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All Journal Wahana Matematika dan Sains Jurnal Salaka : Jurnal Bahasa, Sastra, dan Budaya Indonesia
Muhammad Fazra
Universitas Negeri Medan

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Dependence on the Use of ChatGPT and Its Impact on Statistics Students' Linguistic Literacy in Compiling Data Analysis Reports Menggie Orlanda Br Simarmata; Nazla Dia Maharani; Riris Apriani Simarmata; Wilda Rahmadani; Widi Aulia; Muhammad Fazra; Hendra Kurnia Pulungan
Jurnal Salaka : Jurnal Bahasa, Sastra, dan Budaya Indonesia Vol. 8 No. 1 (2026): Jurnal Salaka : Jurnal Bahasa, Sastra, dan Budaya Indonesia
Publisher : Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jsalaka.v8i1.60

Abstract

The rapid development of generative artificial intelligence, particularly ChatGPT, has significantly influenced higher education, especially in student academic writing activities. However, research specifically examining the relationship between ChatGPT dependency and student language literacy in preparing data analysis reports remains limited. This study aimed to analyze the relationship between dependency on ChatGPT usage and the language literacy of Statistics students in preparing data analysis reports. A quantitative approach with a survey strategy was employed. The population consisted of 265 active Statistics students at Universitas Negeri Medan from the 2023, 2024, and 2025 cohorts, with 66 respondents selected through purposive sampling. Data were collected using a digital questionnaire via Google Forms, measuring ChatGPT dependency (7 items) and language literacy (6 items) on a 4-point Likert scale. Descriptive statistical analysis and Pearson correlation tests were conducted using RStudio. The results showed that ChatGPT dependency was in the Agree category (mean = 2.70), with students demonstrating selective use by disagreeing with directly copying AI output (1.91). Language literacy was also in the Agree category (mean = 2.98), although confidence in independent writing remained low (2.62). The Pearson correlation test revealed no significant relationship between ChatGPT dependency and language literacy (r = -0.002; p = 0.9903 > 0.05). The study concludes that AI dependency does not inherently weaken language literacy, and educational efforts should focus on critical AI usage rather than prohibition. Keywords: ChatGPT dependency, language literacy, generative artificial intelligence, academic writing, Statistics students.
Penerapan Model Regresi Spasial pada Data Tingkat Pengangguran Terbuka di Seluruh Provinsi Indonesia Naomi Sitompul; Riris Apriani Simarmata; Angelica Carolina Tambunan; Aura Patresia Naibaho; Lirana Sapriani Gulo; Muhammad Fazra; Hanna Dewi Marina Hutabarat
Wahana Matematika dan Sains: Jurnal Matematika, Sains, dan Pembelajarannya Vol. 20 No. 1 (2026): April 2026
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/wms.v20i1.113559

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh Upah Minimum Provinsi (UMP) dan Indeks Pembangunan Manusia (IPM) terhadap Tingkat Pengangguran Terbuka (TPT) di seluruh provinsi Indonesia tahun 2024 menggunakan pendekatan regresi spasial. Data sekunder diperoleh dari Kemnaker dan BPS tahun 2024, mencakup 38 provinsi dengan data spasial berbasis shapefile dari LapakGIS. Metode analisis yang digunakan meliputi uji autokorelasi spasial dengan Indeks Moran's I, matriks pembobotan spasial berbasis k-nearest neighbor (KNN), serta perbandingan tiga model regresi: Ordinary Least Squares (OLS), Spatial Autoregressive Model (SAR), dan Spatial Error Model (SEM). Hasil pengujian Moran's I menunjukkan tidak adanya autokorelasi spasial yang signifikan pada data TPT (p-value = 0,1202 pada k = 2), sehingga model OLS terpilih sebagai model terbaik berdasarkan nilai AIC terendah dan R² sebesar 29,26%. Hasil estimasi OLS menunjukkan bahwa UMP berpengaruh positif dan signifikan terhadap TPT (p = 0,0013), mengindikasikan bahwa kenaikan upah minimum cenderung meningkatkan angka pengangguran melalui mekanisme efisiensi tenaga kerja oleh pelaku usaha. Sementara itu, IPM menunjukkan pengaruh positif yang tidak signifikan secara statistik. Implikasi penelitian ini menegaskan perlunya kebijakan penetapan upah minimum yang mempertimbangkan daya serap tenaga kerja secara sektoral, agar tidak kontraproduktif terhadap upaya penurunan pengangguran di Indonesia.
Co-Authors Angelica Carolina Tambunan Aura Patresia Naibaho Hanna Dewi Marina Hutabarat HENDRA KURNIA PULUNGAN, HENDRA KURNIA Lirana Sapriani Gulo Menggie Orlanda Br Simarmata Naomi Sitompul Nazla Dia Maharani Riris Apriani Simarmata Widi Aulia Wilda Rahmadani