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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JUITA : Jurnal Informatika Jurnal E-Komtek Techno Jurnal Pengabdian Teknik dan Sains (JPTS)
Dimara Kusuma Hakim
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Forecasting Air Temperature Using the Triple Exponential Smoothing Method Heri Susanto; Dimara Kusuma Hakim
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 1 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i1.1723

Abstract

Changes in air temperature are a major challenge in Indonesian agriculture. Erratic air temperatures hurt plant growth, so farmers must adjust planting schedules and plant selection according to the air temperature at a certain period. The author aims to predict minimum and maximum air temperatures in Temanggung district in 2024 using the Triple Exponential Smoothing (TES) method. Monthly air temperature data in Temanggung district for the period 2020 to 2023 is used for air temperature forecasting using the TES method. The analysis results show that the TES model can predict air temperature with fairly good accuracy. The minimum temperature is expected to be 23°C, maximum 26-27°C. The research results provide benefits for the agricultural sector in Temanggung. Farmers can use the results of air temperature predictions to adjust planting schedules based on crops that suit the air temperature to minimize the negative impact of air temperature on plant growth and agricultural yields.
Forecasting Rainfall in Planting Onion Crops in Brebes District, Brebes District Using Holt-Winters Exponential Smoothing Nufus Mar'Atu Sholikhah Wasirudin; Dimara Kusuma Hakim
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 1 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i1.1746

Abstract

Planting shallots is very dependent on rainfall. High rainfall when planting shallots can result in shallot plants not growing well, resulting in reduced selling value at harvest time and low rainfall. Therefore, this study aims to determine the rainfall forecasting process for planting shallot plants in Brebes District, Brebes Regency. The data used in rainfall forecasting is monthly data in Brebes District from January 2019 to December 2023 using the Holt-Winters Exponential Smoothing method. Data sourced from NASA's Power Data Access Viewer. In the surface data, get the MAPE value0.05241. Earth Skin Temperature data gets a MAPE value of 2.34346. Wind Speed data gets a MAPE value of 14.5396. DataPrecipitationgot a value of 138.829583. These findings contribute to further understanding regarding rainfall forecasting in shallot planting, which can support the planting process so that the harvest is good and produces high selling value.
Comparison of Double and Triple Exponential Smoothing Methods for Rainfall Prediction Wisnu Adji, Muhammad; Dimara Kusuma Hakim
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 1 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i1.1755

Abstract

Rainfall is water that falls to the ground surface over a certain period and is measured in millimeters (mm). Rainfall is essential for the life of living things. Forecasting plays a significant role in decision-making in modern times, with two main methods: causal models and time series. Time series models have five types of data patterns: random, constant, seasonal, cyclical, and trend. For rainfall forecasting, the Double Exponential Smoothing and Triple Exponential Smoothing methods are used for trend pattern data. This research compares the two approaches based on error values using average rainfall data in Bojonegoro. The results show that Double Exponential Smoothing has a Mean Absolute Percentage Error (MAPE) of 0.6996%, while Triple Exponential Smoothing has a MAPE of 119.1497%. So, Double Exponential Smoothing is more accurate.
Co-Authors Achmad Fauzan Fathul Wahid Fitria Ekowati HERI SUSANTO Hindayati Mustafidah Irfan Ardiansyah Nufus Mar'Atu Sholikhah Wasirudin Sigit Sugiyanto Tresna Yudha Prawira Windy Agus Setiasih Wisnu Adji, Muhammad