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All Journal Journal of Science and Applicative Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Statistika dan Aplikasinya Parameter: Journal of Statistics Premium: Insurance Business Journal Jurnal Pengabdian Masyarakat Bangsa RENATA Jurnal Pengabdian Masyarakat Kita Semua Indonesian Journal of Applied Mathematics Jurnal KALANDRA TeknoKreatif: Jurnal Pengabdian kepada Masyarakat Ulil Albab
Dwi Mahrani
Actuarial Science Study Program, Faculty Of Science, Institut Teknologi Sumatera, Indonesia
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ANALISIS DAMPAK PERUBAHAN OMSET PELAKU USAHA UMKM PADA MASA PANDEMI COVID-19 MELALUI PENDEKATAN REGRESI LOGISTIK MULTINOMIAL Dwi Mahrani; Syafitri, Nabilah
Premium Insurance Business Journal Vol. 9 No. 1 (2022): PREMIUM INSURANCE BUSINESS JOURNAL
Publisher : P3M Trisakti School of Insurance (TSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35904/premium.v9i1.31

Abstract

Virus Corona atau yang lebih dikenal dengan Covid-19 pertama kali ditemukan di Wuhan, China pada bulan Desember 2019. Covid-19 pertama kali masuk ke Indonesia pada bulan Maret 2020. Untuk mengambil Tindakan pencegahan, pemerintah membuat kebijakan jaga jarak atau social distancing dan Pembatasan Sosial Skala Besar di sejumlah kota besar di Indonesia termasuk salah satunya adalah provinsi Jambi. Jambi merupakan salah satu provinsi yang memiliki banyak sektor lapangan usaha baik itu sektor alam maupun industri. Penelitian ini bertujuan untuk menganalisis dampak yang ditimbulkan terhadap omset para pelaku usaha di Provinsi Jambi. Variabel respon yang digunakan memiliki 4 kategori, yaitu kategori omset kurang dari 300 juta, kategori omset dari 300 juta sampai 2.5 miliar, kategori omset dari 2.5 miliar sampai 50 miliar dan kategori omset lebih dari 50 miliar. Oleh karena itu, metode yang digunakan dalam penelitian ini adalah regresi logistik multinomial. Setelah Analisis dilakukan, faktor-faktor yang mempengaruhi omset para pelaku usaha di tahun adalah perubahan pendapatan dengan kategori menurun, lapangan/sektor usaha dengan kategori pertanian, konstruksi, industry pengolahan, jasa keuangan dan asuransi, serta perdagangan besar dan eceran, profil usaha saat ini dengan kategori sektor yang sama dan terjadinya perekrutan sumber daya manusia selama masa Covid-19. Pengujian kesesuaian dari model yang telah dihasilkan menunjukkan bahwa tidak ada perbedaan antara hasil observasi dengan hasil prediksi. Maka dari itu, hasil dari analisis menunjukkan bahwa model memiliki ketepatan klasifikasi Apparent Error Rate sebesar 79,3 persen.
Literasi Pemanfaatan Software JASP Untuk Meningkatkan Keterampilan Statistik Guru di MAN 1 Bandar Lampung Andirasdini, Indah Gumala; Sofia, Ayu; Rivai, Muklas; Mahrani, Dwi; Yulita, Tiara; Irwan, Sri Efrinita; Berliana Ratam, Aldila Nur Indah; Gustina K.S., Annisa Hevita; Dewi, Karina Sylfia; Marisa, Marisa; Azzanina, Nanda; Baiti, Putri Isnaini Cahyaning; Rosni, Rosni
RENATA: Jurnal Pengabdian Masyarakat Kita Semua Vol. 3 No. 1 (2025): Renata - April 2025
Publisher : PT Berkah Tematik Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61124/1.renata.147

