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All Journal Jurnal Ilmiah Matematika Panthera : Jurnal Ilmiah Pendidikan Sains dan Terapan Madani: Multidisciplinary Scientific Journal Socius: Social Sciences Research Journal Parameter: Jurnal Matematika, Statistika dan Terapannya
Haliza, Putri Yusra
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Analisis Faktor-faktor yang Mempengaruhi Keputusan Pembelian Mobil Menggunakan Regresi Logistik Biner Haliza, Putri Yusra; Tamara, Angga; Mario, Christoffel; Hondro, Yizhar Saputra; Siahaan, Linda Natasya; Dalimunthe, Syairal Fahmy
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 2 (2025): March
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15077946

Abstract

This study aims to analyze the factors influencing car purchase decisions using binary logistic regression. Data were obtained from 1,000 respondents with independent variables including age, marital status, gender, car ownership, and income. The analysis results show that marital status, gender, and income significantly influence purchase decisions. Married respondents tend to have a lower likelihood of purchasing a car compared to single respondents, while females have a smaller tendency compared to males. On the other hand, higher income significantly increases the probability of car purchase. The constructed binary logistic regression model has a prediction accuracy of 93.8%, demonstrating its reliability in classifying purchase decisions. This study provides valuable insights for the automotive industry in designing effective and targeted marketing strategies. Additionally, further exploration of other factors such as brand preferences, geographic location, and psychological factors is recommended to enrich the understanding of automotive market behavior.
Strategi Pengelolaan Panti Asuhan dalam meningkatkan Kesejahteraan Anak Asuh di Asrama Sahabat Yatim Medan Aksara N, Nurmayani; Haliza, Putri Yusra; Sarah, Auta Shintha; Faradhilah, Anatasia
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 3 (2025): April 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15145439

Abstract

A good and correct orphan management system greatly affects the fate and future of orphans. The welfare of orphans is not only measured physically, but also mentally and spiritually. This study aims to understand the strategies, programs and challenges faced by the Sahabat Yatim Medan Aksara Orphanage and then provide solutions to any challenges faced. The research method used is a qualitative approach method by conducting interviews with caregivers, foster children, and management staff. Direct observation was conducted to see how the rules are applied, the availability of supporting facilities, the physical and psychological well-being of foster children, and the relationship between foster children and caregivers. The results showed that Sahabat Yatim Medan Aksara Orphanage has implemented rules, provided facilities for education and daily needs but still faced several challenges. Overall, the quality of life of foster children has been improved physically, mentally, and spiritually through good management and a comprehensive welfare program.
Penerapan Regresi Linier Berganda Dalam Memprediksi IPM Berdasarkan Faktor Ekonomi Dan Sosial Di Sumatera Barat Haliza, Putri Yusra; Rafiza, Rizky; Simanullang, Junitro
Socius: Jurnal Penelitian Ilmu-Ilmu Sosial Vol 2, No 12 (2025): July 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15696487

Abstract

Penelitian ini bertujuan untuk menganalisis dan memprediksi Indeks Pembangunan Manusia (IPM) di Provinsi Sumatera Barat berdasarkan faktor-faktor ekonomi dan sosial, yaitu Produk Domestik Regional Bruto (PDRB) per kapita, Angka Melek Huruf (AMH), rata-rata upah karyawan per bulan, dan Umur Harapan Hidup (UHH). Metode yang digunakan adalah regresi linier berganda dengan pendekatan forward selection, menggunakan data sekunder dari Badan Pusat Statistik (BPS) tahun 2020 hingga 2024 dengan total 95 observasi dari 19 kabupaten/kota. Hasil penelitian menunjukkan bahwa seluruh variabel independen secara signifikan mempengaruhi IPM, baik secara simultan maupun parsial. Model yang dihasilkan memenuhi seluruh uji asumsi klasik, seperti normalitas, homoskedastisitas, tidak adanya autokorelasi, dan linearitas. Nilai Root Mean Squared Error (RMSE) yang rendah juga mengindikasikan bahwa model memiliki kemampuan prediksi yang baik. Dengan demikian, regresi linier berganda dapat menjadi pendekatan yang efektif dalam memodelkan dan memprediksi IPM di wilayah Sumatera Barat berdasarkan indikator sosial dan ekonomi. 
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI NILAI UJIAN MENGGUNAKAN REGRESI LOGISTIK ORDINAL Triono, Wira; Haliza, Putri Yusra; Sarah, Auta Shintha; Simorangkir, Agnes Monica
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 3 No 2 (2024): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv3i02pp135-146

Abstract

Penelitian ini menganalisis faktor-faktor yang mempengaruhi nilai ujian siswa dengan menggunakan regresi logistikordinal. Pendidikan merupakan kunci utama untuk kemajuan suatu bangsa, dan pemahaman terhadap faktor-faktor yang memengaruhi kinerja siswa sangatlah penting. Penelitian ini mengkaji faktor internal seperti jam belajar, motivasi, jam tidur, dan kehadiran, serta faktor eksternal termasuk pendapatan keluarga dan jenis sekolah. Menggunakan data sekunder dari dataset "Faktor Performa Siswa" yang tersedia di Kaggle, analisis ini menerapkan model logit kumulatif untuk mengidentifikasi hubungan antara variabel-variabel tersebut. Hasil penelitian menunjukkan bahwa jam belajar dan motivasi memiliki dampak signifikan terhadap nilai ujian, memberikan wawasan berharga untuk pengembangan kebijakan pendidikan yang bertujuan meningkatkan hasil belajar siswa. Penelitian ini berkontribusi pada pemahaman tentang bagaimana berbagai faktor saling terkait dalam keberhasilan akademik, serta menyoroti pentingnya intervensi yang terarah dalam pendidikan.
Prediksi Curah Hujan Bulanan Sumatera Utara Menggunakan Model SARIMA Haliza, Putri Yusra; Auta Shintha Sarah; Didi Febrian; Novel W.M.Simanjuntak
Jurnal Ilmiah Matematika Vol. 13 No. 1 (2026)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jim.v13i1.32153

