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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi JTAM (Jurnal Teori dan Aplikasi Matematika) SeBaSa: Jurnal Pendidikan Bahasa dan Sastra Indonesia Munazzama Journal of Islamic Management and Pilgrimage
Ramadhanti, Aulia
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Religion Arts Humanities Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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KESEPADANAN MAKNA DALAM TERJEMAHAN LIRIK LAGU LEAD THE WAY KARYA JHENÉ AIKO DAN KITA BISA KARYA ADRIAN WAROUW Praftina, Alinda Tyas; Ramadhanti, Aulia; Salsabiila, Fardha Yoedya; Kusumastuti, Fenty
SEBASA Jurnal Pendidikan Bahasa dan Sastra Vol 7 No 2 (2024): SeBaSa
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/sbs.v7i2.26784

Abstract

This research focuses on the similarity in meaning between the lyrics of the song Bsu (Lead The Way) and Bsa (We Can). This research uses descriptive qualitative research methods. The theory used in this research is J.S.'s category shift theory. Catford (1965). The data used in this research are the lyrics of the song Lead The Way and the lyrics of the song Kita Bisa. The research data source was taken from the DisneyMusicVevo YouTube channel as source language data and the DisneyMusicAsiaVevo YouTube channel as target language data. The results of research on the equivalence of meaning in the translation of the lyrics of the song Lead The Way into Kita can be found in several types of category shifts by the category shift theory by Catford (1965). The types of shifts that occur are intra-system shifts, unit shifts, structure shifts, and class shifts.
Role of Religious Institutions in American to Strengthening Islamic Religion Fauziyah, Nurul; Ismaita, Annisa Natasya; Ramadhanti, Aulia
Munazzama: Journal of Islamic Management and Pilgrimage Vol. 5 No. 1 (2025): June
Publisher : Fakultas Dakwah dan Komunikasi Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/mz.v5i1.18722

Abstract

The United States possesses a strategically significant geographical location, bordered by the Atlantic Ocean to the east and the Pacific Ocean to the west. This unique positioning has made the country a destination for immigrants from various nations, including Muslim communities. This study aims to explore the historical foundations and development of Islam in the United States, particularly through the contributions of religious institutions and communities that promote and strengthen Islamic teachings. The research utilizes a library-based methodology with a qualitative approach, drawing from books, journals, and official reports relevant to the topic. The findings indicate that, while Islam remains a minority religion in America, its number of adherents continues to grow. This phenomenon is closely tied to the active roles played by religious organizations such as CAIR, ISNA, MSA, and FIMA, which support education, advocacy, and interfaith dialogue. Furthermore, global incidents, such as the attacks on September 11, 2001, have served as significant turning points in increasing public interest in Islam. These institutions are crucial in shaping a positive image of Islam within America's diverse society.
Analysis of Geographically Weighted Logistic Regression Models with A Bisquare Weighting Matrix on Poverty Status in West Java Saifudin, Toha; Chamidah, Nur; Aldawiyah, Najwa Khoir; Marthabakti, Citrawani; Ramadhanti, Aulia; Nahar, Muhammad Hafidzuddin; Muzakki, Naufal
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36315

Abstract

This research addresses the first Sustainable Development Goal and aims to analyze poverty status in West Java Province, which has the second highest number of poor people in Indonesia. The study employs Geographically Weighted Logistic Regression (GWLR) and compares it with global logistic regression. Influential variables include GDP, unemployment, population density, access to safe water, and roof type (bamboo/wood). Results show that 55.6% of regions are classified as poor, with the GWLR model using a Fixed Bisquare kernel achieving 81.4% accuracy, outperforming global logistic regression at 66.7%. Significant variables vary by region: unemployment rate in Bogor, Depok, and Bekasi; population density in Bekasi, Karawang, and Purwakarta; water access in Sukabumi; and roof type in Indramayu and Bogor. These spatial variations suggest that poverty reduction requires a region-specific approach. Consequently, policies should be formulated considering the priorities and characteristics of each region in West Java Province.
Modelling Factors Affecting the Middle Income Trap in Indonesia Using Generalized Additive Models (GAM) Amelia, Dita; Suliyanto, Suliyanto; Zhafira, Azizah Atsariyyah; Ramadhanti, Aulia; Suyono, Billy Christandy; Hizbullah, Firqa Aqila
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.35119

Abstract

Indonesia is currently facing a significant challenge known as the Middle Income Trap (MIT), a condition where economic growth stagnates after reaching middle-income status, hindering progress toward becoming a high-income country. This study aims to identify and model the socio-economic factors influencing MIT at the provincial level in Indonesia during the 2020–2023 period. The Generalized Additive Model (GAM) is employed to estimate nonlinear relationships between predictors and the response variable while capturing complex patterns in panel data. GRDP per capita is used as an indicator of MIT, with six predictor variables: life expectancy, poverty rate, informal employment share, secondary education completion rate, food insecurity prevalence, and population density. The results showed that the best model was obtained based on the minimum GCV and AIC values of the Gaussian family with an identity link function and 5 knot points with the highest correlation of 99,9%. Five variables show nonlinear effects, while food insecurity exhibits a significant negative linear impact. The findings provide a valuable reference for designing inclusive and adaptive eco nomic policies based on each region’s socio-economic characteristics to mitigate MIT risks and also supports the achievement of Sustainable Development Goal (SDG) 8, which promotes decent work and sustained economic growth.
Comparing MARS and Binary Logistic Regression to Modelling Hepatitis C Cases using the SMOTE Balancing Method Chamidah, Nur; Ramadhanti, Aulia; Ramadhani, Azzah Nazhifa Wina; Syahputra, Bimo Okta; Ariyawan, Jovansha; Kurniawan, Ardi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.33196

Abstract

Hepatitis is an inflammatory liver disease caused by viral infection and remains a major global public health concern, responsible for approximately 1.4 million deaths annually. Egypt is among the countries with the highest prevalence of Hepatitis C. To address this issue and support Goal 3 of the Sustainable Development Goals (SDGs), this study applies a quantitative approach using secondary data to analyze factors influencing Hepatitis C infection in Egypt. Two statistical models Binary Logistic Regression and Multivariate Adaptive Regression Splines (MARS) were compared, with the SMOTE method implemented to correct class imbalance. The dataset consisted of 608 patient observations, initially imbalanced at a ratio of 86.5:13.5, and were balanced to 52.6:47.4 after SMOTE application. The results revealed that the MARS model demonstrated superior predictive performance compared to binary logistic regression. All independent variables were found statistically significant (p < 0.05), except sex. Additionally, all odds ratios were less than 1, indicating a lower probability of Hepatitis C infection relative to non-infection. These findings highlight the relevance of statistical modeling and data-driven strategies in supporting preventive health measures. 
Co-Authors Aldawiyah, Najwa Khoir Ardi Kurniawan Ariyawan, Jovansha Dita Amelia Hizbullah, Firqa Aqila Ismaita, Annisa Natasya Kusumastuti, Fenty Marthabakti, CitraWani Muzakki, Naufal Nahar, Muhammad Hafidzuddin Nur Chamidah Nurul Fauziyah, Nurul Praftina, Alinda Tyas Ramadhani, Azzah Nazhifa Wina Salsabiila, Fardha Yoedya Suliyanto Suliyanto Suyono, Billy Christandy Syahputra, Bimo Okta Toha Saifudin Zhafira, Azizah Atsariyyah