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All Journal Prosiding Seminar Nasional CORISINDO
Azizah, Istin Fitriani
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Computer Science & IT

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Journal : Prosiding Seminar Nasional CORISINDO

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Prediksi Produksi Jagung dengan Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA) Julyanti , Nafi’ah Zahra; Azmi, Rinda Fitriana; Azizah, Istin Fitriani; Soraya, Siti
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5263

Abstract

West Nusa Tenggara (NTB) is one of the largest corn producing provinces in Indonesia, but its production has not been optimal to meet the increasing domestic and global demand. Along with the rapid growth of industry in the Asian region, the supply of corn in the world market tends to be limited, which is around 13% of the total world corn production, this creates a gap between demand and availability. This study aims to predict corn production trends in NTB using the Autoregressive Integrated Moving Average (ARIMA) method based on time series data from 2001–2023 from NTB Satu Data. The ARIMA method was chosen because of its ability to model historical data patterns without independent variables, making it suitable for short-term forecasting in the agricultural sector. The forecast results show that corn production in West Nusa Tenggara Province is expected to continue to increase from 2024 to 2028, with an average annual growth of 4.78%. However, this growth rate tends to decrease from year to year, indicating a slowdown in the rate of production growth. The use of the ARIMA method is effective as a prediction tool for strategic planning to increase corn production, reduce dependence on imports, and stabilize market prices.
Analisis Regresi Spasial dan Pola Penyebaran pada Kasus Demam Berdarah Dengue (DBD) Hisbullah, Hisbullah; Al Jauziah, Hanief; Soraya, Siti; Azizah, Istin Fitriani
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5264

Abstract

Dengue Hemorrhagic Fever (DHF) is one of the endemic diseases whose spread is greatly influenced by environmental conditions, available health facilities, and the spatiality of an area. This study aims to analyze the pattern of DHF case distribution in NTB Province using the spatial regression method. By utilizing secondary data obtained from 2022, this study also analyzes the influence of five independent variables, namely population, number of general hospitals, poverty rate, number of health centers, and number of houses affected by flooding on the number of DHF cases in each district/city. Spatial analysis was carried out using the Spatial Autoregressive (SAR) model, preceded by a positive spatial autocorrelation test through the Moran index. The results of the study showed significant positive spatial autocorrelation (p <0.05), which indicates that areas with a high number of cases tend to border areas with high cases. The SAR model was proven to be better than the OLS model based on the R² (0.9986) and AIC (101.669) values. This finding is expected to be the basis for planning priority area interventions in controlling DHF cases in NTB Province in a spatial and targeted manner.
Co-Authors Al Jauziah, Hanief Azmi, Rinda Fitriana Hisbullah Hisbullah Julyanti , Nafi’ah Zahra Siti Soraya