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Pendekatan Machine Learning untuk Estimasi Harga Rumah dengan Regresi Linier Hakim, Hamdan; Kamil, Dinata; Alatas, Burhan
Journal of Science and Technology: Alpha Vol. 1 No. 1 (2025): Journal of Science and Technology: Alpha, January 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/alpha.v1i1.99

Abstract

Estimasi harga rumah merupakan salah satu tantangan utama dalam bidang properti, terutama karena banyaknya faktor yang memengaruhi nilai suatu rumah, seperti lokasi, luas bangunan, jumlah kamar, dan fasilitas. Artikel ini membahas pendekatan machine learning menggunakan regresi linier untuk memprediksi harga rumah berdasarkan berbagai parameter tersebut. Regresi linier dipilih karena kesederhanaannya, interpretabilitasnya, dan kemampuannya untuk menangani hubungan linier antara variabel. Data yang digunakan berasal dari dataset publik, yang mencakup berbagai fitur terkait properti. Dalam penelitian ini, data dibagi menjadi set pelatihan dan pengujian untuk mengevaluasi performa model. Hasil evaluasi menunjukkan bahwa regresi linier mampu memberikan estimasi harga rumah yang cukup akurat, terutama dalam dataset dengan distribusi data yang merata. Selain itu, analisis dilakukan untuk mengidentifikasi fitur yang paling berpengaruh terhadap harga rumah, seperti lokasi dan ukuran properti. Studi ini menunjukkan bahwa regresi linier dapat menjadi solusi awal yang efektif untuk estimasi harga rumah, meskipun model yang lebih kompleks mungkin diperlukan untuk menangani data yang lebih besar dan variabel yang lebih dinamis. Kata kunci: machine learning, regresi linier, estimasi harga rumah, prediksi, properti.
Transformasi Relasi Sosial Akibat Kecerdasan Buatan dalam Praktik Kerja Kreatif Humaniora Digital Hakim, Hamdan; Aziz, Teuku Ilham
PERSEPTIF: Jurnal Ilmu Sosial dan Humaniora Vol. 3 No. 3 (2025): PERSEPTIF: Jurnal Ilmu Sosial dan Humaniora
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/perseptif.v3i3.440

Abstract

The development of artificial intelligence has brought significant changes to digital humanities practices, particularly in creative work that involves the production and interpretation of cultural knowledge. This study aims to analyze the transformation of social relations resulting from the integration of artificial intelligence into creative work practices in digital humanities. The main focus is on changes in interaction patterns, collaboration structures, role distribution, the formation of professional identities, and ethical dynamics that emerge in relations between humans and AI systems. The study adopts an interpretative qualitative approach with a multiple case study design. Data were collected through in-depth interviews, limited participant observation, and analysis of digital artifacts produced in AI-based creative practices. Data analysis was conducted thematically to identify patterns of social relations and meanings constructed by creative workers. The findings show that artificial intelligence is no longer positioned solely as a technical tool, but as a relational entity that plays an active role in the creative process. The presence of AI shifts interaction patterns toward hybrid human–machine relations, reconfigures work collaboration, and influences the legitimacy and identity of creative workers. This transformation is ambivalent. It opens opportunities for creative exploration while also generating tensions related to authority, the value of creativity, and inequalities in access to technology. This study emphasizes the importance of a critical digital humanities approach that is oriented toward human values in responding to the integration of artificial intelligence. The findings are expected to provide empirical and conceptual contributions to the development of digital humanities studies in the era of artificial intelligence.