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All Journal Indonesian Journal of Geography Indonesian Journal of Agricultural Science agriTECH Jurnal Ilmiah Rekayasa Pertanian dan Biosistem SAINS TANAH - Journal of Soil Science and Agroclimatology Jurnal Irigasi Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Pengabdian dan Pengembangan Masyarakat Jurnal Litbang Kota Pekalongan

Bayu Dwi Apri Nugroho

Universitas Gadjah Mada

Author-ID : 2872078

Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Public Health

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Penerapan Sistem Monitoring Lahan dan Analisa Neraca Air Klimatik Pertanian di Lahan Gambut Bayu Dwi Apri Nugroho; Sri Nuryani Hidayah Utami; Benito Heru Purwanto
agriTECH Vol 39, No 2 (2019)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Farming in peatland can produce a commodity well if it follows the right planting calendar. Microclimate conditions in the peatland cannot yet be measured in real-time within a shorter time interval. Pelalawan, a region where most of its farmers use peatland for oil palm cultivation, need guidance on applying the best method of oil palm cultivation, which is possible to improve. This study aims to apply a telemetric based (field monitoring system) real-time climatic data application to monitor the agricultural field (peatland). Climate data and weather – soil sensors were set up in Pelalawan village from August 18 to November 16, 2018. Besides, the advancement of planting calendar determination method is also done for peatland farming with a climatic water balance analysis. The change in peatland farming has been successfully observed and measured. The changes in the climatic environment can be observed continuously within a time interval of 30 minutes. Sun radiation data show a significant fluctuation shift from day to day. It also occurs for rainfall, temperature and humidity data. Climatic data fluctuation can be monitored directly and continuously with a Field Monitoring System (FMS) application. Water balance for paddy and corn is obtained based on Plant Water Need and Effective Rain. The recommended schedule according to water balance analysis (surplus and deficit) is paddy 1 – corn – paddy 2.

Lotka Volterra Model Simulation for Rice-field Rat and Tyto Alba Owls in Sumpiuh District, Banyumas Regency, Central Java Reza Kusuma Nurrohman; Ardiansyah Ardiansyah; Bayu Dwi Apri Nugroho
agriTECH Vol 39, No 4 (2019)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Rice-field rat (Rattus argentiventer) is a rodent that has a high level of productivity. These animals attack rice plants from the vegetative to the generative phase. This research aimed to analyze and to predict the accuracy of the use of owls with mathematical equations model in Kebokura and Lebeng villages, Sumpiuh district. Lotka - Volterra and Competitive Lotka-Volterra models were used to predict the population dynamics of Owl (predator) and rice-field rats (prey), then Runge - Kutta numerical method was applied to analyze the population dynamics of predator and prey at a certain time. The results of the analyses using the Lotka – Volterra, Competitive Lotka - Volterra equations and simulation data, each graph data showed that the rats’ population was able to be maximally suppressed. Based on the analysis result, started with 24 owls and 1,689 rats, the rats’ population could be suppressed to 104 using Lotka – Volterra, and to 176 using the Competitive Lotka – Volterra model. Then in the first and second simulation, started with 50 and 100 owls and 1,689 rats, analysis using Lotka – Volterra and Competitive Lotka – Volterra showed that the rat population could be suppressed to as much as 126, 188 and 145, 189, respectively. Based on the analysis, it could be concluded that use of Serak Jawa owl strategy was able to reduce and stabilize the rat populations. Furthermore, the higher population of owls can prevent the population explosion of rats and can suppress the rat population to a lower number.

Relationships between Sea Surface Temperature (SST) and rainfall distribution pattern in South-Central Java, Indonesia Bayu Dwi Apri Nugroho
Indonesian Journal of Geography Vol 47, No 1 (2015): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Although there has been a high relationship between global climate and rainfall in Indonesia, little evidence is available for relationship between Sea Surface Temperature (SST) and rainfall pattern in highland of country. This study evaluates the relationships between Sea Surface Temperature (SST) and rainfall distribution pattern in Gunungkidul district, highland of South-Central Java, Indonesia. Principal Component Analysis (PCA) approach was used to summarize the average of SSTs during rainy season (October to March) for the El Niño monitoring regions: IOBW (Indian Ocean Basin-Wide), Niño.West and Niño.3. Monthly rainfall data was collected from Agricultural Government of Gunungkidul district. In this area, rainfall was highest in the southern and western mountainous areas, especially near the coast, and SSTs values were highly correlated with rainfall in those areas. Almost all sub districts in Gunungkidul district has significant correlations between PC1 SSTs and rainfall during October-November-December (OND).