Abstract

Penelitian ini memiliki tujuan dalam rangka memprediksi curah hujan bulanan di Provinsi Sumatera Utara dengan model Seasonal Autoregressive Integrated Moving Average (SARIMA). Curah hujan di wilayah ini menunjukkan fluktuasi yang tinggi dengan pola musiman, sehingga diperlukan pemodelan yang mampu menangkap karakteristik tersebut. Data yang dipergunakan berupa curah hujan bulanan periode Januari 2016 hingga Januari 2026 yang dianalisis menggunakan Python. Tahapan penelitian meliputi visualisasi data, uji stasioneritas dengan Augmented Dickey-Fuller (ADF), differencing untuk mencapai kondisi stasioner, identifikasi model melalui plot ACF dan PACF, uji signifikansi parameter, serta diagnosis residual menggunakan uji Shapiro-Wilk dan Box-Ljung. Pemilihan model terbaik dilakukan menurut nilai Akaike Information Criterion (AIC) dan evaluasi akurasi menggunakan Mean Absolute Percentage Error (MAPE). Hasil penelitian mengungkapkan bahwasanya model SARIMA(0,1,1)(1,0,1)¹² merupakan model terbaik dengan nilai AIC terkecil sebesar 1258,5816 dan MAPE sebesar 26,63%. Prediksi periode Februari 2026 hingga Desember 2027 mengindikasikan pola musiman yang konsisten, dengan curah hujan lebih rendah pada pertengahan tahun dan meningkat pada akhir tahun, terutama bulan November. This investigation purposes to predict monthly rainfall in North Sumatra Province using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Rainfall variability in this region shows a clear seasonal pattern, making accurate prediction important for climate-related planning and mitigation. The data utilized were monthly rainfall reanalysis data from January 2016 to January 2026, processed and analyzed using Python. The modeling procedure included rainfall visualization, stationarity testing with the Augmented Dickey-Fuller (ADF) test, differencing to achieve stationarity, model identification through ACF and PACF plots, parameter significance testing, and residual diagnostics using Shapiro-Wilk and Box-Ljung tests. Model selection was according to the Akaike Information Criterion (AIC) and forecasting accuracy was evaluated using Mean Absolute Percentage Error (MAPE). The results indicate that SARIMA(0,1,1)(1,0,1)¹² is the best model, with significant parameters, residuals satisfying normality and white noise assumptions, and the smallest AIC value (1258.5816). The model achieved a MAPE of 26.63%, indicating a fairly good forecasting performance. Forecast results for February 2026 to December 2027 show consistent seasonal fluctuations, with lower rainfall in mid-year and higher rainfall toward the end of the year, especially in November.
Analisis Sensitivitas Premi Asuransi Jiwa Berjangka terhadap Suku Bunga dengan Model CIR Berdasarkan Volatilitas & Waktu Haliza, Putri Yusra; Sarah, Auta Shintha; Simorangkir, Agnes Monica
Panthera : Jurnal Ilmiah Pendidikan Sains dan Terapan Vol. 6 No. 2 (2026): April
Publisher : Lembaga Pendidikan, Penelitian, dan Pengabdian Kamandanu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/panthera.v6i2.1235

Abstract

This study aims to analyze the sensitivity of term life insurance premiums to interest rate changes using the Cox-Ingersoll-Ross (CIR) model by considering volatility and coverage period. The study uses interest rate data for the 2021–2025 period obtained from the Central Statistics Agency (BPS) and the 2019 Indonesian Mortality Table (TMI), with a case study of a 30-year-old insured, a sum insured of IDR 100,000,000, and tenors of 5, 10, and 20 years. The results show that the premiums of the CIR model are consistently higher than those of the fixed interest rate model by a difference of around 0.5%–1.5%. Quantitatively, an increase in the interest rate from 3% to 7% significantly reduces the premium, while an extension of the coverage period increases the premium proportionally. Meanwhile, interest rate volatility has a relatively small effect on the premium, in line with the low value of the volatility parameter (σ = 0.00549). Thus, interest rates and coverage terms are the dominant factors in determining premiums, while volatility has a limited influence in the model used.
Co-Authors Auta Shintha Sarah Didi Febrian Faradhilah, Anatasia Hondro, Yizhar Saputra Mario, Christoffel N, Nurmayani Novel W.M.Simanjuntak Rafiza, Rizky Sarah, Auta Shintha Siahaan, Linda Natasya Simanullang, Junitro Simorangkir, Agnes Monica Syairal Fahmy Dalimunthe Tamara, Angga Triono, Wira