Publications

@article{nokey,

title = {Scaling of waves between monotone slopes},

author = {E. van Groesen and Ayu Shabrina and Arnida L. Latifah and Andonowati},

url = {https://doi.org/10.1016/j.wavemoti.2024.103330},

doi = {https://doi.org/10.1016/j.wavemoti.2024.103330},

year  = {2024},

date = {2024-08-01},

urldate = {2024-08-01},

journal = {Wave Motion},

volume = {129},

number = {103330},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The Rate of Modelling the Change of Hydrodynamic Components and Ecosystem Degradation due to the Existence of Coastal Reclamation Research in 2012-2022},

author = {Subiyanto and Nabilla Azka Putri and Novan Tofany and Mohammad Fadhli Ahmad and Sudradjat Supian},

url = {https://doi.org/10.46336/ijrcs.v5i2.615},

doi = {https://doi.org/10.46336/ijrcs.v5i2.615},

year  = {2024},

date = {2024-08-01},

urldate = {2024-08-01},

journal = {International Journal of Research in Community Services},

volume = {5},

number = {2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Numerical Analysis of Shoreline Changes along the Coast Batu Hiu-Bojong Salawe, Pangandaran Regency, West Java Province, Indonesia},

author = {Subiyanto and Yuyun Hidayat and Saeful Anwari and Mustafa Mamat and Mohammad Fadli Ahmad and Novan Tofany and Sudradjat Supian},

url = {https://doi.org/10.37934/araset.42.2.5871},

doi = {https://doi.org/10.37934/araset.42.2.5871},

year  = {2024},

date = {2024-08-01},

journal = {Journal of Advanced Research in Applied Sciences and Engineering Technology},

volume = {42},

issue = {2},

pages = {58-71},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Effect of bathymetry data on tsunami wave ray tracing in the western Banten sea},

author = {Arnida L Latifah and Henokh Lugo Hariyanto and Rido Dwi Ismanto},

url = {https://doi.org/10.1016/j.csr.2024.105247},

doi = {https://doi.org/10.1016/j.csr.2024.105247},

year  = {2024},

date = {2024-06-01},

urldate = {2024-06-01},

journal = {Continental Shelf Research},

volume = {277},

number = {105247},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Comparison of Statistical and Machine-Learning Model for Analyzing Landslide Susceptibility in Sumedang Area, Indonesia},

author = {Hana Listi Fitriana and Rido Dwi Ismanto and Jessica Stephanie Tulus and Atriyon Julzarika and Jalu Tejo Nugroho and Johannes Manalu},

url = {https://www.gaee.agh.edu.pl/gaee/article/view/470},

doi = {https://doi.org/10.7494/geom.2024.18.2.73},

year  = {2024},

date = {2024-03-16},

urldate = {2024-03-16},

journal = {Geomatics and Environmental Engineering},

volume = {18},

number = {2},

abstract = {Landslides have produced several recurrent dangers, including losses of life and property, losses of agricultural land, erosion, population relocation, and others. Landslide mitigation is critical since population and economic expansion are rapidly followed by significant infrastructure development, increasing the risk of catastrophes. At an early stage in landslide-disaster mitigation, landslide-risk mapping must give critical information to help policies limit the potential for landslide damage. This study will utilize the comparative frequency ratio (FR) and random forest (RF) techniques; they will be utilized to properly investigate the distribution of flood vulnerability in the Sumedang area. This study has identified 12 criteria for developing a landslide-susceptibility model in the research region based on the features of past disasters in the research area. The FR and RF models scored 88 and 81% of the AUC value, respectively. Based on the McNemar test, the FR and RF models featured the same performance in determining the landslide-vulnerability level performances in Sumedang. They performed well in assessing landslides in the research region; therefore, they may be used as references in landslide prevention and references in future regional development plans by the stakeholders.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Landslide-generated wave simulation using coupled multi-phase flow and Boussinesq-type models},

author = {Arnida L. Latifah and Novan Tofany and Mochammad Raja Jaefant Alphalevy},

url = {https://www.sciencedirect.com/science/article/pii/S0029801824007984?dgcid=author},