Spatial and Temporal Analysis of Seasonal Rainfall on the East Coast of North Sumatra, Indonesia Nuzul Hijri Darlan; Sigit Supadmo Arif; Putu Sudira; Bayu Dwi Apri Nugroho
Indonesian Journal of Geography Vol 52, No 3 (2020): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.56724

The east coast of North Sumatra has lower rainfall than the central (Bukit Barisan) and the west coast. Meanwhile, the literature on the influence of climate phenomena, such as El Nino, La Nina, and positive/negative IOD, on the rainfall distribution in North Sumatra remains quite limited. This paper aims to describe the spatial distribution of seasonal rainfall on the east coast of North Sumatra and its correlation with ENSO and the IOD. Hopefully, the spatial analysis of seasonal rainfall and its correlation to ENSO and IOD can improve the understanding on rainfall distribution and the influenced factors in the study area. For 16 years (1999–2014), the monthly rainfall data at 52 rain gauge stations that passed the homogeneity test were divided into the seasonal 6-month and 4-month. Hereafter, the seasonal rainfall was spatially analyzed with the Inverse Distance Weighting (IDW) method using ArcMap software. The spatial analysis results can clearly describe the rainfall dynamics and its anomalies, therefore, can be more easily understood. The repetition of rainfall anomaly patterns can be seen in January to June (JFMAMJ), January to April (JFMA), and May to August (MJJA), which occurs in 3–4 years. Furthermore, the Pearson-correlation analysis shows that SOI has a strong positive correlation on JFMAMJ (0.529), JFMA (0.485), and MJJA (0.366), while IOD has a strong positive correlation on MJJA (0.512) and negative on September to December - SOND (-0.341).

USING GLOBAL CLIMATE INDICES TO PREDICT RAINFALL AND SUGARCANE PRODUCTIVITY IN DRYLANDS OF BANYUWANGI, EAST JAVA, INDONESIA Muhammad Rasyid Ridla Ranomahera; Bayu Dwi Apri Nugroho; Prima Diarini Riajaya; Rivandi Pranandita Putra
Indonesian Journal of Agricultural Science Vol 21, No 2 (2020): DECEMBER 2020
Publisher : Indonesian Agency for Agricultural Research and Development

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21082/ijas.v21n2.2020.p78-88

In Indonesia, sugarcane (Saccharum officinarum L.) is mostly cultivated in drylands, thus depending on rainfall for crop growth and development. Rainfall is an essential factor affecting sugarcane productivity. The global climate indices can be used to investigate potential of rainfall within a given area and its relationship with crop productivity. This reserach aimed to analyze the relationship between the global climate index, rainfall, and sugarcane productivity in drylands near Glenmore sugar mill, i.e., Benculuk and Jolondoro, Banyuwangi, East Java, Indonesia. The global climate index data used were the Southern Oscillation Index (SOI) and Sea Surface Temperature (SST) between 1995 and 2014. Results of this research showed that SOI and SST can be used to predict the rainfall in both Benculuk and Jolondoro. Rainfall (y) can be predicted with SST data (x) using the equation of y = -352.49x + 7724.1 in Benculuk and y = -107.32 + 3443.4 in Jolondoro, as well as with SOI data (x) using the equation of y = 38.664x + 1555.1 in Benculuk and y = 10.541x + 1567.8 in Jolondoro. Sugarcane productivity (y) in Jolondoro can be predicted using data of total rainfall (x) between October and March with the following equation: y = -0.1672x + 1157.3. This equation can be used by sugar mills, sugarcane growers, and other sugarcane-relevant stakeholders for determining the appropriate growing season.