Abstract

Guru sebagai agen perubahan memiliki peran strategis dalam mengembangkan literasi digital di lingkungan kerja. Salah satu aspek penting dalam literasi digital adalah kemampuan dalam memanfaatkan teknologi dan aplikasi digital untuk mendukung proses pembelajaran dan pengolahan data. Pemanfaatan software JASP (Jeffreys's Amazing Statistics Program) menjadi salah satu cara efektif bagi guru untuk meningkatkan keterampilan statistik seperti mengolah dan menganalisis data. Dengan memanfaatkan JASP, guru dapat melakukan analisis statistik secara intuitif dan efisien, sehingga memudahkan dalam mengajarkan konsep-konsep statistik kepada siswa. Pengabdian dalam bentuk literasi pemanfaatan software JASP ini didasari oleh kebutuhan mendesak akan kemampuan memahami analisis data yang efektif di kalangan pendidik, mengingat pentingnya pengolahan data dalam proses pembelajaran dan evaluasi. Metode yang digunakan dalam pengabdian ini meliputi pelatihan intensif dan workshop yang dirancang untuk memperkenalkan fitur-fitur utama JASP, termasuk analisis statistik dasar hingga lanjutan. Peserta diberikan kesempatan untuk langsung mempraktikkan penggunaan software sehingga diharapkan dapat meningkatkan pemahaman dan keterampilan. Hasil dari kegiatan ini menunjukkan peningkatan kemampuan guru yang signifikan dalam mengolah dan menganalisis data. Hal ini ditunjukkan dari hasil pre-test dan post-test yang dilakukan sebelum dan sesudah kegiatan. Kegiatan pengabdian ini tidak hanya memberikan pengetahuan baru, tetapi juga membangun kepercayaan diri para guru dalam menggunakan teknologi untuk mendukung pengajaran. Kesimpulan dari pengabdian ini menekankan pentingnya pelatihan berkelanjutan dalam literasi data untuk meningkatkan kualitas pendidikan
CLASSIFICATION ANALYSIS USING MINIMUM SPANNING TREE AND PREDICTIONS USING ARIMA ON THE MOST INFLUENTIAL STOCKS ON THE LQ45 INDEX Theo Markus; Ayu Sofia; Dwi Mahrani
Jurnal Statistika dan Aplikasinya Vol. 9 No. 1 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09113

Abstract

The 2023 recession, largely driven by high inflation, highlights the importance of investing. The stock market, with its regulated framework and potential for significant returns, presents a viable investment option. The LQ45, an index tracking the top 45 Indonesian stocks by market capitalization, provides a benchmark. To identify promising investments, this study employed the Minimum Spanning Tree (MST) method to pinpoint the most influential stocks within the LQ45 network, followed by Auto-Regressive Integrated Moving Average (ARIMA) for price prediction. The MST analysis, utilizing degree centrality, closeness, and betweenness measures, identified BBNI as the most influential, followed by BBTN and BMRI. Price predictions for BBNI and BBTN exhibited close alignment with actual market prices, while BMRI showed a larger deviation. For BBNI shares, the ARIMA(1,0,0) model is used with a MAPE of 1.78%; for BBTN shares, the ARIMA(0,2,2) model is used with a MAPE of 2.65%; and for BMRI shares, the ARIMA(2,2,1) model is used with a MAPE of 1.84%. This research contributes to the field of stock market analysis by demonstrating the effectiveness of combining network analysis techniques, specifically the MST method, with time series forecasting models like ARIMA for stock selection. The findings provide valuable insights for investors seeking to navigate market volatility and make informed investment decisions. The findings of this research can serve as a valuable guide for investors considering BBNI, BBTN, and BMRI shares.
Pelatihan Pembuatan Laporan Keuangan Pelaku Usaha Mikro, Kecil, Dan Menengah (UMKM) Di Desa Badran Sari Julianty, Dila Tirta; Listiani, Amalia; Lestari, Fuji; Sofia, Ayu; Rivai, Muklas; Mahrani, Dwi; Fitriawati, Andi
RENATA: Jurnal Pengabdian Masyarakat Kita Semua Vol. 3 No. 3 (2025): Renata - Desember 2025
Publisher : PT Berkah Tematik Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61124/1.renata.140

