Pemodelan Determinan Adopsi dan Segmentasi Perilaku Investor Layanan Margin Trading pada Platform Sekuritas Digital

Wicaksono, Muhammad Wahyudi (2026) Pemodelan Determinan Adopsi dan Segmentasi Perilaku Investor Layanan Margin Trading pada Platform Sekuritas Digital. Masters thesis, Intitut Teknologi Sepuluh Nopember.

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Abstract

Kemudahan akses fasilitas margin trading pasca diterbitkannya POJK Nomor 6 Tahun 2024 meningkatkan peluang investasi sekaligus kerentanan finansial akibat perbedaan kesiapan kognitif investor. Sebagian besar penelitian terdahulu masih menggunakan pendekatan variable-centric yang mengasumsikan perilaku investor bersifat homogen. Oleh karena itu, penelitian ini menerapkan Sequential Hybrid Analytics untuk menganalisis determinan adopsi dan memetakan segmentasi investor. Tahap pertama menggunakan PLS-SEM berdasarkan Extended Technology Acceptance Model (Extended TAM) yang diintegrasikan dengan Financial Literacy, Trust, dan Perceived Risk. Tahap kedua menggunakan K-Means Clustering berbasis Latent Variable Scores hasil PLS-SEM. Data diperoleh melalui purposive sampling terhadap investor individu di Indonesia yang memiliki Single Investor Identification (SID) aktif. Hasil penelitian menunjukkan seluruh hipotesis didukung secara statistik. Perceived Usefulness menjadi determinan utama Behavioral Intention, sedangkan Perceived Risk menurunkan kecenderungan penggunaan margin trading. Analisis klaster menghasilkan tiga segmen investor, yaitu Digital Progresif (42,86%), Pasif (29,83%), dan Konservatif (27,31%). Penelitian ini memberikan kontribusi terhadap pengembangan Extended TAM serta menawarkan pendekatan hibrida untuk mendukung strategi edukasi dan mitigasi risiko investor.
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The accessibility of margin trading following the issuance of Financial Services Authority Regulation (POJK) No. 6 of 2024 has increased investment opportunities while also raising financial vulnerability due to differences in investors' cognitive readiness. Most previous studies have adopted a variable-centric approach that assumes homogeneous investor behavior. Therefore, this study employs Sequential Hybrid Analytics to examine adoption determinants and investor segmentation. The first stage applies PLS-SEM based on the Extended Technology Acceptance Model (Extended TAM) integrated with Financial Literacy, Trust, and Perceived Risk. The second stage uses K-Means Clustering based on Latent Variable Scores generated by PLS-SEM. Data were collected through purposive sampling from Indonesian individual investors with an active Single Investor Identification (SID). The findings indicate that all hypotheses are supported. Perceived Usefulness is the strongest determinant of Behavioral Intention, whereas Perceived Risk reduces investors' intention to adopt margin trading. The clustering analysis identifies three investor segments: Digital Progressive (42.86%), Passive (29.83%), and Conservative (27.31%). This study contributes to the extension of Extended TAM and demonstrates a hybrid analytical approach to support investor education and risk mitigation strategies.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	extended TAM, margin trading, sequential hybrid analytics, PLS-SEM, K-Means clustering, financial literacy, trust
Subjects:	H Social Sciences > HG Finance H Social Sciences > HG Finance > HG4910 Investments T Technology > T Technology (General) T Technology > T Technology (General) > T59.7 Human-machine systems.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 59101-(S2) Master Thesis
Depositing User:	Muhammad Wahyudi Wicaksono
Date Deposited:	28 Jul 2026 06:55
Last Modified:	28 Jul 2026 06:55
URI:	http://repository.its.ac.id/id/eprint/138635

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