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All Journal Mandalika Mathematics and Educations Journal Jurnal Pengabdian Masyarakat Asia Journal of Mathematics, Computation and Statistics (JMATHCOS)
Muklas Rivai
Institut Teknologi Sumatera
Arts Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Other

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Implementation of Amortization and Sinking Fund in Financial Literacy Education to Prevent Online Loan Traps Among Students of MAN 1 Bandarlampung Indah Gumala Andirasdini; Fuji Lestari; Dila Tirta Julianty; Muklas Rivai
Jurnal Pengabdian Masyarakat Vol. 7 No. 1 (2026): Jurnal Pengabdian Masyarakat
Publisher : Institut Teknologi dan Bisnis Asia Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jpm.v7i1.2837

Abstract

Purpose: This community service initiative aims to strengthen students’ financial literacy by introducing key concepts such as amortization tables and sinking fund strategies. A significant proportion of students exhibit limited understanding of high-interest debt structures and lack essential personal financial management skills. The concept of amortization was introduced to demystify loan repayment mechanisms, while the sinking fund approach was presented as a disciplined strategy for long-term saving and financial goal achievement. Method: The program was implemented through a series of interactive socialization sessions, hands-on educational activities, and simulation workshops. Students actively developed amortization schedules and sinking fund models, enabling them to apply theoretical knowledge in practical contexts. To measure the impact, pre-test and post-test questionnaires were administered to assess improvements in students’ comprehension of financial principles. Practical Applications: The program successfully produced a range of accessible educational resources, including learning modules, student-friendly booklets, and digital Excel templates. These tools empower students to independently simulate loan repayment scenarios and savings plans, promoting self-reliance and informed financial decision-making. Conclusion: The results demonstrated a marked improvement in students’ financial literacy, with scores increasing from an average of 5.67 to 8.00. The integrated, experiential approach not only enhanced understanding but also fostered greater financial resilience among youth, equipping them with the knowledge to avoid predatory online lending practices that are increasingly common among students today.
Modelling Extreme Stock Market Risk with Peaks Over Threshold-Value at Risk and APARCH Specifications Aulia Khairani Hutabarat; Ayu Sofia; Muklas Rivai
Journal of Mathematics, Computations and Statistics Vol. 9 No. 2 (2026): Volume 09 Issue 02 (June 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/hcm5vr15

Abstract

The capital market plays an important role in a country's economy. Through the capital market, investors can also grow their wealth by investing in stocks, bonds, or other instruments. Investing in stocks in the capital market has high profit potential, but also carries significant volatility risks. One company that experienced significant volatility was PT Indofood Sukses Makmur Tbk., as in 2020 when the COVID-19 pandemic caused extreme volatility in global and local markets. Therefore, risk management is necessary to minimize risks using the Value at Risk method.This study also aims to analyze the risk of investing in PT Indofood Sukses Makmur Tbk. shares using the VaR method with APARCH modeling and the POT approach. The data used are daily closing prices from March 2020 to June 2025. The results show that the best model for forecasting is APARCH(1,1) with a better forecasting accuracy than the naive forecast, as indicated by the MASE value of 0,6131. The VaR estimate indicates that the longer the forecasting period and the higher the confidence level used, the higher the VaR value. This indicates that the extreme risk is higher for the next ten periods. The validity test (backtesting) also confirms that the VaR estimation results are accurate for the long term at a significance level of 1%, 5% and 10%.
Segmentasi Kecamatan di Kota Bandung Berdasarkan Statistik Penyandang Disabilitas Menggunakan Algoritma K-Means Clustering Rosni Rosni; Erinna Fredella; Muklas Rivai
Mandalika Mathematics and Educations Journal Vol 8 No 1 (2026): Edisi Maret
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i1.11430

Abstract

People with disabilities continue to experience discrimination, stigmatization, and unfulfilled rights. The number of people with disabilities in Bandung City is the second highest in West Java Province. Various factors, including a disability-unfriendly environment, lack of accessibility to public infrastructure, and insufficient social support. This study aims to analyze and segment subdistricts in Bandung City based on disability statistics using the K-Means clustering algorithm. The types of disabilities analyzed include mental disabilities, physical disabilities, physical and mental disabilities, visual impairments, hearing impairments, and other types of disabilities. The results of the study showed that the optimal number of clusters, as determined by the Elbow method, is 2 clusters. A total of 18 subdistricts are classified into Cluster 1, characterized by a relatively lower number of persons with disabilities, while the remaining 12 subdistricts are classified into Cluster 2, which has a relatively higher number of persons with disabilities. The results of this segmentation are expected to support the realization of Bandung City as an inclusive city and to assist the government in developing more targeted policies and programs.
Analisis Klaterisasi Perubahan Iklim di Indonesia Menggunakan K-Means Tahun 2023 Muklas Rivai; Rosni Rosni; Nasrullah Bachtiar
Mandalika Mathematics and Educations Journal Vol 8 No 2 (2026): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i2.11817

Abstract

Perubahan iklim global memberikan dampak signifikan terhadap pola cuaca di Indonesia, memengaruhi sektor penting seperti pertanian, perikanan, kesehatan, dan ekonomi. Untuk menganalisis data iklim yang kompleks, metode klasterisasi K-Means digunakan guna mengidentifikasi pola cuaca serupa, yang bermanfaat bagi mitigasi bencana, perencanaan sumber daya, dan pengelolaan iklim secara lebih efektif. Data yang digunakan mencakup kecepatan angin, Kelembapan, dan curah hujan dari 34 provinsi di Indonesia pada tahun 2023. Berdasarkan analisis metode silhouette, ditemukan bahwa jumlah klaster optimal adalah dua. Klaster pertama meliputi 15 provinsi seperti Sumatera Utara, Jambi, Papua Barat dan lainnya. Karakteristik kluster pertama yaitu kecepatan angin rendah, Kelembapan tinggi, dan curah hujan tinggi. Kondisi ini dipengaruhi oleh lokasi geografis tropis, pola angin muson stabil, topografi (lembah, hutan, atau pegunungan), serta kedekatan dengan sumber uap air. Klaster kedua Terdiri dari 19 provinsi seperti Aceh, Jawa Timur, Nusa Tenggara Barat dan lainnya. Karakteristik klister kedua yaitu memiliki kecepatan angin tinggi, Kelembapan rendah, dan curah hujan rendah. Faktor geografis seperti wilayah terbuka, angin muson kering, dan jarak dari sumber Kelembapan utama. Hasil penelitian ini diharapkan dapat membantu perencanaan dan mitigasi bencana terkait pola cuaca di Indonesia.
Co-Authors Aulia Khairani Hutabarat Ayu Sofia Dila Tirta Julianty Erinna Fredella Fuji Lestari Indah Gumala Andirasdini Nasrullah Bachtiar Rosni Rosni