Abstract

Hingga saat ini terdapat sekitar 15 Usaha Mikro, Kecil, dan Menengah yang ada di Desa Badran Sari. Kegiatan usaha yang dilakukan oleh UMKM tidak terlepas dari transaksi keuangan baik transaksi masuk maupun keluar. Apabila transaksi tersebut diolah dengan baik maka dapat menghasilkan laporan keuangan yang tepat untuk berbagai periode waktu. Dengan adanya laporan keuangan yang tepat, maka bisa didapatkan informasi yang tepat mengenai kondisi keuangan dari suatu usaha sehingga bisa membuat keputusan yang tepat untuk masa yang akan datang. Dengan rendahnya kemampuan masyarakat desa dalam mengolah informasi sehingga menjadikan para pelaku UMKM tidak dapat memanfaat informasi keuangan yang mereka miliki sebagai dasar dalam pengambilan keputusan dan pengembangan usahanya. Oleh karena itu perlu diadakannnya suatu pelatihan terkait pembuatan laporan keuangan untuk meningkatkan kemampuan masyarakat Desa Badran Sari yang memiliki UMKM sehingga tercapainya masyarakat informasi dan berbasi pengetahuan. Hal ini diharapkan dapat meningkatkan ukuran usaha UMKM dan meningkatkan kegiatan perekonomian di Desa Badran Sari, Kecamatan Punggur, Kabupaten Lampung Tengah. Setelah dilaksanakannya pelatihan mengenai penyusunan laporan keuangan, jumlah peserta yang memiliki tingkat pemahaman rendah mengalami penurunan dari semula 68,18% menjadi 36,36% dan jumlah responden dengan tingkat pemahaman sedang mengalami peningkatan lebih dari dua kali lipat dari semula 27,27% menjadi 59,09%
Pelatihan Pemanfaatan Looker Studio dalam Analisis Data dan Dashboard Statistik bagi Peningkatan Kompetensi Siswa SMKS Nurul Huda Pringsewu Rosni; Mahrani, Dwi; Fitriawati , Andi; Sofia, Ayu; Yulita, Tiara; Irawan, Agus; Mt, Ma’rufah Hayati; Mahkya, Dani Al; Nasrullah; Simanjuntak, Erica Grace; Irfan, Miftahul; Madonna, Nora; Alfian, Muhammad Nuril; Siregar, Abian Avisena; Lestari, Yushinta Cahya
KALANDRA Jurnal Pengabdian Kepada Masyarakat Vol 4 No 6 (2025): November
Publisher : Yayasan Kajian Riset Dan Pengembangan Radisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/jurnalkalandra.v4i6.605

Abstract

This Community Service (PkM) program aims to enhance students’ competencies in data analysis and statistical dashboard management through the utilization of the Looker Studio application. The training was conducted at SMKS Nurul Huda Pringsewu, involving students as participants. The training methods included lectures, demonstrations, and hands-on practice in processing data and presenting it in the form of interactive dashboards. The results of the program showed that students were able to understand the basic concepts of data exploration, the purpose of data visualization, and the use of key features in Looker Studio. In addition, students’ skills in selecting appropriate chart types according to analytical needs improved significantly. Based on the satisfaction survey, most participants rated the activity as very satisfactory (63%) and satisfactory (16%), although a small proportion expressed dissatisfaction (16%) or were not satisfied (5%). Overall, this PkM activity successfully contributed to improving students’ data literacy and digital skills, which are expected to support them in facing both academic challenges and the demands of a data-driven workforce
A COMPARATIVE STUDY OF IBNR CLAIM RESERVE ESTIMATION USING BENKTANDER, WALTER NEUHAUS, AND OPTIMAL CREDIBILITY LOSS RATIO APPROACHES Dwi Mahrani; Edward Al Faruq Purba
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss3pp1893-1910

Abstract

Reinsurance plays a crucial role in risk transfer for insurance companies, particularly in managing large and volatile losses. One of the key challenges in reinsurance is the accurate estimation of Incurred But Not Reported (IBNR) claim reserves, especially for nonproportional assumed property business, which is characterized by high claim volatility and delayed reporting patterns. This study provides an empirical comparison of credibility-based reserving methods—namely the Benktander and Walter Neuhaus approaches—using reported claims and earned premium data from United States reinsurance companies for the period 2010–2019. Unlike most existing studies that focus on proportional or direct insurance portfolios, this research evaluates the performance of these methods in a nonproportional reinsurance context and benchmarks them against the Optimal Credibility Loss Ratio method, which minimizes Mean Squared Error (MSE). Claim reserves are estimated using run-off triangle techniques, loss development factors, and credibility weighting schemes, and the accuracy of each method is assessed through MSE ratios. The results show that the Benktander method produces reserve estimates that are consistently closer to the optimal benchmark, with an average MSE ratio of 1.0265, compared to 1.4184 for the Walter Neuhaus method. These findings indicate that the Benktander approach offers a more stable and statistically efficient reserve estimation for immature and volatile nonproportional reinsurance data. The study contributes to actuarial reserving literature by providing empirical evidence on the relative effectiveness of credibility-based methods and offering practical insights for actuaries in selecting appropriate IBNR reserving techniques under high uncertainty.
Comparison of Mack Chain-Ladder and Bootstrap Methods for Claim Reserve Estimation under IFRS 17 in Lampung General Insurance Tiara Yulita; Putri Isnaini Cahyaning Baiti; Dila Tirta Julianty; Ayu Sofia; Dwi Mahrani; M. Naufal Athaatmaja
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 3 (2026): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i3.38485

