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All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN ESTIMASI: Journal of Statistics and Its Application NEAR: Jurnal Pengabdian kepada Masyarakat
Alimatun Najiha
Universitas Tadulako
Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Public Health Social Sciences Transportation Other

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Nilai Risiko Terkondisi pada Return Finansial Menggunakan Metode Copula Gumbel Najiha Alimatun; Anisa Anisa; Andi Kresna Jaya
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 1, Januari, 2022 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.12246

Abstract

The calculation of VaR is assumed normal distribution while the conditions in the real world distribution conditions of the return value depends on the market conditions that occurred at the time. Thus, this makes VaR estimates invalid which results in portfolio risk occurring greater than the predetermined risk. Therefore, In this study, the estimated risk value uses the Conditional Value at Risk (CVaR), which measures the expected value depending on what is the worst percentage of the risk loss, and using Copula Gumbel to model financial return in the investment data of PT. Telkomunikasi Indonesia tbk and PT. XL Axiata tbk. for the period March 11, 2019 to March 10, 2020. In this study, the CVaR estimation results for the 99% confidence level is 0.231, while for the VaR estimate it is 0.192. This indicates that risk value with CVaR estimate is better able to show higher risk than VaR.
Comparison of Random Survival Forest and Fuzzy Random Survival Forest Models in Telecommunications Industry Customer Data Nurhaliza, Sitti; Harismahyanti, Andi; Najiha, Alimatun
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 21 No. 2 (2024)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2024.v21.i2.17498

Abstract

The telecommunications sector is facing increasing competition, and customer churn is still a majorchallenge despite the implementation of advanced promotions and high-quality services. Churn refers tothe discontinuation of services by customers, influenced by several factors that can be found through datamodeling. This study compares two predictive models, Random Survival Forest (RSF) and Fuzzy RandomSurvival Forest (FRSF), for predicting customer churn time in the telecommunications industry. Bothmodels are evaluated using the median C-index value obtained from 20 repetitions, ensuring moreconsistent and reliable results. RSF, a widely used survival analysis method, has shown strong predictivepower, with studies reporting up to 99% accuracy in churn prediction. However, FRSF, a modified versionthat incorporates fuzzy logic, has proved superior performance, particularly in handling imprecise oruncertain data. The results show that FRSF achieves a lower error rate of 0.1739, compared to RSF's errorrate of 0.1906. These findings suggest that FRSF outperforms RSF in churn prediction, making it a morereliable and righter model for finding at-risk customers. The study concludes that the FRSF model is thepreferred choice for predicting churn in the telecommunications industry, offering better predictive qualityand consistency in handling uncertain data.
Peningkatan Kompetensi Guru Dalam Pemanfaatan AI Untuk Penyusunan Bahan Ajar Adaptif di Era Kurikulum Merdeka di SMP Negeri 2 Sigi Harismahyanti A Andi; Nurul Fiskia Gamayanti; Jamidun Jamidun; Alimatun Najiha; Morina A. Fathan
NEAR: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2025): NEAR
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/nr.v5i1.3140

Abstract

Perkembangan pesat kecerdasan buatan (Artificial Intelligence/AI) telah membuka peluang besar untuk meningkatkan kualitas pendidikan, khususnya dalam penyusunan bahan ajar yang adaptif terhadap karakteristik siswa. Penelitian ini bertujuan untuk meningkatkan kompetensi guru SMP Negeri 2 Sigi dalam memanfaatkan AI, khususnya ChatGPT, guna mendukung implementasi Kurikulum Merdeka yang menekankan pembelajaran berdiferensiasi. Metode yang digunakan adalah Participatory Action Research (PAR) dengan tahapan identifikasi kebutuhan, pelatihan intensif, praktik penyusunan bahan ajar berbasis AI, serta evaluasi berkelanjutan selama satu bulan. Hasil kegiatan menunjukkan peningkatan signifikan dalam literasi digital, keterampilan teknis, serta kreativitas guru dalam pembuatan modul ajar interaktif dan kontekstual. Selain itu, terbentuk komunitas belajar mandiri yang mendorong inovasi berkelanjutan di lingkungan sekolah. Program ini membuktikan bahwa pelatihan partisipatif disertai pendampingan intensif mampu mengatasi keterbatasan infrastruktur dan literasi digital, serta menjadi strategi efektif dalam mewujudkan transformasi pembelajaran digital di daerah berkembang. Kegiatan ini diharapkan menjadi model replikasi bagi guru-guru sekolah lain dalam mengintegrasikan kecerdasan buatan sebagai bagian integral inovasi Kurikulum Merdeka
Co-Authors Andi Kresna Jaya Anisa Anisa Harismahyanti A Andi Harismahyanti A., Andi Jamidun Jamidun Morina A. Fathan Nurul Fiskia Gamayanti Sitti Nurhaliza