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All Journal SAINSMAT Jurnal Riset Pembelajaran Matematika Sekolah SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Parameter: Jurnal Matematika, Statistika dan Terapannya
Hapsari, Nimas Ayu
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Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Education Mathematics Physics

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Pengaruh Model Pembelajaran Search, Solve, Create, and Share (SSCS) terhadap Kemampuan Pemahaman Konsep Matematis Peserta Didik SMP Negeri 15 Kota Tangerang Selatan Hapsari, Nimas Ayu; Salsabila, Ellis; Meidianingsih, Qorry
JURNAL RISET PEMBELAJARAN MATEMATIKA SEKOLAH Vol. 7 No. 2 (2023): Jurnal Riset Pembelajaran Matematika Sekolah
Publisher : Program Studi Pendidikan Matematika FMIPA Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jrpms.072.05

Abstract

Penelitian ini bertujuan untuk mengetahui apakah terdapat pengaruh model pembelajaran Search, Solve, Create, and Share (SSCS) terhadap kemampuan pemahaman konsep matematis peserta didik SMP Negeri 15 Kota Tangerang Selatan. Metode penelitian yang digunakan adalah metode eksperimen semu (quasi experiment). Instrumen penelitian yang digunakan adalah instrumen tes kemampuan pemahaman konsep matematis berupa enam soal uraian yang telah dinyatakan valid dan reliabel. Populasi target penelitian ini adalah peserta didik SMP Negeri 15 Kota Tangerang Selatan. Teknik pengambilan sampel menggunakan Purposive Sampling dan Cluster Random Sampling. Berdasarkan hasil pengujian prasyarat analisis data setelah perlakuan, hasil tes kemampuan pemahaman konsep matematis peserta didik kelas eksperimen dan kelas kontrol berdistribusi normal dan bersifat homogen. Pengujian hipotesis statistik menggunakan Uji-t dengan taraf signifikansi , diperoleh dan . Nilai sehingga ditolak dan diperoleh kesimpulan bahwa rata-rata tes kemampuan pemahaman konsep matematis peserta didik kelas eksperimen lebih tinggi dari kelas kontrol. Besar pengaruh model pembelajaran Search, Solve, Create, and Share (SSCS) terhadap kemampuan pemahaman konsep matematis peserta didik SMP Negeri 15 Kota Tangerang Selatan adalah dengan persentase dan berada pada kategori tinggi. Hal ini menunjukkan bahwa terdapat pengaruh model pembelajaran Search, Solve, Create, and Share (SSCS) terhadap kemampuan pemahaman konsep matematis peserta didik SMP Negeri 15 Kota Tangerang Selatan. Kata kunci: Pembelajaran matematika, kemampuan pemahaman konsep matematis, model pembelajaran Search, Solve, Create, and Share (SSCS).
Risk Factors For Stunting Incidence In Urban and Rural Areas Of Indonesia Using Bayesian Spatial CAR Zulhijrah, Zulhijrah; Rifaldi, Destriana Aulia; Hapsari, Nimas Ayu; Sulaeman, Sulthan Naufal; Aidi, Muhammad Nur
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142712542025

Abstract

Stunting is a chronic growth disorder in children under five that requires evidence-based interventions. To understand the factors that contribute to stunting in different regions of Indonesia, Bayesian Conditional Autoregressive (CAR) modeling was used to estimate the relative risk of stunting. The analysis showed that the Besag-York-Mollié (BYM) model with covariates provided the best results in estimating the risk of stunting. The data for this study were obtained from the 2018 Basic Health Research Survey. In urban areas, immunization coverage has a significant effect on stunting risk, while in rural areas, in addition to immunization, vitamin supplementation coverage and poverty level are also significant factors. Based on the modeling, the region with the highest risk in urban areas is West Sulawesi Province with a relative risk of 1.638, while the lowest is Bali Province with 0.564. In rural areas, Papua Province had the highest risk of 1.820, while North Sulawesi Province had the lowest risk of 0.599. These findings suggest that immunization coverage is instrumental in reducing stunting, both in urban and rural areas. In addition, in rural areas, increasing vitamin supplementation coverage and decreasing poverty levels can help reduce the risk of stunting. Therefore, intervention policies should be tailored to the characteristics of each region to be more effective in addressing stunting in Indonesia.
Risk Factors For Stunting Incidence In Urban and Rural Areas Of Indonesia Using Bayesian Spatial CAR Zulhijrah, Zulhijrah; Rifaldi, Destriana Aulia; Hapsari, Nimas Ayu; Sulaeman, Sulthan Naufal; Aidi, Muhammad Nur
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142712542025

Abstract

Stunting is a chronic growth disorder in children under five that requires evidence-based interventions. To understand the factors that contribute to stunting in different regions of Indonesia, Bayesian Conditional Autoregressive (CAR) modeling was used to estimate the relative risk of stunting. The analysis showed that the Besag-York-Mollié (BYM) model with covariates provided the best results in estimating the risk of stunting. The data for this study were obtained from the 2018 Basic Health Research Survey. In urban areas, immunization coverage has a significant effect on stunting risk, while in rural areas, in addition to immunization, vitamin supplementation coverage and poverty level are also significant factors. Based on the modeling, the region with the highest risk in urban areas is West Sulawesi Province with a relative risk of 1.638, while the lowest is Bali Province with 0.564. In rural areas, Papua Province had the highest risk of 1.820, while North Sulawesi Province had the lowest risk of 0.599. These findings suggest that immunization coverage is instrumental in reducing stunting, both in urban and rural areas. In addition, in rural areas, increasing vitamin supplementation coverage and decreasing poverty levels can help reduce the risk of stunting. Therefore, intervention policies should be tailored to the characteristics of each region to be more effective in addressing stunting in Indonesia.
Forecasting the Inflation Rate Using Long Short-Term Memory Model Based on Consumer Price Index Limba, Syella Zignora; Hapsari, Nimas Ayu; Anggraini, Yenni; Notodiputro, Khairil Anwar; Maulifah, Laily Nissa Atul
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): 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/parameterv4i3pp537-550

Abstract

Human life is constantly exposed to risks such as illness, accidents, and death, which create financial uncertainties for individuals and families. Life insurance serves as an essential financial instrument to mitigate these risks by transferring potential liabilities to insurance companies. This study analyzes premium reserves for whole life and term life insurance using the New Jersey Prospective Method, applying a 6% interest rate and the 2023 Indonesian Mortality Table (TMPI) as the basis of calculation. Actuarial commutation functions are employed to compute annuity values, single net premiums, annual net premiums, and reserve allocations across different ages. The results indicate that reserve values increase with age, reflecting higher mortality risks, with whole life insurance showing a sharper escalation compared to term life insurance. The New Jersey Prospective Method demonstrates accuracy and consistency in reserve estimation, particularly by setting zero reserves in the first policy year, thereby supporting initial liquidity. These findings highlight the method’s effectiveness in maintaining financial stability and readiness of insurance companies to meet future claims and long-term obligations to policyholders.
Co-Authors Anggraini, Yenni Ellis Salsabila, Ellis Limba, Syella Zignora Maulifah, Laily Nissa Atul Meidianingsih, Qorry Muhammad Nur Aidi Rifaldi, Destriana Aulia Sulaeman, Sulthan Naufal Zulhijrah, Zulhijrah