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Trace Matriks Simetris Berbentuk Khusus 6×6 Berpangkat Bilangan Bulat Siti Rugayah; Daz Vholasky Anggraini; Mutiara Praptasari; Theysa Sahlani Pratiwi
AL-MIKRAJ Jurnal Studi Islam dan Humaniora (E-ISSN 2745-4584) Vol. 5 No. 2 (2025): AL-Mikraj Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v5i2.6994

Abstract

Suppose is a special symmetric matrix of order 6×6 with integer powers, where the entries are real number elements. To obtain the general form of the trace of the matrix by determining the general form of the matrix A_n^6 where the rank of the matrix is ​​first sought from the power of two to eleven and the power of negative two to negative eleven. Then guess the general formula for the exponent of the matrix with positive integer powers which is proven by mathematical induction and with the same steps guess the formula for the exponent of the matrix with negative integer powers which will be proven by the matrix inverse rule. So that the result is obtained, namely the general form of the trace of the matrix and is proven by the definition of trace along with examples of applications of the trace matrix.
Pengaruh ROE Terhadap Nilai Perusahaan: Studi Empiris pada Perusahaan Jakarta Islamic Index (JII) Periode 2019-2021 Mutiara Praptasari; Daz Vholasky Anggraini; Theysa Sahlani Pratiwi
Tamilis Synex: Multidimensional Collaboration Analysis of the Influence of Performance on Company Value and Purchasing Decisions in the Digital Er
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/tls.v2i1.526

Abstract

The purpose of this study is to analyze the effect of ROE on company value in the JII group for the 2019-2021 period. Using a quantitative approach to analyze the relationship between ROE and company value as measured by the PER in companies in the JII for the 2019-2021 period. The analysis techniques used include multiple linear regression tests, t-tests, coefficient of determination (R²) tests, and correlation tests to measure the strength of the relationship between variables. The results show that ROE has a significant and positive effect on company value, with most of the PER variability explained by ROE. The results of the analysis show that ROE has a significant and positive effect on company value as measured by PER. Companies with high ROE, such as Unilever Indonesia and Indofood CBP, have high PERs, reflecting investor confidence in the prospect of profit growth. Conversely, companies with lower ROEs such as Vale Indonesia have lower PERs, indicating a more cautious market view. Although ROE has a strong influence, other factors such as macroeconomic conditions, industry prospects, and sharia compliance also affect company value.
Pengaruh Literasi Digital terhadap Etika Penggunaan Artificial Intelligence pada Mahasiswa Perguruan Tinggi Yusuf Unggul Budiman; Ahmad Jurnaidi Wahidin; Daz Vholasky Anggraini
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7479

Abstract

The development of Artificial Intelligence (AI) in higher education has transformed the way students seek information, complete assignments, and understand academic materials. However, AI use also raises ethical issues, including plagiarism, overreliance on instant answers, and a lack of transparency in acknowledging AI assistance. This study aims to analyze the effect of digital literacy on the ethical use of AI among university students. A quantitative survey method was employed. Data were collected using a 1–5 Likert-scale questionnaire from 125 respondents, with 119 complete responses analyzed. Digital literacy was measured using 12 items, while ethical AI use was measured using 12 items. Data were analyzed using descriptive statistics, validity testing, reliability testing, correlation, and simple linear regression. The results show that digital literacy has a positive and significant effect on ethical AI use. The correlation coefficient of 0.638 indicates a strong relationship, while the coefficient of determination of 0.406 indicates that digital literacy explains 40.6% of the variation in ethical AI use. The regression equation is Y = 1.196 + 0.706X. These findings indicate that students with higher digital literacy tend to use AI more ethically, responsibly, and transparently. This study recommends strengthening digital literacy programs with an emphasis on AI ethics in higher education.