Dampak Perubahan Curah Hujan Terhadap Tingkat Kerentanan Erosi Tanah Di Sub DAS Merawu, Jawa Tengah Donnie Koes Nugraha; Bayu Dwi Apri Nugroho; Chandra Setyawan
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 10, No 3 (2021): September
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v10i3.356-366

This research was held to estimate rainfall and change in soil erosion vulnerability from 2020 to 2050 in Merawu Sub-Watershed, Banjanegara District with RCP 2.6, 4.5 and 8.5. The RCP is an overview of the concentration trends for greenhouse gases, aerosols and land use change created by the climate modeling community. Rainfall prediction was generated from SDSM Software and combined with USLE to predict soil erosion in ArcGIS 10.4. Changes in rainfall intensity are an important factor in changes of soil erosion rates because the kinetic energy of falling rainwater can cause soil erosion.The results showed rainfall in Banjarnegara Station at 2020-2050 with RCP 2.6,4.5 and 8.5 were increasing by +0,26%; +0,60%; +0,52%, while in Kalisapi Station were decreasing by -1,54%; -1,65% dan -2,20%. The change of soil erosion vulnerability prediction showed that soil erosion in Sub-DAS Merawu at 2020-2050 with RCP 2.6,4.5 and 8.5 in very light category were -0,02%;-0,02%;-0,03%, light category were -0,17%;-0,17%;-0,17%, moderate category -0,05%;-0,05%;-0,04%, heavy category -0,26%;-0,35%;-0,37%, and very heavy category were +1,46%;+1,88%;+1,95%. While the average soil erosion prediction at RCP 2.6, 4.5 and 8.5 were +0,86, +1,19% and +1,03%, respectively. Keywords: soil erosion prediction, rainfall prediction, SDSM Software, Sub-DAS Merawu

Effect of Extreem Rainfall Pattern on The Growth and Yield of Chili Peppers Wini Prayogi Abdila; Bayu Dwi Apri Nugroho; Chandra Setyawan
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 11, No 1 (2022): March
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v11i1.117-129

The purpose of this study was to observe the effect of extreme rainfall patterns in the DI Yogyakarta region on the growths of rawit/cayenne (Capsicum frutescens L.) and keriting/curly (Capsicum annum) chili peppers. The experimental design used was Randomized Complete Block Design (RCBD) with single factor consisting of three levels namely: maximum frequency index (P1), rainfall intensity index (P2), and control treatment (K). The frequency and intensity indexes (P1 and P2) of May-June-July from each weather station were used as the bases of rainfall simulations applied in watering the rawit and keriting chili pepper cultivations. Whilst, control (K) was the watering on the basis of optimum crop water requirement. The growth parameters observed included plant height, number of leaves, age of flowering, age of fruiting, age of first harvest, final weight of biomass, and yield. The data sets were analyzed by using one-way Analysis of Variance (ANOVA) at α=0.05 for each species. The results showed that the three levels of treatments did not significantly affect the growth and yield based on all parameters observed for both of the two species. So even the potted media were flooded, the water easily drained through the holed base of pots, making plant growth undisturbed. This finding suggested that planting chili peppers in pots or elevated media could mitigate the effect of extreme rainfalls.Keywords: Extreme Precipitation, Extreme Indices, Plant Growth, chili pepper

MODEL PREDIKSI LEVEL AIR DI LAHAN PERKEBUNAN KELAPA SAWIT DENGAN JARINGAN SARAF TIRUAN BERDASARKAN PENGUKURAN SENSOR RAIN GAUGE DAN ULTRASONIK Hasan Al Banna; Bayu Dwi Apri Nugroho
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 10, No 1 (2021): Maret
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v10i1.104-112

Monitoring and regulating water levels in oil palm swamps has an essential role in providing sufficient water for crops and conserving the land to not easily or quickly deteriorate. Presently, water level is still manual and has weaknesses, one of which is the accuracy of the data taken depending on the observer. Technology such as sensors integrated with artificial neural network is expected to observe and regulate water levels. This study aims to build a prediction model of water levels in oil palm plantations with artificial neural networks based on the rain gauge and ultrasonic sensors installed on Automatic Weather Station (AWS). The obtained results showed that the prediction model runs well with an R2 value of 0,994 and RMSE 1,16 cm. The water level prediction model in this research then tested for accuracy to prove the model's success rate. Testing the water level prediction model's accuracy in the dry season obtained an R2 value of 0,96 and an RMSE of 1,99 cm. Testing the water level prediction model's accuracy in the rainy season obtained an R2 value of 0,85 and an RMSE value of 4,2 cm. Keywords : artificial neural network, automatic weather station, palm oil, water level

Pengenalan Metode Tanam SRI (System Rice of Intensification) dengan Teknologi untuk Peningkatan Produktifitas dan Ramah Lingkungan Bayu Dwi Apri Nugroho; Chusnul Arif; Nur Aini Iswati Hasana; Rizki Maftukhah; Fadila Suryandika; Umi Hapsari; Badi’atun Nihayah
Jurnal Pengabdian dan Pengembangan Masyarakat Vol 3, No 2 (2020): NOVEMBER 2020
Publisher : Pengabdian dan Pengembangan Masyarakat Sekolah Vokasi UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jp2m.55636