Abstract

Claim  reserves are funds set aside by insurance companies to pay for reported claims (RBNS) as well as claims that have not yet been reported (IBNR), and they are crucial because they directly affect the financial health of the company. In 2024, there were customer complaints in Lampung regarding delays in claim payments by general and life insurance companies. Therefore, this study uses claim data from general insurance companies in Lampung for the period 2013–2024. The novelty of this study lies in comparing the Mack Chain Ladder analytical method and the Bootstrap simulation method for estimating claim reserves within the IFRS 17 framework using regional insurance data from Lampung, which has not been widely explored in previous studies. This study aims to estimate claim reserves and estimate the Liability for Incurred Claims (LIC),The objective of this study is to compare claim reserve values using an analytical approach (Mack Chain-Ladder) and a simulation approach (Bootstrap), implemented in accordance with the International Financial Reporting Standard (IFRS) 17. The IFRS 17 components to be calculated include the Liability for Incurred Claims (LIC) , Best Estimate Liability (BEL), and Risk Adjustment (RA) under IFRS 17. . Accurate estimation of claim reserves and the implementation of IFRS 17 play a vital role in ensuring the sustainability of insurance companies. The Mack Chain-Ladder (MCL) method is used to obtain equations for the expected value and variance of future claims as well as the prediction error rate. Meanwhile, the Bootstrap method generates numerous simulated claim datasets that reflect various possible scenarios. The advantage of the simulation approach is its ability to provide a full predictive distribution, which can be used to estimate the risk adjustment under IFRS 17. The empirical results show that the estimated claim reserve using the Mack Chain-Ladder (MCL) method is 234,740,644, while the Bootstrap method with 5.000 simulations produces a reserve range ofIn addition, this study also discusses methods for calculating capital requirements based on Value at Risk and for estimating risk adjustment using risk measures applied to the simulated distribution of claim liabilities over the contract period. 233,158,004-236,320,156. These results provide empirical insights into claim reserve estimation and support the implementation of IFRS 17 in regional insurance companies by calculating the BEL, RA, and LIC values, whose results are based on the claim reserve calculation .
Actuarial Evaluation of Additional Contributions in Early Retirement Programs Using the Spreading Gains and Losses Method Dwi Mahrani; Miftha Ulya Nazima; Ayu Sofia; Tiara Yulita
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 1 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i1.28726

Abstract

This study examines the actuarial and funding implications of accelerated retirement in a defined benefit pension scheme by integrating the Projected Unit Credit (PUC) method with the Spreading Gains and Losses approach. While both methods are widely applied in pension valuation, limited empirical evidence evaluates their combined implementation under retirement age acceleration scenarios, particularly in Indonesian public sector schemes. This study addresses that gap using secondary administrative employment data of 87 female civil servants obtained from the Investment and One-Stop Integrated Services Office of Lampung Province (Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu Provinsi Lampung), grouped into four entry-age cohorts (22–25 years). The analysis compares normal retirement at age 58 with accelerated retirement at age 50, assuming a 5% annual effective interest rate and 8% biennial salary growth. The results indicate that, at valuation age 45, actuarial liabilities increase by approximately 49.8% under retirement at age 50 relative to age 58. The shorter discounting period and earlier benefit payments outweigh the reduced contribution period, resulting in the emergence of Unfunded Actuarial Liability (UAL). The resulting Past Service Liability (PSL) is amortized over five years, requiring additional contributions ranging from IDR 27.06 million to IDR 82.05 million across entry-age groups. These findings highlight the high sensitivity of pension funding to retirement age assumptions and emphasize the importance of actuarial impact assessments prior to policy implementation. However, the deterministic framework and relatively small sample size limit broader generalization of the results.
Comparative Modeling of Pineapple Production Using Gaussian GLM and Random Forest Regression Radot MH Siahaan; Indah Gumala Andirasdini; Fuji Lestari; Dwi Mahrani; Amalia Listiani
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 1 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i1.28721

