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All Journal AKSIOMA: Jurnal Program Studi Pendidikan Matematika JIPM (Jurnal Ilmiah Pendidikan Matematika) Math Didactic: Jurnal Pendidikan Matematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Unisda Journal of Mathematics and Computer Science (UJMC) Jambura Journal of Mathematics Transformasi : Jurnal Pendidikan Matematika dan Matematika Variance : Journal of Statistics and Its Applications JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Teknik Informatika (JUTIF) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Differential: Journal on Mathematics Education
Feby Indriana Yusuf
Universitas PGRI Banyuwangi
Humanities Computer Science & IT Education Engineering Mathematics Public Health Other

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EVALUATING NEARMISS AND SMOTE FOR VEHICLE INSURANCE FRAUD CLAIM CLASSIFICATION WITH A RANDOM FOREST CLASSIFIER Yusuf, Feby Indriana; Handamari, Endang Wahyu
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page219-230

Abstract

This study evaluates the detection of fraudulent car insurance claims in unbalanced data by comparing two resampling techniques, namely NearMiss (undersampling) and SMOTE (oversampling), combined with Random Forest. The public dataset, consisting of 1,000 observations and 40 features, was preprocessed for missing value handling, label encoding, and min–max normalization, and split into 70% training data and 30% test data. Three scenarios were evaluated: original data (unbalanced), NearMiss, and SMOTE, using accuracy, precision, sensitivity (recall), specificity, and F1-score evaluations. The analysis results show that NearMiss provides the most balanced performance for antifraud purposes, with a sensitivity of 0.865, an F1-score of 0.667, and an accuracy of 0.787. For the original unbalanced data, the model achieved a sensitivity of 0.297 and an accuracy of 0.767. SMOTE achieved the highest precision (0.567) and accuracy (0.783), but its sensitivity was lower than that of NearMiss. These findings confirm that the selection of resampling techniques must be aligned with operational objectives: NearMiss is more appropriate when the priority is to capture as many fraud cases as possible, while SMOTE is more suitable when false positive control is prioritized.
Implementasi Metode Extreme Value Theory untuk Menghitung Maksimal Kerugian Akibat Bencana Alam Yusuf, Feby Indriana; A’la, Kevina Alal; Thalita, Bella Cindy
Jambura Journal of Mathematics Vol 8, No 1: February 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v8i1.35193

Abstract

This study employs Extreme Value Theory (EVT) using the Block Maxima (BM) approach and the Generalized Extreme Value (GEV) distribution to model and estimate the potential maximum financial losses caused by natural disasters in Central Java, Indonesia. Historical loss data from 2022 are utilized to calibrate GEV distribution parameters, followed by Monte Carlo simulations to project risks over a 12-year horizon. The results reveal that the data exhibit heavy-tailed characteristics (indicated by a positive shape parameter), signaling significant extreme risks. Goodness-of-fit tests, specifically Kolmogorov-Smirnov and Anderson-Darling, confirm the validity of the GEV model. Return level analysis indicates a sharp escalation in risk; for a 100-year return period, potential losses reach a substantial magnitude. These findings contribute methodologically to regional fiscal risk estimation and underscore the necessity of precise financial mitigation instruments.
Co-Authors Adi, Puti Zakiyah Raisa Anggraini, Dessy Anggraini, Dessy Anjasari, Dwi Hilda Anjasari, Dwi Hilda Arvianti, Aurellia A’la, Kevina Alal Barep Yohanes Bukhori, Hilmi Aziz Dwi Hilda Anjasari Dwi Mifta Mahanani, Dwi Mifta Dzurotul Mutimmah Eko Listiwikono Endang Wahyu Handamari Fitri Nurmasari Hady Rasikhun Heri Susanto Imam Nurhadi Purwanto Julianti, Nurma Haya Nada, Qothrun Nadya Adharani Novi Prayekti Nurma Haya Julianti Permata, Wahyu Finda Permata, Wahyu Finda Rachmaniah Mirza Hariastuti Rahmi, Miftachul Rahmi, Miftachul Saiful Bukhori Saragih, Trecy Elisabet Tioralina Sari, Meylita Situmorang, Boy Nathanael Susanti, Reny Eka Evi Syaiful Anam Syamsiar, Syamsiar Thalita, Bella Cindy Wiwik Handayani