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Triharto, Rahmat
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Biochemistry, Genetics & Molecular Biology Chemistry Education Engineering Environmental Science Industrial & Manufacturing Engineering

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IMPLEMENTATION OF CORN PRODUCTION EXPERIENCE 2025-2030 IN INDONESIA USING POM QM APPLICATION Majidah, Alfi Syahriyyah; Putri Apri, Nabila Rizka; Triharto, Rahmat
Jurnal Agroindustri Berkelanjutan Vol 4, No 1 (2025)
Publisher : Jurusan Teknologi Hasil Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jab.v4i1.10774

Abstract

Corn is one of the agricultural products used as a staple food by the Indonesian population. Forecasting is essential to support decision-making by farmers and the government in efforts to continuously improve production. The available data will be analyzed using the POM-QM for Windows Version 5 software, employing several methods: Moving Average, Weighted Moving Average, Linear Regression, Exponential Smoothing, and Exponential Smoothing with Trend. These methods are evaluated based on three error measurements: Mean Squared Error (MSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). The analysis results show that the most effective method for forecasting corn production is the Weighted Moving Average method, as it yields the lowest MAD, MSE, and MAPE values compared to the other methods. Therefore, the Weighted Moving Average method is used to forecast corn production in Indonesia from 2025 to 2030, helping inform management decisions for farmers, business actors, and government policymakers. Key words: forecasting, corn production, POM QM.
PENGARUH PROSES BLANSING DAN SUHU PENGERINGAN PADA BUBUK CABAI MERAH BESAR (Capsicum annuum L.) DAN DAUN JERUK PURUT (Citrus hystrix) TERHADAP SIFAT SENSORI YANG DIHASILKAN THE EFFECT OF THE BLANCING PROCESS AND DRYING TEMPERATURE OF GREAT RED CHILLI POWDER (Capsicum annuum L.) AND KAFFIR LIME LEAVES (Citrus hystrix) ON THE PRODUCED SENSORY PROPERTIES Triharto, Rahmat; -, Suharyono; Suroso, Erdi; Utomo, Tanto
Jurnal Agroindustri Berkelanjutan Vol. 3 No. 1 (2024)
Publisher : Jurusan Teknologi Hasil Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jab.v3i1.8849

Abstract

Large red chilies are a type of plant that has a low shelf life due to their high water content. The way to extend the shelf life is to process it into large red chili powders. The addition of kaffir lime leaves is also needed to add a distinctive aroma and thus increase the attractiveness of chili powder. The quality of a product is influenced by several factors, including the blanching process and drying temperature. The aim of this research was to determine the effect of the blanching process and drying temperature on the sensory properties preferred by panelists. This research used a randomized complete block design (RAKL) with 2 factors. The first factor was the blanching process: without blanching and blanching at 90 °C for 6 minutes. The second factor is drying temperature: oven drying at a temperature of 60 °C, oven drying at a temperature of 70 °C, oven drying at a temperature of 80 °C, oven drying at a temperature of 90 °C. This research was carried out in three repetitions. The data obtained were tested for similarity of variances using the bartlett test, analyzed for variance, and further processed with further orthogonal polynomial comparison tests at the 5% and 1% levels. In this research, the blanching process and temperature differences each had a very significant effect on chili powder production. However, there was no interaction between the blanching process and temperature differences in the production of large red chili powder and kaffir lime leaves.
IMPLEMENTATION OF CORN PRODUCTION EXPERIENCE 2025-2030 IN INDONESIA USING POM QM APPLICATION Majidah, Alfi Syahriyyah; Putri Apri, Nabila Rizka; Triharto, Rahmat
Jurnal Agroindustri Berkelanjutan Vol. 4 No. 1 (2025)
Publisher : Jurusan Teknologi Hasil Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jab.v4i1.10774

Abstract

Corn is one of the agricultural products used as a staple food by the Indonesian population. Forecasting is essential to support decision-making by farmers and the government in efforts to continuously improve production. The available data will be analyzed using the POM-QM for Windows Version 5 software, employing several methods: Moving Average, Weighted Moving Average, Linear Regression, Exponential Smoothing, and Exponential Smoothing with Trend. These methods are evaluated based on three error measurements: Mean Squared Error (MSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). The analysis results show that the most effective method for forecasting corn production is the Weighted Moving Average method, as it yields the lowest MAD, MSE, and MAPE values compared to the other methods. Therefore, the Weighted Moving Average method is used to forecast corn production in Indonesia from 2025 to 2030, helping inform management decisions for farmers, business actors, and government policymakers. Key words: forecasting, corn production, POM QM.
Co-Authors Erdi Suroso Majidah, Alfi Syahriyyah Putri Apri, Nabila Rizka Suharyono - Utomo, Tanto