doi = {https://doi.org/10.1016/j.oceaneng.2024.117461},

year  = {2024},

date = {2024-03-13},

urldate = {2024-03-13},

journal = {Ocean Engineering},

volume = {300},

number = {117461},

abstract = {The effect of landslide-generated tsunami waves on coastal areas can be initially understood through a numerical simulation. Moreover, an efficient numerical simulation would be beneficial for predicting tsunami waves. However, a single numerical model that can capture the landslide and wave propagation is still impractical, especially in a large-scale domain. A domain-partitioning technique or coupling model would be more practical. This paper reports a numerical study of a landslide-generated wave, which uses a multi-phase CFD model for the landslide phenomena and a surface wave model based on Boussinesq-type equations for wave propagation. The proposed coupling model that sits between the multi-phase CFD and wave models validated by laboratory experiments is shown to be effective. The computation domain of the CFD model can be defined as small as it covers the impacted area of the landslide. The rest of the domain can be handled by the wave model that propagates the wave accurately with a low computation cost.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Numerical Simulation of Pipeline Scour and Sedimentation around Submerged Pipelines with an Open-Source Multiphase-CFD Model},

author = {Subiyanto and Novan Tofany},

url = {https://semarakilmu.com.my/journals/index.php/CFD_Letters/article/view/4937},

doi = {https://doi.org/10.37934/cfdl.16.7.150165},

year  = {2024},

date = {2024-02-29},

urldate = {2024-02-29},

journal = {CFD Letters},

volume = {16},

number = {7},

abstract = {This paper presents a comprehensive study on pipeline scour and sedimentation phenomena using an open-source multiphase Computational Fluid Dynamics (CFD) model. The research focuses on understanding the complex interactions between fluid flow, sediment transport, and scour formation around submerged pipelines. The proposed analysis aims to enhance the understanding of scour development and sedimentation deposition, which is crucial for the design, operation, and maintenance of various engineering structures, including offshore pipelines and underwater infrastructure. The results show that the model exhibits the ability to compute sediment transport without depending on traditional assumptions related to bed-load and suspended-load layers. The simulation results affirm the model's proficiency in replicating the underlying mechanisms accountable for the onset of these processes, notably seepage flow and piping. Furthermore, this model can successfully depict the vortex phenomenon, which promotes the accumulation of sediment around the pipe. This phenomenon arises from the contrast in pressure between the centre of the vortex and the pressure exerted on the sediment beneath it.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Significance of weather condition, human mobility, and vaccination on global COVID-19 transmission},

author = {Amandha Affa Auliya and Inna Syafarina and Arnida L Latifah and Wiharto},

url = {https://www.sciencedirect.com/science/article/pii/S1877584524000029},

doi = {https://doi.org/10.1016/j.sste.2024.100635},

year  = {2024},

date = {2024-01-18},

urldate = {2024-01-18},

journal = {Spatial and Spatio-temporal Epidemiology},

volume = {48},

number = {100635},

abstract = {The transmission growth rate of infectious diseases, particularly COVID-19, has forced governments to take immediate control decisions. Previous studies have shown that human mobility, weather condition, and vaccination are potential factors influencing virus transmission. This study investigates the contribution of weather conditions, namely temperature and precipitation, human mobility, and vaccination to coronavirus transmission. Three machine learning models: random forest (RF), XGBoost, and neural networks, are applied to predict the confirmed cases based on three aforementioned variables. All models’ prediction are evaluated via spatial and temporal analysis. The spatial analysis observes the model performance over countries on certain times. The temporal analysis looks at the model prediction of each country during the specified period. The models’ prediction results effectively indicate the transmission trend. The RF model performs best with a coefficient of determination of up to 89%. Meanwhile, all models confirm that vaccination is most significantly associated with COVID-19 cases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wahyuni2023,

title = {Investigation of the Development of Tropical Storm Nicholas based on Global and Regional Climate Data},

author = {Intan Nuni Wahyuni and Ayu Shabrina and Fadhil Lobma and Arnida L. Latifah},

doi = {10.23917/forgeo.v37i2.21728},

issn = {2460-3945},

year  = {2023},

date = {2023-12-29},

journal = {For. Geo.},

volume = {37},

number = {2},

publisher = {Universitas Muhammadiyah Surakarta},

abstract = {This paper studies the simulation of Cyclone Nicholas that occurred close to the coastal area of Western Australia and fell on the mainland of Southwestern Australia. The simulation was conducted via a dynamical downscaling model, Weather Research and Forecasting (WRF), to obtain a higher resolution with reference to the regional climate data. The model simulation is generated using a global reanalysis of climate data for the initial and lateral boundary conditions. We investigated the response of the tropical storm to the model regarding the track and intensity using a modified Kyklop method that appears more appropriate for a landfall cyclone. Our study suggests that the regional climate data computed by the model deviates from the storm track of the global climate data forcing field. In this study, the track of the simulated storm is parallel to the satellite data, but it is shifted slightly to the east, closer to the mainland. Nevertheless, the model simulation can implement the intensity of the storm as strongly as the observation, while the forcing data delivers substantial underestimation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vatresia2023b,

