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All Journal Media Statistika Prosiding Seminar Nasional Official Statistics
Baiq Nurul Haqiqi, Baiq Nurul
Jurusan Komputasi Statistik, Sekolah Tinggi Ilmu Statistik (STIS)
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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ANALISIS PERBANDINGAN METODE FUZZY C-MEANS DAN SUBTRACTIVE FUZZY C-MEANS Haqiqi, Baiq Nurul; Kurniawan, Robert
MEDIA STATISTIKA Vol 8, No 2 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (200.309 KB) | DOI: 10.14710/medstat.8.2.59-67

Abstract

Fuzzy C-Means (FCM) is one of the most frequently used clustering method. However FCM has some disadvantages such as number of clusters to be prespecified and partition matrix to be randomly initiated which makes clustering result becomes inconsistent. Subtractive Clustering (SC) is an alternative method that can be used when number of clusters are unknown. Moreover, SC produces consistent clustering result. A hybrid method of FCM and SC called Subtractive Fuzzy CMeans (SFCM) is proposed to overcome FCM’s disadvantages using SC. Both SFCM and FCM are implemented to cluster generated data and the result of the two methods are compared. The experiment shows that generally SFCM produces better clustering result than FCM based on six validity indices.Keywords : Clustering, Fuzzy C-Means, Subtractive Clustering, Subractive Fuzzy C-Means
Disrupsi Artificial Intelligence terhadap Pekerja Kreatif Digital: Analisis Opini Publik dan Tren Pasar Kerja Menggunakan Big Data Haqiqi, Baiq Nurul
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2392

Abstract

The disruption caused by Artificial Intelligence (AI) technology presents new challenges for digital creative workers in Indonesia. On one hand, AI offers efficiency in content production; on the other hand, concerns arise about the displacement of human roles, imitation of artistic styles, and a decline in the originality value of works. This study aims to understand public responses to this phenomenon by leveraging big data through opinion analysis on social media platform X and labor market trend analysis based on job vacancy data from the JobStreet website. Utilizing the IndoBERT language model trained via a few-shot learning approach using the SetFit framework, sentiment analysis reveals a dominance of negative sentiment (65.65%), while emotion detection uncovers that anger (24.34%) and disgust (22.57%) are the most prominent emotional reactions. Public discussions largely highlight issues related to digital art, the use of image generators, animation production, and content automation, which generally reflect concerns about potential shifts in values and roles within the creative industry. Meanwhile, labor market data show that digital creative job vacancies declined in 2025 compared to 2022, with geographic concentration still centered in the Java Island, particularly in Jakarta. The findings of this study are expected to open opportunities for further research to deepen understanding of the impact of AI disruption on digital creative workers and provide an initial overview for related policy formulation.
Co-Authors Robert Kurniawan, Robert