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All Journal Desimal: Jurnal Matematika Zero : Jurnal Sains, Matematika, dan Terapan Variance : Journal of Statistics and Its Applications Jurnal Statistika dan Aplikasinya Parameter: Journal of Statistics Enthusiastic : International Journal of Applied Statistics and Data Science MATHunesa: Jurnal Ilmiah Matematika Smart Society: Community Service and Empowerment Journal Jurnal Pengabdian Masyarakat Bangsa RENATA Jurnal Pengabdian Masyarakat Kita Semua Indonesian Journal of Applied Mathematics Jurnal KALANDRA Parameter: Jurnal Matematika, Statistika dan Terapannya TeknoKreatif: Jurnal Pengabdian kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS)
Ayu Sofia
Actuarial Science Study Program, Sumatera Institute Of Technology, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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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.
ANALISIS KLASIFIKASI KUALITAS HIDUP MANUSIA ANTAR KABUPATEN/KOTA DI INDONESIA MENGGUNAKAN ALGORITMA CATBOOST CLASSIFIER DAN SHAP VALUES Ayu Sofia; Linda Rassiyanti
MATHunesa: Jurnal Ilmiah Matematika Vol. 14 No. 1 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v14n1.p430-444

Abstract

Human development must go hand in hand with improving quality of life, as reflected by HDI and its influencing factors. Classifying quality of life based on HDI into developed, developing, and underdeveloped areas offers insights into the human development performance of each district/city in Indonesia. The CatBoost Classifier and SHAP values help build an accurate model while interpreting variable influences. This study analyzes human quality of life classification across districts/cities based on HDI and related factors. The CatBoost model achieved 92.23% accuracy, with the best performance in the developing class, while the underdeveloped class showed low accuracy due to data imbalance. SHAP analysis revealed that average years of schooling, per capita expenditure, and region type were key variables in the developed and developing classes, while island location and sanitation access dominated in the underdeveloped class. These findings highlight the importance of education, economic welfare, and basic infrastructure in shaping quality of life. This research also supports actuarial social risk planning, particularly in designing data- and region-based social security systems.
Pemanfaatan Looker Studio untuk Mengembangkan Kompetensi Analisis dan Visualisasi Data Siswa SMKS Nurul Huda Pringsewu Rosni Rosni; Nora Madonna; Andi Fitriawati; Dani Al Mahkya; Agus Irawan; Erica Grace Simanjuntak; Ma’rufah Hayati; Nasrullah Nasrullah; Miftahul Irfan; Dwi Mahrani; Ayu Sofia; Tiara Yulita; Muklas Rivai
Jurnal Pengabdian Masyarakat Bangsa Vol. 4 No. 1 (2026): Maret
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v4i1.4194

Abstract

Kemampuan dalam memanfaatkan teknologi, khususnya dalam eksplorasi dan visualisasi data, menjadi tantangan signifikan dalam dunia pendidikan di era digital saat ini. SMKS Nurul Huda Pringsewu sebagai mitra kegiatan pengabdian menunjukkan adanya keterbatasan kompetensi siswa dalam mengolah data dan menyajikannya dalam bentuk visual yang informatif. Menanggapi permasalahan tersebut, tim Pengabdian kepada Masyarakat (PkM) melaksanakan pelatihan menggunakan aplikasi Looker Studio untuk eksplorasi data dan pembuatan dashboard statistik. Looker Studio merupakan platform berbasis web yang memudahkan pengguna dalam mengolah data numerik dan menyajikannya secara visual, sehingga proses pembacaan data tidak lagi dilakukan secara manual. Pelatihan ini bertujuan untuk meningkatkan kemampuan siswa dalam mengolah dan memvisualisasikan data menggunakan teknologi terkini. Hasil dari kegiatan ini menunjukkan peningkatan kompetensi siswa dalam mengeksplorasi data statistik serta peningkatan kualitas pembuatan dashboard yang lebih informatif dan menarik. Kegiatan ini diharapkan dapat menjadi langkah awal dalam membekali siswa dengan keterampilan digital yang relevan dengan kebutuhan industri saat ini.
Co-Authors Ade Lailani Aditya Rahman Agus Irawan Agus Irawan Alfian, Muhammad Nuril Aliem, Dien Manarul Andi Fitriawati Andi Fitriawati Anik Djuraidah Aulia Khairani Hutabarat Azzanina, Nanda Bagus Sartono Baiti, Putri Isnaini Cahyaning Bariq, Muhammad Shidqi Abdul Berliana Ratam, Aldila Nur Indah Dani Al Mahkya Dani Al Mahkya Dewi, Karina Sylfia Dharu Cahyoaji Sasongko Dien, Zulfanita Dila Tirta Julianty Dwi Mahrani Erica Grace Simanjuntak Fitriawati , Andi Fuji Lestari Gustina K. S, Annisa Hevita Gustriza Erda Indah Gumala Andirasdini Irfan, Miftahul Irwan, Sri Efrinita Josepa , Tiffany Audrey Khairunnisa Maharani Lestari, Yushinta Cahya Linda Rassiyanti Linda Rassiyanti Linda Rassiyanti Listiani, Amalia Luluk Muthoharoh Madonna, Nora Marisa Marisa Ma’rufah Hayati Miftahul Irfan Miftha Ulya Nazima Mt, Ma’rufah Hayati Muklas Rivai Muklas Rivai Nasrullah Nasrullah Nasrullah Nora Madonna Nurfitra Pitri, Rizka Rivai, Muklas Rizka Pitri Rizka Pitri Rosni Rosni Rosni, Rosni Siahaan, Marco Marolop Simarmata, Gabriel Camoranesa Siregar, Abian Avisena Siswanto Siswanto Theo Markus Tiara Yulita Yuliana Yuliana Yulita, Tiara Zul’aina, Restu Apriani