title = {Automatic image segmentation model for indirect land use change with deep convolutional neural network},

author = {Arie Vatresia and Ferzha Utama and Nanang Sugianto and Astri Widyastiti and Rendra Rais and Rido Ismanto},

doi = {10.1007/s41324-023-00560-y},

issn = {2366-3294},

year  = {2023},

date = {2023-11-15},

journal = {Spat. Inf. Res.},

publisher = {Springer Science and Business Media LLC},

keywords = {Artificial Intelligence, Computer Science Applications, Computers in Earth Sciences, Geography},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Current-induced scouring around a submarine pipeline using a multi-phase flow model with different inter-phase drag models},

author = {Novan Tofany and David Eka Putra and Arnida L Latifah},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0029801823020759},

doi = {https://doi.org/10.1016/j.oceaneng.2023.115691},

year  = {2023},

date = {2023-10-15},

urldate = {2023-10-15},

journal = {Ocean Engineering},

volume = {286},

pages = {115691},

abstract = {This paper numerically investigates scouring beneath a submarine pipeline induced by the current. The simulations use an Eulerian–Eulerian multi-phase model for sediment transport developed in OpenFOAM (the open-source Computational Fluid Dynamic toolbox), which can capture fluid–particle–structure interactions. The model implements the Hybrid Fictitious Domain-Immersed Boundary (HFD-IB) method for representing the pipeline structure in the computational domain. The simulated flow fields are validated by experimental data for the developed flow around a pipeline over scoured beds, resulting in favorable results for velocity profiles. Further, three inter-phase drag models, the EF (Engelund and Fredsøe, 1976), RZ (Richardson and Zaki, 1997), and ERZ (Lee and Huang, 2018) are applied and subsequently examined in simulating pipeline scouring, particularly the effects on the flow field, sediment transport, and the resulting scour profile during the onset and tunnel erosion stages. The models produce consistent results with the measured scour profile. All models show that buoyancy is dominant in driving the sand movements within and near the bed surface in both stages. Meanwhile, the drag force is dominant for sand transport above the bed where the inter-phase relative velocity is high. However, the three models differently capture the physical behaviors of the particle response time and relative velocity near the bed surface and within the bed, which impact the computed drag force and, thus, the resulting scour profile.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ismanto2023,

title = {Development of Flood-Hazard-Mapping Model Using Random Forest and Frequency Ratio in Sumedang Regency, West Java, Indonesia},

author = {Rido Dwi Ismanto and Hana Listi Fitriana and Johanes Manalu and Alvian Aji Purboyo and Indah Prasasti},

doi = {10.7494/geom.2023.17.6.129},

issn = {2300-7095},

year  = {2023},

date = {2023-10-13},

journal = {GaEE},

volume = {17},

number = {6},

pages = {129--157},

publisher = {AGHU University of Science and Technology Press},

abstract = {Flooding, often triggered by heavy rainfall, is a common natural disaster in Indonesia, and is the third most common type of disaster in Sumedang Regency. Hence, flood-susceptibility mapping is essential for flood management. The primary challenge in this lies in the complex, non-linear relationships between indices and risk levels. To address this, the application of random forest (RF) and frequency ratio (FR) methods has been explored. Ten flood-conditioning factors were determined from the references: the distance from a river, elevation, geology, geomorphology, lithology, land use/land cover, rainfall, slope, soil type, and topographic wetness index (TWI). The 35 flood locations from the flood-inventory map were selected, and the remaining 18 flood locations were used for justifying the outcomes. The flooded areas from the RF model were 28.39%; the rest (71.61%) were non-flooded areas. Also, the flooded areas from the FR method were 8.02%, and the non-flooded areas were 91.98%. The AUC for both methods was a similar value – 83.0%. This result is quite accurate and can be used by policymakers to prevent and manage future flooding in the Sumedang area. These results can also be used as materials for updating existing flood-susceptibility maps.},

keywords = {Computer Science (miscellaneous), Computers in Earth Sciences, Earth-Surface Processes, Environmental Engineering, Geography},

pubstate = {published},

tppubtype = {article}

}

@article{Latifah2023,

title = {Phase-Resolved Wave Simulation over Isolated Seamount},

author = {Arnida L. Latifah and Henokh Lugo Hariyanto and Durra Handri and E. van Groesen},

