaching strategies. Further research is needed to explore the potential of the t distribution in wider applications and develop more innovative methods of analysis.