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All Journal BIMASTER Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Forum Analisis Statistik Fraction: Jurnal Teori dan Terapan Matematika
Siti Aprizkiyandari, Nurul Qomariyah, Shantika Martha,
Universitas Tanjungpura
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences

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PEMODELAN TINGKAT PENGANGGURAN TERBUKA DI KALIMANTAN BARAT DENGAN PENDEKATAN LINEAR MIXED MODEL Miftahul Zannah; Setyo Wira Rizki; Siti Aprizkiyandari
Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 11, No 4 (2022): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v11i4.57773

Abstract

Tingkat Pengangguran Terbuka (TPT) merupakan indikator di bidang ketenagakerjaan untuk melihat dinamika perubahan pengangguran dalam suatu daerah. Angka pengangguran yang rendah dapat mencerminkan pertumbuhan ekonomi dan kesejahteraan penduduk yang baik. Berdasarkan data BPS Kalimantan Barat, Tingkat Pengangguran Terbuka (TPT) secara umum menunjukkan  pola kenaikan mulai tahun 2017 sampai 2020 yang diamati setiap tahun. Kabupaten/Kota di Kalbar memiliki nilai awal  TPT yang berbeda satu sama lain. Keragaman nilai TPT awal dapat dimodelkan menggunakan pendekatan linear mixed model untuk mendapatkan varians yang terjadi dengan menggunakan struktur pengaruh acak. Penelitian ini bertujuan untuk memodelkan keragaman tingkat pengangguran terbuka di Kalimantan Barat serta faktor-faktor yang diduga mempengaruhinya dengan pendekatan linear mixed model. Faktor-faktor yang diduga mempengaruhi tingkat pengangguran terbuka adalah persentase penduduk miskin, persentase penduduk, dan tingkat partisipasi angkatan kerja. Hasil pemodelan TPT dengan pendekatan linear mixed model dapat secara efektif menangkap keragaman yang terjadi pada pola pergerakan antar Kabupaten/Kota. Model terbaik menunjukkan bahwa faktor-faktor yang signifikan mempengaruhi TPT di Kalbar yaitu persentase penduduk miskin dan tingkat partisipasi angkatan kerja dengan pengaruh Kabupaten/Kota. Berdasarkan hasil pemodelan didapatkan kesalahan model terbaik menggunakan MAPE sebesar 14,37% yang artinya akurat. Kata Kunci : Linear Mixed Model, Tingkat Pengangguran Terbuka
PEMODELAN JUMLAH KEMATIAN BAYI AKIBAT TETANUS NEONATORUM DENGAN METODE GEOGRAPHICALLY WEIGHTED ZERO-INFLATED POISSON REGRESSION : MODELING THE NUMBER OF INFANT DEATH DUE TO NEONATORUM TETANUS USING GEOGRAPHICALLY WEIGHTED ZERO-INFLATED POISSON REGRESSION METHOD Astri Maulini; Nurfitri Imro'ah; Siti Aprizkiyandari
Fraction: Jurnal Teori dan Terapan Matematika Vol. 3 No. 2 (2023): Fraction: Jurnal Teori dan Terapan Matematika
Publisher : Jurusan Matematika, Fakultas Teknik, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/fraction.v3i2.43

Abstract

Tetanus Neonatorum (TN) is an infection in infants caused by the Clostridium tetani bacteria. In 2020, the Case Fatality Rate (CFR) due to TN in Indonesia increased to 50% compared to 2019, which was 11.76%. So it is necessary to study the number of infant deaths due to TN. This study discusses the modeling and factors that influence TN disease in Indonesia using the Geographically-Weighted Zero-Inflated Poisson Regression (GWZIPR) method. The GWZIPR model is divided into two based on the state: the ln model for the Poisson state and the logit model for the zero states. The data in this study are the number of infant deaths due to TN, the percentage of pregnant women carrying out Td2+ immunization, the percentage of pregnant women delivering at health facilities, and the percentage of puskesmas carrying out P4K in 34 provinces in Indonesia in 2020. The results of this study are that there is an excess zero of 58.82% and spatial heterogeneity occurs so that each region has a different model based on significant variables. The factors that influence the number of infant deaths due to TN are divided into four groups based on significant variables in the ln and logit models.
Forecasting of Rubber Export Values in West Kalimantan Using the ARIMA Method Hesty Pratiwi; Sy. Farini Nurhaliza; Siti Aprizkiyandari
Jurnal Forum Analisis Statistik Vol. 3 No. 2 (2023): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v3i2.60

Abstract

Rubber is one of the largest commodities in Indonesia after palm oil. Rubber has become the primary export commodity in West Kalimantan. In 2023, the export value of rubber in West Kalimantan experienced fluctuations every month. These changes can have a negative impact on the economy in West Kalimantan. Forecasting the value of rubber exports is crucial because the data on rubber export values is often used as a basis for economic planning in a region. The objective of this research is to determine a suitable model for forecasting the value of rubber exports in West Kalimantan and to forecast the value of rubber exports in West Kalimantan for the next 12 periods using the Autoregressive Integrated Moving Average (ARIMA) method.In the stage of determining the best model, it was found that the best model for forecasting the value of rubber exports in West Kalimantan is the ARIMA (1,1,0) model, with a MAPE (Mean Absolute Percentage Error) value of 20.7%. This means that the forecasting results fall into the acceptable category. The forecasting results can be used as an early warning for policy-making related to rubber exports in the upcoming periods.
Co-Authors Andri andri Astri Maulini Bartolomius Bartolomius Darussalam Darussalam Dini Anggorowati Evy Sulistianingsih Hesty Pratiwi Laksono Trisnantoro Leony Agustine Miftahul Zannah Neva Satyahadewi Nurfitri Imro’ah Nurhalita Nurhalita Nurul Qomariyah Rakhmad Perkasa Harahap Setyo Wira Rizki Shantika Martha Siti Lestari Sulya Hikma Yulandari Sy. Farini Nurhaliza Tantri Palupi