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All Journal TEKNIK INFORMATIKA Journal of the Indonesian Mathematical Society Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) BAREKENG: Jurnal Ilmu Matematika dan Terapan Communication in Biomathematical Sciences FARABI: Jurnal Matematika dan Pendidikan Matematika Recent in Engineering Science and Technology Lentera Jurnal Pengabdian Maysarakat
Nugraha, Edwin Setiawan
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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A Backpropagation Artificial Neural Network Approach for Loan Status Prediction Nugraha, Edwin Setiawan; Sitepu, Gabrielle Jovanie
JURNAL TEKNIK INFORMATIKA Vol. 15 No. 2 (2022): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v15i2.27006

Abstract

Providing credit has become a main source of profit for financial and non-financial institutions. However, this transaction might lead into credit risk. This risk occurred if debtors unable to complete their obligations that will led loss for creditors.  It is necessity for company to create assessment in distinguishing eligible or non-eligible prospective customer. Artificial Neural Network (ANN) is introduced in solving this typical classification case. Furthermore, one of learning algorithm in ANN namely Backpropagation is able to minimizing error of output in order to receive accurate result. This research aims to form models that capable in classifying the loan status of applicants by utilizing historical data. The method developed in this research is Backpropagation with activation function is a sigmoid function. In addition, this research formed two data model for analyzed; with first data model is every variable given in dataset and for the second data model is the variables that influenced the loan acceptance. Backpropagation shows high performance with more or less data variables. The results of this research show that the both data model has highest accuracy of prediction is 94.37% while the lowest accuracy prediction is 80.28%.
Prediksi Faktor Pengaruh Klaim Asuransi Menggunakan Regresi Logistik Mahadewi, Ni Made Mila; Sutany, Adelia; Kurniawan, Tania Oktavionabila; Nugraha, Edwin Setiawan
FARABI: Jurnal Matematika dan Pendidikan Matematika Vol 8 No 2 (2025): FARABI (In Press)
Publisher : Program Studi Pendidikan Matematika FKIP UNIVA Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47662/farabi.v8i2.1238

Abstract

Bagi perusahaan asuransi, memahami faktor-faktor yang mempengaruhi pengajuan klaim sangat penting. Hal ini harus dilakukan oleh perusahaan asuransi agar mereka dapat menjaga keseimbangan dari jumlah premi yang didapatkan dan jumlah klaim yang dilakukan oleh nasabah. Ketidakpastian terkait faktor risiko yang signifikan dapat menimbulkan kesulitan dalam menentukan harga premi yang tepat dan pengelolaan risiko yang akan dilakukan oleh perusahaan. Penelitian ini bertujuan untuk menganalisis faktor apa saja yang dapat memengaruhi kemungkinan nasabah mengajukan klaim asuransi dengan menggunakan metode regresi logistik. Hasil yang didapatkan dari analisis ini menunjukkan bahwa dari 7 variabel bebas ada 4 variabel yang mempengaruhi jumlah klaim, yakni age, children, bmi, dan smoker mempengaruhi klaim. Kinerja dari model ini menunjukkan bahwa hasil dari accuracy sebesar 89%, precision sebesar 90%, sensitivity sebesar 91% dan F1-score sebesar 90%. Penelitian ini berharap bahwa model yang telah dibuat dapat menjadi acuan bagi masyarakat dan industri asuransi untuk mengetahui faktor penyebab klaim secara akurat dan efisien.
Co-Authors Alika, Zalfani Alvina, Celine Ardiansyah, Trio Azizah, Jasmine Bonyah, Ebenezer Dani Suandi Dedi Rianto Rahadi Dwi Wijonarko Fitriani agustina Hamzah, Dadang Amir Ilahi, Fadilah Karunia Eka Lestari Khaerunnisa, Ine Kurniawan, Tania Oktavionabila Mahadewi, Ni Made Mila Mokhammad Ridwan Yudhanegara Muhammad Faisal Olivia, Agna Pratama, Muhammad Nabil Priambodo, Oktanindita Ramadhan, Joko Iwan Ramdhani, Randi Risnawita Risnawita, Risnawita Samsul Arifin Sisilia Sylviani Sitepu, Gabrielle Jovanie Sudding, Fauziah Nur Fahirah Sutany, Adelia Zalukhu, Jernihlawati