PURWANTO, Iwan and Isnanto, Rizal and Widodo, Aris Puji (2025) PENGEMBANGAN MODEL SISTEM PENILAIAN CALON NASABAH PADA P2P LENDING MENGGUNAKAN METODE BIG FIVE PERSONALITY DAN FUZZY MAMDANI. Doctoral thesis, UNIVERSITAS DIPONEGORO.

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Abstract

Perkembangan fintech, khususnya platform Peer-to-Peer (P2P) Lending, telah memberikan alternatif baru dalam sistem perbankan dan keuangan. Platform ini memungkinkan UMKM dan individu mendapatkan akses kredit yang lebih luas. Namun, penilaian risiko kredit yang efektif menjadi tantangan utama bagi platform ini. Penelitian ini bertujuan untuk mengembangkan model sistem penilaian calon nasabah pada P2P lending dengan mengintegrasikan Metode Big Five Personality dan Fuzzy Mamdani, guna mengurangi risiko kredit macet dengan menilai kelayakan kredit berdasarkan analisis psikometrik dan faktor-faktor non-keuangan.
Metodologi yang digunakan dalam penelitian ini adalah pendekatan kuantitatif. Data dikumpulkan melalui survei Big Five Personality yang diikuti oleh 197 nasabah. Analisis data dilakukan dengan menggunakan sistem Fuzzy Mamdani untuk menghasilkan skor penilaian risiko yang akurat. Hal ini memungkinkan model untuk mengintegrasikan aspek psikologis individu ke dalam penilaian risiko kredit.
Hasil penelitian menunjukkan bahwa model yang dikembangkan berhasil memperbaiki proses penilaian kredit. Model ini memberikan rekomendasi pinjaman yang lebih presisi dan berhasil mengurangi potensi kredit macet dengan mempertimbangkan aspek kepribadian calon nasabah. Ini menandai sebuah kemajuan signifikan dalam metodologi penilaian risiko kredit, khususnya untuk platform P2P lending. Implikasi praktis dari penelitian ini bagi industri P2P lending adalah peningkatan akurasi dalam penilaian risiko dan pengambilan keputusan kredit. Secara teoretis, penelitian ini memberikan kontribusi pada pengembangan model penilaian risiko kredit yang mengintegrasikan analisis kepribadian, menawarkan perspektif baru dalam penilaian kredit di sektor keuangan.
Kata Kunci: Platform Peer-to-Peer (P2P) Lending, UMKM, Metode Big Five Personality, Fuzzy Mamdani, Kredit macet

The development of fintech, especially Peer-to-Peer (P2P) Lending platforms, has provided a new alternative in the banking and financial system. These platforms allow SMEs and individuals to gain broader access to credit. However, effective credit risk assessment remains a major challenge for these platforms. This research aims to develop a customer assessment model for P2P lending by integrating the Big Five Personality Method and Fuzzy Mamdani, in order to reduce the risk of loan default by evaluating creditworthiness based on psychometric analysis and non-financial factors.
The methodology used in this research is a quantitative approach. Data were collected through a Big Five Personality survey of 197 customers. Data analysis was performed using the Fuzzy Mamdani system to generate accurate risk assessment scores. This allows the model to integrate the psychological aspects of individuals into credit risk assessment.
The results of the study indicate that the developed model successfully improves the credit assessment process. This model provides more precise loan recommendations and successfully reduces the potential for loan defaults by considering the personality aspects of prospective customers. This marks a significant advancement in the methodology of credit risk assessment, especially for P2P lending platforms. The practical implication of this research for the P2P lending industry is an increase in accuracy in risk assessment and credit decisionmaking. Theoretically, this research contributes to the development of a credit risk assessment model that integrates personality analysis, offering a new perspective in credit assessment in the financial sector.
Keywords: Peer-to-Peer (P2P) Lending Platform, SMEs, Big Five Personality Method, Fuzzy Mamdani, Loan Default

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