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All Journal Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Jurnal Ekologi, Masyarakat dan Sains Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Euclid Asian Journal of Applied Education MARAS : Jurnal Penelitian Multidisplin PRIMER: Jurnal Ilmiah Multidisiplin Emerging Statistics and Data Science Journal
Resa Septiani Pontoh
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Padjadjaran
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Ancaman Resesi: Peran UMKM Dalam Akselerasi Perekonomian Jawa Barat Pasca Pandemi: Ancaman Resesi: Peran UMKM Gumelar, Farhat; Fathia Luthfiah Nur Solihat; Ni Gusti Ayu Putu Meyrasinta Susila; Resa Septiani Pontoh
Emerging Statistics and Data Science Journal Vol. 1 No. 2 (2023): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol1.iss.2.art29

Abstract

Pandemi COVID-19 yang melanda Indonesia, termasuk Jawa Barat berdampak besar pada peningkatan jumlah pengangguran yang tentunya berhubungan dengan keterpurukan kondisi perekonomian. Selain itu timbul isu resesi tahun 2023 pada masa pemulihan pasca pandemi COVID-19 saat ini yang sangat dikhawatirkan oleh khalayak. Usaha Mikro, Kecil, dan Menengah (UMKM) dapat menjadi sumber pendapatan masyarakat dan menyerap ketersediaan angkatan kerja karena menciptakan lapangan kerja baru sehingga dapat mengurangi pengangguran. Pada penelitian ini, ingin diketahui pengaruh jumlah Usaha Mikro, Kecil, dan Menengah (UMKM) dan pengeluaran per kapita terhadap Tingkat Pengangguran Terbuka (TPT) serta memprediksi Tingkat Pengangguran Terbuka (TPT) berdasarkan kedua faktor tersebut serta dilakukan pula analisis klaster hierarki untuk mengelompokkan kabupaten dan kota di Jawa Barat berdasarkan Tingkat Pengangguran Terbuka (TPT), pengeluaran per kapita, dan jumlah Usaha Mikro, Kecil, dan Menengah (UMKM). Hasil penelitian menunjukkan bahwa potensi resesi yang diperkirakan terjadi pada tahun 2023 dapat dicegah melalui pemberdayaan Usaha Mikro, Kecil, dan Menengah (UMKM). Usaha Mikro, Kecil, dan Menengah (UMKM) dapat dengan cepat mencari pasar ekspor ketika dampak resesi mulai terjadi, seperti naiknya harga akibat pemutusan kerja dan adanya inflasi.
Identification and Modelling Tuberculosis Incidence Risk Factors in West Java with Negative Binomial Mixed Model Random Forest Restu Arisanti; Resa Septiani Pontoh; Sri Winarni; Nisa Akbarilah Putri; Stefany Maurin
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.29750

Abstract

Tuberculosis (TB) is a major health problem in many parts of the world, including in West Java Province, Indonesia. Accurate assessment of TB risk factors can improve overall TB control efforts. This study introduces modelling by integrating Negative Binomial Mixed Models (NBMM) and Random Forest (RF) called the Negative Binomial Mixed Model Random Forest (NBMMRF) model. This model is used to identify and assess risk factors associated with the incidence of tuberculosis. Firstly, using NBMM to add fixed effects and random effects in the model and compensate for overdispersion. Afterwards, we included a Random Forest component in the model, which helped us detect relevant predictive features and change model weights accordingly. The resulting Negative Binomial Mixed Model Random Forest has a high accuracy value of up to 0.915. After obtaining the appropriate model, forecasting of tuberculosis cases in 2024 was carried out and the forecasting result was 1904 cases, which increased from the number of cases in the previous year. The results of this study show the importance of various related parties to continue to be vigilant, pay attention to various related risk factors, and continue to make various efforts to study, prevent, and control Tuberculosis disease effectively.
Co-Authors Akbar, Muhammad Faizal Aldi Anugerah Sitepu Asrirawan Bertho Tantular Budi Nurani Ruchjana Dedi Rosadi Defi Yusti Faidah Dewi Arafa Azra Dwi Maharani Fathia Luthfiah Nur Solihat Gumelar, Farhat Gumgum Darmawan Khairunnisa, Hanifah Muhamad Iqbal Mawardi Muhammad Faizal Akbar Ni Gusti Ayu Putu Meyrasinta Susila Nisa Akbarilah Putri Oinike, Aritonang Keshia Pratama, Raissheva Andika Restu Arisanti Sarah Aprilia Setialaksana, Wirawan - Sitepu, Aldi Anugerah Sri Winarni Sri Winarni Stefany Maurin Tri Wulanda Fitri Utami, Yosi Febria Uzzi Ziqma Wibowo, Fellita Odelia Yuyun Hidayat