doi = {10.3390/jmse11091765},

issn = {2077-1312},

year  = {2023},

date = {2023-09-00},

journal = {JMSE},

volume = {11},

number = {9},

publisher = {MDPI AG},

abstract = {This paper investigates the wind wave deformations above two isolated shallow seamounts using a phase-resolved wave model simulation using the HAWASSI-AB software. The first seamount is located some 8 km from the south coast of Jawa, Indonesia, near Glagah, with its top area about 2 m from the water level, while the second is the Socotra Rock, in the East China Sea, which has a top 4.6 m under the sea surface. The simulations found that isolated shallow bathymetry may generate a crossing sea region endangering ships. In both domains, short-crested wave simulations of second order show strong refraction and diffraction effects when waves run towards and downstream of the top of the seamount. Waves near the summit embrace the seamount and form a focal area with larger waves downstream. After crossing the Socotra Rock, the interaction waves lead to a crossing sea in the deep water. On the other hand, having passed the Glagah, waves further downstream are partly absent over a substantial stretch of the coast. For both cases, the phase-resolved wave simulation results determine detailed wind wave conditions and wave spectra over the whole area, compensating for a lack of experimental data.},

keywords = {Ocean Engineering, Water Science and Technology},

pubstate = {published},

tppubtype = {article}

}

@article{Ismanto2023b,

title = {Comparison Analysis of HIMAWARI 8, CHIRPS dnd GSMaP Data to Detect Rain In Indonesia},

author = {Rido Dwi Ismanto and Indah Prasasti and Hana Listi Fitriana},

doi = {10.31172/jmg.v24i1.863},

issn = {2527-5372},

year  = {2023},

date = {2023-08-08},

urldate = {2023-08-08},

journal = {JMG},

volume = {24},

number = {1},

pages = {9--17},

publisher = {Pusat Penelitian dan Pengembangan Badan Meteorologi Klimatologi dan Geofisika},

abstract = {<jats:p>The need for rainfall data, especially for areas where the number of observation stations is not very close, is very important for local climate analysis activities. This data need can be met, one of which is from remote sensing data, such as Himawari 8. The Himawari 8 rainfall data are data derived using the INSAT Multi-Spectral Rainfall Algorithm (IMSRA) method based on the infrared channel on the Himawari 8 satellite. However, research on the IMSRA method was carried out using a case study of a region in India. Thus, validation is needed to determine the ability of Himawari 8 rainfall data to detect rain in Indonesia. The data used for comparison are CHIRPS and GSMaP rainfall data. In addition, BMKG rainfall data are used as benchmark data. The technique used for validation is using the Contingency Table method. The results of the validation show that the rain detection ability for Himawari 8 rainfall data is relatively good, namely 66% for 2019 and 85% for 2020. In addition, the ability to detect rain using Himawari 8 rainfall data is quite good compared to the ability to detect rain using CHIRPS rainfall data and GSMaP rainfall data.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shabrina2023,

title = {Comparative Analysis of Machine Learning-based Forest Fire Characteristics in Sumatra and Borneo},

author = {Ayu Shabrina and Intan Nuni Wahyuni and Arnida L Latifah},

doi = {10.15575/join.v8i1.1035},

issn = {2527-9165},

year  = {2023},

date = {2023-06-28},

urldate = {2023-06-28},

journal = {join},

volume = {8},

number = {1},

pages = {72--80},

publisher = {Sunan Gunung Djati State Islamic University of Bandung},

abstract = {<jats:p>Sumatra and Borneo are areas consisting of rainforests with a high vulnerability to fire. Both areas are in the tropics which experience rainy and dry seasons annually. The long dry season such as in 2019 triggered forest and land fires in Borneo and Sumatra, causing haze disasters in the exposed areas. This indicates that climate variables play a role in burning forests and land in Borneo and Sumatra, but how climate affects the fires in both areas is still questionable. This study investigates the climate variables: temperature, humidity, precipitation, and wind speed in relation to the fire’s characteristics in Borneo and Sumatra. We use the Random Forest model to determine the characteristics of forest fires in Sumatra and Borneo based on the climate variables and carbon emission levels. According to the model, the fire event in Sumatra is slightly better predicted than in Borneo, indicating a climate-fire dependence is more prominent in Sumatra. Nevertheless, a maximum temperature variable is seemingly an important indicator for forest and land fire in both domains as it gives the largest contribution to the carbon emission.</jats:p>},

keywords = {Artificial Intelligence},

pubstate = {published},

tppubtype = {article}

}

@article{Vatresia2023,

title = {Regression Analysis for Crop Production Using CLARANS Algorithm},

author = {Arie Vatresia and Ruvita Faurina and Yanti Simanjuntak},

doi = {10.15575/join.v8i1.1031},

issn = {2527-9165},

year  = {2023},

date = {2023-06-28},

journal = {join},

volume = {8},

number = {1},

pages = {1--10},

publisher = {Sunan Gunung Djati State Islamic University of Bandung},

abstract = {Crop production rate relies on rainfall over Rejang Lebong district. Data showed a discrepancy between increased crop production and rainfall in Rejang Lebong District. However, the 

