Scenario development to create a sustainable price of rice: A system thinking approach

Suryani, Erma; Hendrawan, Rully Agus; Damanhuri,; Rahmawati, Ulfa Emi; Chou, Shuo‐Yan

doi:10.1016/j.procs.2021.12.178

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…Perform structural testing to ensure all variables are related and nothing is static [29][30][31][32]. Additionally, structural testing should clarify the relationship between each response variable and the appropriate unit.…”

Section: Behavior Stuctural and Model Validationmentioning

confidence: 99%

“…The second test is behavioral validity testing, which is used in model verification to test the nature of the model based on the goals it wants to achieve. In line with [28], the verification process is performed by two test methods, model verification by comparison test (mean comparison) or model verification by amplitude change comparison test (% variance error) [29][30][31][32]. The model is considered valid if in the mean comparison test E1 5% and in the amplitude variation comparison test (% variance error) if E2 30%.…”

Section: Behavior Stuctural and Model Validationmentioning

confidence: 99%

“…The model is considered valid if in the mean comparison test E1 5% and in the amplitude variation comparison test (% variance error) if E2 30%. The system validation process is performed in two experimental ways, which are model validation with mean comparison or mean comparison test statistics [29][30][31][32].…”

Section: Behavior Stuctural and Model Validationmentioning

confidence: 99%

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Increasing rice productivity in presence of climate change using Internet of Things (IoT)

Firmansyah,

Suryani

2024

E3S Web Conf.

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Climate change is becoming increasingly unpredictable. This also has an impact on agriculture, such as the increase in rice productivity. The internet of things is one of the latest technologies that can help increase land productivity. One of the uses of the Internet of things is to identify the temperature and rainfall. The problems currently faced by farmers are determining planting schedules and pest control that caused the decline in rice production. In this study, IoT will be designed to develop smart agriculture using system thinking to increase agricultural dryland productivity where agriculture in Madura is classified as dryland agriculture with rainfall amounts falling into the low-medium category of 50 -150 mm/day, this also affects the temperature in rice cultivation, so the use of IoT will focus on controlling the temperature, pest and stability of the rice paddy soaking water while planting rice until the harvest process for maximum results. The result of this study is a causal loop diagram of internet-based system thinking that can be used as a recommendation to increase agricultural land productivity with temperature, pest and irrigation control using IoT, especially in the form of sensor technology.

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Section: Behavior Stuctural and Model Validationmentioning

confidence: 99%

Section: Behavior Stuctural and Model Validationmentioning

confidence: 99%

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Increasing rice productivity in presence of climate change using Internet of Things (IoT)

Firmansyah,

Suryani

2024

E3S Web Conf.

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“…Pertumbuhan penduduk yang semakin meningkat akan mempengaruhi kebutuhan pangan Pengadaan pangan khususnya beras dalam jumlah yang cukup dan harga yang wajar masih menjadi tujuan utama pembangunan pertanian nasional karena kekurangan beras. Dapat menyebabkan ketidakstabilan sosial dan ekonomi di negara tersebut [6]. Dampak dari tidak stabil harga terhadap penghidupan banyak mendapat perhatian karena berdampak pada sektor lain, termasuk aspek sosial ekonomi [7], berdasarkan uraian dan permasalahan diatas maka dilakukanlah proses prediksi harga beras, dalam proses analisa prediksi yang menggunakan aplikasi Rapidminer dengan menggunakan algoritma neural network dengan penambahan operator windowing dan operator lainnya.…”

Section: Pendahuluanunclassified

Peramalan Harga Komoditas Beras Di Kalimantan Timur Menggunakan Algoritma Neural Network

Adjie Setyadj,

Faqih,

Arie Wijaya

2023

jati

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Beras merupakan salah satu bahan makanan yang sangat penting bagi sebagian besar penduduk Indonesia. Selain menjadi makanan pokok, kebutuhan beras juga semakin meningkat, terutama di Provinsi Kalimantan Timur yang jumlah penduduknya terus bertambah setiap tahun. Kenaikan dan penurunan harga beras sangat mempengaruhi petani karena berdampak pada produksi yang lebih tinggi. Oleh karena itu, diperlukan solusi untuk mengatasi kekhawatiran terkait perubahan tersebut. akan terjadinya naik turunnya harga beras dengan memprediksi harga beras di Kalimantan timur yang bernilai numerik. Penelitian ini bertujuan memprediksi harga beras harian yaitu beras premium, menggunakan sample dataset harga beras. Dengan himpunan data selama 3 tahun terakhir, dari tanggal 25 mei 2020 sampai 20 Desember 2022, yang diperoleh dari Komunitas di Kalimantan Timur yang berjumlah 1001. Metode yang digunakan dalam penelitian ini menggunakan algoritma neural network dengan windowing salah satu cara untuk mengetahui status penjualan beras adalah dengan melakukan prediksi menggunakan algoritma neural network dengan menggunakan aplikasi rapidminer. Hasil eksperimen memprediksi harga beras berhasil. Hasil dari prediksi harga beras model menggunakan algoritma neural network menunjukkan hasil kinerja yang diukur dengan Root Mean Square Error (RMSE) beras premium menghasilkan RMSE sebesar 52,846.

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Enhancing Food Security through Import Volume Optimization and Supply Chain Communication Models: A Case Study of East Java's Rice Sector

Shobur,

Nyoman Marayasa,

Bastuti

et al. 2024

Journal of Open Innovation: Technology, Market, and Complexity

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Scenario development to create a sustainable price of rice: A system thinking approach

Cited by 5 publications

References 20 publications

Increasing rice productivity in presence of climate change using Internet of Things (IoT)

Increasing rice productivity in presence of climate change using Internet of Things (IoT)

Peramalan Harga Komoditas Beras Di Kalimantan Timur Menggunakan Algoritma Neural Network

Enhancing Food Security through Import Volume Optimization and Supply Chain Communication Models: A Case Study of East Java's Rice Sector

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