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All Journal BERKALA SAINSTEK Jurnal Basicedu Parameter: Journal of Statistics Jurnal Basicedu
Fadri, Firda
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics Physics Social Sciences

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Journal : BERKALA SAINSTEK

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Implementation of the Fuzzy Time Series Singh Method for Forecasting Non-Oil and Gas Export Values in Indonesia Borahima, Maharani Safira B.; Sain, Hartayuni; Setiawan, Iman; Fadri, Firda
BERKALA SAINSTEK Vol 12 No 3 (2024)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v12i3.52663

Abstract

Export activities drive a country's economic growth by increasing revenue and strengthening trade relations between countries. In Indonesia, non-oil and gas products are the primary contributors of export performance. In 2022, non-oil and gas exports values reached 275.96 million USD, marking an increase of 25.80% compared to the previous year's export value. This growth in export value was influenced by various external factors, leading to substantial changes. The government requires further analysis to forecast future trends in non-oil and gas export values due to the uncertain and fluctuating patterns. The Singh Fuzzy Time Series method, an advancement of FST, utilizes fuzzy sets to forecast volatile economic data, yielding more accurate predictions. This research used the Singh FST method and achieved a low MAPE value of 1.31%, indicating a high level of accuracy. Forecasts for Indonesia's non-oil and gas export value over the next three months are projected to reach USD 22,263.02 million in January 2023, followed by USD 22,217.21 million in February 2023, and USD 22,243.68 million in March 2023. These export value forecasts can aid the government in policy-making related to exports and sustain the stability of the country’s economic growth rate.
Negative Binomial Regression Modeling to Analyze the Determinants of Infant Mortality in West Java Province Fadri, Firda; Firmansyah, Ari; Erlanda, Victor Alesyus
BERKALA SAINSTEK Vol. 13 No. 1 (2025)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v13i1.53686

Abstract

The Infant Mortality Rate (IMR) is an important indicator in assessing the quality of public health and the success of health programs in a region. Proper handling of factors that determine IMR is essential to reduce this number. The data used were 27 districts/cities in West Java in 2022 with predictor variables including the number of health workers, percentage of poor population, percentage of iron tablet consumption, percentage of clean and healthy living behavior, percentage of exclusive breastfeeding, and percentage of low birth weight babies. The results of the analysis with Poisson Regression showed overdispersion so that IMR modeling was carried out using Negative Binomial Regression. The AIC value for the Negative Binomial Regression model was 305.630 and the BIC value was 315.997. The deviance ratio and Pearson's Chi-square approached one, indicating effective handling of overdispersion. The only significant variable affecting IMR was the percentage of clean and healthy living behavior. This shows the importance of increasing clean and healthy living behavior as the main strategy for reducing IMR in West Java Province.
Co-Authors Ari Firmansyah, Ari Borahima, Maharani Safira B. Erlanda, Victor Alesyus Hartayuni Sain Iman Setiawan Nurisya, Khofifatu Rizka Elan Fadilah, Rizka Elan