Pengembangan pertanian di lahan iklim kering dengan metode budidaya SRI (System of Rice Intensification) dengan teknologi sederhana dinilai efektif untuk dapat meningkatkan produktifitas lahan. Tujuan dari pengenalan metode tanam SRI dengan penerapan teknologi yaitu memberikan ilmu dan pengetahuan kepada petani terkait metode budidaya pertanian dengan menggunaakan teknologi dalam mengambil keputusan kepada petani dengan harapan dapat meningkatkan produktivitas pertanian serta dapat mengaplikasikan pertanian yang ramah lingungan. Pengabdian ini dilaksanakan di Desa Kambaniru dan Wukukalara, Kec. Kambera, Kab. Sumba Timur, Nusa Tenggara Timur pada bulan Juli 2018-Juli 2019. Indikator keberhasilan dari kegiatan ini (1) Potensi untuk scaling up dan replikasi dari kegiatan ini untuk merubah paradigma (membawa perubahan secara luas). Hal ini terkait dengan resiko budidaya pertanian terhadap perubahan iklim yang terjadi saat ini maupun di masa mendatang (2) Bentuk transfer pengetahuan dan teknologi kepada penerima manfaat (3) Terwujudnya keselarasan dengan kebijakan nasional dan provinsi (4) Tercapainya efektifitas dan efisiensi (kelayakan ekonomi dan kewajaran finansial, serta efektifitas kegiatan). Kegiatan demplot budidaya padi SRI mampu memberi percontohan kepada Kelompok Tani di Desa Kambaniru dan Desa Wukukalara tentang budidaya padi yang ramah lingkungan yang berupa penghematan air dan penurunan gas emisi rumah kaca, serta memiliki produktivitas yang cukup tinggi yaitu sebesar 6.25 ton/ha.

Pembaharuan Konsep Prediksi Debit Andalan untuk Operasi dan Pemeliharaan Irigasi Modern Bayu Dwi Apri Nugroho; Sigit Supadmo Arif
Jurnal Irigasi Vol 14, No 1 (2019): Jurnal Irigasi
Publisher : Balai Teknik Irigasi

The management of conventional irrigation system, which is still being applied in the recent time is probabilistic, especially in analyzing discharge for planning of irrigation operation and maintenance. It can be seen from the process of exerted data analysis, which is two-week or ten-days empirical data analysis. Therefore, to change the management of conventional irrigation system into modern requires flexibly and real-time based due to climate change in Indonesia. The available discharge prediction analysis is done using mathematic model analysis as the replacement of probabilistic model and the use of real time observation data by utilizing automatic weather observation technology. This new concept has been attempted in Irrigation Area of Wadaslintang and Banyumas Regency, showing that automatic weather observation worked successfully and can be used as the data within mathematic model analysis. The result indicates that telemetry instruments work well as expected. The difference between the use of mathematic method of Artificial Neural Network (ANN) with probabilistic method of P80 shows that ANN method is closer to real compared to the probabilistic P80. It is shown with the validation result measured from January to August 2015. Overall, errors between water surcharge prediction with ANN and realisation is 77%. According to the results, it is suggested that dynamic mathematic measurement method is needed, due to dynamic condition of climate in spite of not neglecting probabilistic method as comparison.

Co-Authors Abi Prabowo Ardiansyah -- -- Badi’atun Nihayah Benito Heru Purwanto Benyamin Nahak Chandra Setyawan, Chandra Chusnul Arif Donnie Koes Nugraha Fadila Suryandika Hanggar Ganara Mawanda Hasan Al Banna Hertiyana Nur Annisa Maftukhah, Rizki Milya Aflah Ulul Albab Muchamad Wahyu Trinugroho Muhammad Khoiru Zaki Muhammad Rasyid Ridla Ranomahera Muhammad Wiji Nur Huda Huda Murtiningrum Murtiningrum Ngadisih Ngadisih Nur Aini Iswati Hasana Nuzul Hijri Darlan Prieskarinda Lestari Prima Diarini Riajaya Putu Sudira Reza Kusuma Nurrohman Sahid Susanto SIGIT SUPADMO ARIF Sri Nuryani Hidayah Utami Umi Hapsari Wini Prayogi Abdila

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