Ketersediaan Kedelai Berdasarkan Peramalan Produksinya dan Beberapa Kendala serta Permasalahannya di Indonesia

Nugraha, Dedi; Wardana, I Putu; Adnyana, Made Oka

doi:10.21082/jpptp.v2n3.2018.p155-163

Cited by 6 publications

(5 citation statements)

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“…In contrast, stagnant flooding is the condition of plants being submerged for more than two weeks to several months with an immersion depth about 25-50 cm [19,21]. Depending on the stage of the plant and the typology of the land, under these conditions, the plant may be flooded > 50 cm for several weeks or throughout the life of the plant [22].…”

Section: Potential Constraints and Characteristics Of Swamplandmentioning

confidence: 99%

Productivity and Agronomic Efficiency of Inundation Tolerance Rice in the Swampland: A Review

Yustisia

Raharjo²,

Suparwoto

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Swampland is one of the potential agroecosystems of rice production in Indonesia, but it is classified as marginal in terms of unpredictable inundation, primarily due to global climate change impact. Submergence-resistant variety’s high-yielding and efficient input are one of the efforts to overcome these constraints. The review aims to explore information on the availability and potentiality of immersion-resistant varieties, the efficiency of cultivation technology, and the availability and potentiality of local rice as a source of genes in creating immersion-resistant varieties. The review method is a reference study of different research results. The review results show that five varieties of swampland rice are mainly assembled to withstand immersion in all vegetative phases, namely for six days (Inpara 3) and fourteen days (Inpara 4-5, Inpari 29-30). Based on the Relative Agronomic Efficiency (RAE) parameter, cultivation technology is available. However, information on the research results and its implementation on these five varieties and other high-yielding rice varieties in the swampland is still limited. Sixteen local accessions of inundation tolerance have been identified. Further research is needed on different varieties of immersion resistance, RAE parameters-based cultivation technology, and new immersion-resistant varieties using available local varietal gene donors. This way the availability of effective technology and its dissemination efforts will have the opportunity to be adopted by the stakeholders, thus increasing their productivity and income.

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Section: Potential Constraints and Characteristics Of Swamplandmentioning

confidence: 99%

Productivity and Agronomic Efficiency of Inundation Tolerance Rice in the Swampland: A Review

Yustisia

Raharjo²,

Suparwoto

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…Data mining adalah teknik pengolahan data mentah dalam jumlah besar menjadi bentuk informasi yang berguna dalam pengambilan keputusan [20]. Penambangan data adalah kegiatan yang mengekstraksi informasi penting yang tersirat dan sebelumnya tidak diketahui dari data [21].…”

Section: Tinjauan Studiunclassified

Storage Server Database Utilization Forecasting Using Holt-Winters and Arima Methods in E-Government System. Study at Kemenkeu Ri

Adinda Krida Wicaksono,

Teguh Prasetyo,

Nazori Az

2023

J. Tek. Inform. (JUTIF)

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Storage is a storage medium which is an important part of the system infrastructure. Storage utilization is one of the variables in determining the needs and performance of a system. If the storage is lacking or depleted it will cause the system to be hampered and the possibility of interference occurring. There were eight complaints or reports of system disturbances recorded in the Ministry of Finance's ticketing service desk application caused by anomalies in storage or disk capacity. Things like this can be anticipated if we know the storage capacity requirements for the future. In compiling ICT capacity analysis at Pusintek there has been no use of past data to plan future storage requirements. The use of data mining algorithms can be used to obtain forecast values from storage utilization. The use of the ARIMA model and Holt-Winters Exponential Smoothing as a method used to predict inventory is considered to be a fairly accurate model. Both algorithms are used to compare which accuracy is better in predicting storage requirements by measuring RMSE. Research data was obtained from monthly utilization reports from January 2021 to December 2022. From the evaluation results it can be concluded that forecasting storage server database utilization using the Holt-Winters method is better than the ARIMA method with the RMSE results for the Holt-Winters method being 14332.661717740748 and the RMSE method ARIMA is 20498.977982137938. The results of this forecasting can be utilized in planning database server storage needs.

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“…Penelitian terdahulu menunjukkan bahwa metode peramalan telah dilakukan pada komoditas peternakan dan pertanian seperti rempah-rempah (Fauzi, 2016), kopi (Tantika, et al, 2018), padi (Pratama & Salamah, 2018;Lestari, et al, 2017), Kedelai (Nugraha, et al, 2019), bawang merah (Jatmiko, et al, 2017), ayam potong (Puspitasari & Afianto, 2017) dan sapi potong (Revi, et al, 2018). Khusus untuk peramalan sapi potong, penelitian terdahulu berfokus pada produksi daging (bukan populasi sapi) dan belum memperbandingkan penggunaan beberapa metode peramalan time series sebagaimana dilakukan pada penelitian ini.…”

Section: Pendahuluanunclassified

Peramalan Jumlah Populasi Sapi Potong di Kalimantan Selatan Menggunakan Metode Moving Average, Exponential Smoothing dan Trend Analysis

Jaya¹

2019

JTAI

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Perkembangan produksi daging sapi di Indonesia selama 30 tahun terakhir secara umum cenderung meningkat. Kebutuhan daging sapi di Indonesia masih belum bisa dicukupi oleh supply domestik, sehingga diperlukan impor daging sapi dari luar negeri. Diperlukan kajian tentang proyeksi ketersediaan populasi sapi potong di masa mendatang agar diambil kebijakan yang tepat dalam menjaga stabilitas dan keterpenuhan supply daging nasional. Penelitian ini bertujuan untuk melakukan peramalan jumlah populasi sapi potong menggunakan 3 (tiga) metode peramalan yaitu metode moving average, exponential smoothing dan trend analysis. Hasil peramalan ini selanjutnya diukur akurasinya menggunakan MAD (Mean Absolud Deviation), MSE (Mean Squared Error) dan MAPE (Mean Absolute Percentage Error). Proyeksi populasi sapi potong pada tahun 2019 (periode berikutnya) menggunakan 3 metode peramalan adalah: 195.100 (moving average); 218.225 (exponential smooting) dan 262.899 (trend analysis). Pengukuran akurasi menggunakan MAD, MSE dan MAPE menunjukkan bahwa metode peramalan jumlah populasi sapi potong yang paling akurat adalah peramalan menggunakan metode polynomial trend analysis (MAD 14.716,12; MSE 327.282.084,17; dan MAPE 0,09) karena memiliki tingkat kesalahan yang lebih kecil dibandingkan hasil peramalan menggunakan metode moving average dan exponential smoothing.

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Ketersediaan Kedelai Berdasarkan Peramalan Produksinya dan Beberapa Kendala serta Permasalahannya di Indonesia

Cited by 6 publications

References 0 publications

Productivity and Agronomic Efficiency of Inundation Tolerance Rice in the Swampland: A Review

Productivity and Agronomic Efficiency of Inundation Tolerance Rice in the Swampland: A Review

Storage Server Database Utilization Forecasting Using Holt-Winters and Arima Methods in E-Government System. Study at Kemenkeu Ri

Peramalan Jumlah Populasi Sapi Potong di Kalimantan Selatan Menggunakan Metode Moving Average, Exponential Smoothing dan Trend Analysis

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