Abstract

This study aims to conduct a comparative modelling of pineapple production at PT Great Giant Pineapple (GGP) using Gaussian GLM as parametric statistical approach and Random Forest Regression method as machine learning based on monthly data from 2014 to 2022. Multicollinearity testing and distribution fitting were conducted to validate the Gaussian assumption. For the Random Forest Regression, hyperparameters were optimized by tuning the number of trees (ntree) and the number of predictors at each split (mtry) with model stability evaluated using Out-of-Bag (OOB) error. The Gaussian GLM achieved a MAPE of 8.41% (R² = 0.106) for the GP3 clone and 11.27% (R² = 0.149) for the F180 clone. Random Forest Regression produced a testing MAPE of 9.28% (R² = 0.144) for GP3 and 12.11% (R² = 0.105) for F180. While both models achieved low prediction error based on MAPE, they differed in identifying influential variables and showed limited explanatory power as indicated by low R² values. The Gaussian GLM identifies air pressure as significant for both clones and rainfall for F180 clone, while Random Forest consistently identifies rainfall as the most influential predictor. These findings confirm the complementary strengths of parametric and machine learning approaches in supporting climate-based production planning and risk mitigation.
Segment Risks Based on Age, Wages, Working Hours, and Claim Costs using K-Medoids Clustering Agus Irawan; Dwi Mahrani; Aldila Nur Indah Berliana Ratam; Marisa Marisa
ULIL ALBAB : Jurnal Ilmiah Multidisiplin Vol. 5 No. 7: Juni 2026
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jim.v5i7.17771

Abstract

Occupational risk plays a crucial role in employment insurance management due to its direct impact on claim frequency and the sustainability of insurance systems. However, workers’ risk levels are heterogeneous and influenced by factors such as age, wages, working hours, and claim costs. This study aims to determine the optimal number of clusters and analyze worker risk segmentation using the K-Medoids Clustering method. Secondary data, obtained from Kaggle and consisting of 54,000 observations, were used. From this dataset, 300 samples were selected using the Slovin formula. The analyzed variables included age, weekly wages, hours worked per week, initial claim cost, and final claim cost. Prior to clustering, the data were standardized using a robust scaler and tested for multicollinearity. The optimal number of clusters was determined using the Silhouette Coefficient method. The results indicated that the optimal clustering structure consisted of three clusters, with a Silhouette Coefficient value of 0.703. These clusters represented low-risk, medium-risk, and high-risk worker groups. The findings offer valuable insights for insurers to enhance risk segmentation, claims management, and more targeted premium policy formulation.
Co-Authors Adria Zhara Al Mujadilla Agus Irawan Agus Irawan Aldila Nur Indah Berliana Ratam Aldila Nur Indah Berliana Ratam Alfian, Muhammad Nuril Amalia Listriani Ananda Amelia Andi Fitriawati Andi Fitriawati Anida Hasibuan Annisa Hevita Gustina Kumalasari Saefulloh Aswan Anggun Pribadi Ayu Sofia Ayu Sofia Ayu Sofia Azzanina, Nanda Baiti, Putri Isnaini Cahyaning Berliana Ratam, Aldila Nur Indah Dani Al Mahkya Dani Al Mahkya Dani Al Mahkya Dila Tirta Julianty Dwi Sofianti Edward Al Faruq Purba Erica Grace Simanjuntak Febi Yosepha Br Ginting Fitriawati , Andi Fuji Lestari Fuji Lestari Indah Gumala Andirasdini Irfan, Miftahul Irwan, Sri Efrinita Karina Sylfia Dewi Lestari, Yushinta Cahya Listiani, Amalia M. Naufal Athaatmaja Madonna, Nora Marco Marolop Siahaan Marisa Marisa Marisa Marisa Ma’rufah Hayati Mhd Rayhan Jovely Alfarizi Miftahul Irfan Miftha Ulya Nazima Mt, Ma’rufah Hayati Nasrullah Nasrullah Nasrullah Nofel Sitinjak Nora Madonna Putri Isnaini Cahyaning Baiti Radot MH Siahaan Rifky Fauzi Rivai, Muklas Rosni, Rosni Siregar, Abian Avisena Syafitri, Nabilah Theo Markus Tiara Shofi Edriani Winda Wulandari Yulita, Tiara