Rainfall forecasting using PSPline and rice production with ocean-atmosphere interaction

Caraka, Rezzy Eko; Supatmanto, Budi Darmawan; Tahmid, Muhammad; Soebagyo, Joko; Mauludin, M. Ali; Iskandar, Akbar; Pardamean, Bens

doi:10.1088/1755-1315/195/1/012064

Cited by 22 publications

(6 citation statements)

References 7 publications

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“…The clustering pattern can be enriched from the data through clustering analysis using machine learning based on unsupervised. Agricultural data such as rainfall [23], irrigation [24], and yield [25] have been successfully mapped based on AI data patterns. In order to fully enrich our research findings in the future, the use of AI and the inclusion of data measurement parameters can be employed.…”

Section: Rli=relative Light Intensitymentioning

confidence: 99%

Light intensity effect on number of seedlings and growth of Gyrinops versteegii

Rawana

Prijono

Suparyanto

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Due to the depletion of its natural population, the Gyrinops versteegii species, one of the species producing agarwood, has been domesticated in Indonesia, particularly in Sragen Central Java. As a result, it was designated as a vulnerable species in both CITES Appendix II and the IUCN Red List Ver23. The research objective is to determine the effect of the light intensity on the number of seedlings, tree density, height, and diameter of the G.versteegii tree growth. The study was conducted from February to October 2018 at a domesticated agarwood community forest in Sragen, Central Java. A systematic plot method, a random start, was applied to this research with 28 nested plots, 1x1 m2 for seedlings and 10x10 m2 for the trees. The data were analyzed using both hierarchical clustering and correlation analysis. The relative light intensity of 2,82% led to an enormous number of seedlings and tree diameter, while the relative light intensity of 0.31% resulted in the highest tree density. The number of seedlings and tree diameter was strongly correlated with the relative light intensity. In contrast, there is an inverse relationship between tree density and relative light intensity.

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Section: Rli=relative Light Intensitymentioning

confidence: 99%

Light intensity effect on number of seedlings and growth of Gyrinops versteegii

Rawana

Prijono

Suparyanto

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…Specially designed to support agriculture and floriculture supply chains [15,16], IoT management tools provide all the appropriate tools to build and maintain such infrastructure [17] and services. Agricultural data are automated processed [18], corrected, and linked in the modern agricultural scenario under the AI algorithms [19][20][21], machines learning technologies [22,23], and models-driven decisionmaking systems [24], enabling the extraction of knowledge about phenomena that cannot be directly measured [25].…”

Section: Related Workmentioning

confidence: 99%

Smart IoT CPO Storage Tank

Renjani

Hermantoro

Nugraha

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Indonesia’s crude palm oil (CPO) production from year to year continues to increase, at the end of 2020 it reached 17.35 million tons, up 3.6% from the previous year. Increasing production will result in more CPO stock and require good storage. The storage process that occurs is to maintain the temperature of the CPO so that the quality is not damaged. This temperature regulation is still done manually and raises the risk of work accidents. The purpose of this research is to create a temperature control system and automatic volume measurement that can be monitored from a smartphone. The manufacture of a control system used ESP8266 NodeMCu microcontroller, temperature sensor, proximity sensor, and 1000-Watt heater. Programming used the Arduino IDE and C++. The result of this study was an IoT CPO Storage Tank design equipped with sensors and microcontrollers. The temperature was measured with the DS18B20 sensor had a data accuracy of 99.19% while the volume measured with the HC-SR04 sensor had an accuracy of 99.78%. Data obtained from the sensor could be seen through the Thingspeak application from a computer or smartphone.

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“…Model penduga pada Tabel 3 menunjukkan bahwa peristiwa La Nina tahun 2005 (La Nina lemah) dan 2010 (La Nina kuat) berdampak terhadap peningkatan deviasi produksi padi masing-masing sebesar 2,62% (45.726 ton), dan 1,33% (25.898 ton) dari produksi padi ekspektasi. Dampak La Nina cenderung memberikan peluang bagi peningkatan produksi akibat perpanjangan periode musim hujan (Caraka et al, 2018;Fitriani, 2017;Sulistyo et al, 2016). Produksi padi tahun 2005 dan 2010 mengalami kenaikan yang cukup besar dibandingkan tahun sebelumnya.…”

Section: Pengaruh Anomali Iklim Terhadap Fluktuasi Produksi Padiunclassified

The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province

Mulyaqin

2020

J.Agromet

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Rice production in Indonesia is facing serious problem, in which the production is fluctuated causing the unstability in the food supply. One factor influencing the rice productions is climate extreme. Here, we analysed rice production in Banten Province for 2002-2015. The objective of this reasearh was to analyse the effect of climate variability on the fluctuation of rice production in Banten. We relied on data from BPS Banten, which provided timeseries of rice production for 2002-2015. We used four statistical approaches namely linear, quadratic, exponential, and moving average models to detect trend in rice production. Our results showed that Rice Production fluctuated every year indicating an increased trend for the observartion period. Based on the trend analysis, the growth rate for rice production was 1,66% per year. Climate extreme has affected on rice production, with El Niño resulted in the decreasing on rice production, whereas La Nina caused an increased of rice production. Further, to adapt climate extreme events, the government needs to encourage farmers to join the Rice Farming Insurance (AUTP) program to protect rice farming from economic losses due to the climate extreme impacts.

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Rainfall forecasting using PSPline and rice production with ocean-atmosphere interaction

Cited by 22 publications

References 7 publications

Light intensity effect on number of seedlings and growth of Gyrinops versteegii

Light intensity effect on number of seedlings and growth of Gyrinops versteegii

Smart IoT CPO Storage Tank

The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province

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