spatiotemporal distribution of the crop variable's dependencies remains unclear. This study analyses the relationship between rainfall and crop production rate in the Rejang Lebong district based on the performance of the machine learning method. In addition, this research also performed regression analysis to carry out rainfall clusters and crop production. This order provides information in the form of cluster results to determine how much the rainfall variable influences the crop production rate  in each cluster. Harnessing the Elbow, CLARANS, Simple Linear Regression, and Silhouette Coefficient methods, this study used 231 rainfall data sourced from the Bengkulu BMKG and 110 data for plant production obtained from BPS Bengkulu Province from 2000-2022. This research found that the optimal clusters were 3 clusters. C1 contains 106 data with the largest regression value for chili = 0.127, C2 contains 15 data with the largest regression value for mustard greens = 0.135, and C3 contains 110 data with the largest regression value for cabbage = 0.408, eggplant = 0.197, and carrots = 0.201. Furthermore, this research also found that the biggest correlation of crops with highly significant improvement would be cabbage commodity (Y=0.4114X+0.2013) and chili plantation with high RSME (0.9897).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vatresia2023c,

title = {Analisis Kesuksesan Sistem Informasi Manajemen Daerah (SIMDA) dengan Metode Delone dan Mclean Success Model dan Technology Acceptance Model (TAM)},

author = {Arie Vatresia and Tini Pasaribu},

doi = {10.21456/vol13iss1pp70-77},

issn = {2502-2377},

year  = {2023},

date = {2023-06-05},

journal = {J. Sistem Info. Bisnis},

volume = {13},

number = {1},

pages = {70--77},

publisher = {Diponegoro University},

abstract = {Eight years since the implementation of the Regional Management Information System (SIMDA), there has been no specific research to analyze the information system both in terms of implementation, system quality, user acceptance, and the success of the system in its implementation. This study aims to determine the success of implementing the program at the Bengkulu Provincial DPMD office using the DeLone And McLean IS Success Model and Technology Accepeance Model (TAM) with seven research variables (system quality, information quality, perceived usefulness, perceived ease of use, service quality, user satisfaction, and net benefits). Furthermore, this research provides recommendations that can be used to update SIMDA so that it suits user needs. The seven variables of this study resulted in twelve proposed hypotheses (six were rejected and another was accepted). Six paths of accepted hypothetical relationships are: system quality with ease of use; relationship between information quality and perceived usefulness; relationship between information quality and net benefits; relationship between service quality and perceived ease of use; relationship between perceived ease of use and user satisfaction; and relationship between perceived usefulness and user satisfaction. Meanwhile, the relationship path of the rejected hypotheses is the relationship between system quality and perceived usefulness, the relationship between system quality and net benefits, the relationship between information quality and perceived ease of use, the relationship between service quality and user satisfaction, the relationship between perceived ease of use and perceived usefulness, and the relationship between user satisfaction and net benefits.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sunaryani_2023,

title = {A web-based numerical model for sustainable management of Lake Batur, Bali: Preliminary results},

author = {A Sunaryani and A B Santoso and F H Muttaqien and F Harvianto and H A Rustini and N L Kartini and D Nilawati and E Triwisesa},

url = {https://dx.doi.org/10.1088/1755-1315/1201/1/012049},

doi = {10.1088/1755-1315/1201/1/012049},

year  = {2023},

date = {2023-06-01},

journal = {IOP Conference Series: Earth and Environmental Science},

volume = {1201},

number = {1},

pages = {012049},

publisher = {IOP Publishing},

abstract = {Lake Batur is one of The National Priority Lakes according to President Regulation Number 60/2021 with the target of restoring water quality through the pollution control program for floating net fishery (FNF), agriculture, and other anthropogenic sources around the watershed. The regulation also states several internal measures designed to restore the lake’s water quality. Unfortunately, detailed information on pollution control priorities, the amount that must be controlled for water quality improvements to be visible, and the effectiveness of internal restoration efforts have yet to be obtained. This can hinder the lake restoration process and, furthermore, its sustainable management. This study aimed to develop a web-based numerical model as an open-source web-service for guiding restoration in Lake Batur. It is accessible via the interactive graphical user interface (GUI) running in a standard web browser and includes tools of varying complexity. The platform provides the user with features to set up some parameters, run and analyze the numerical water quality, and the possibility to set up, run and compare various lake management scenarios. The preliminary results show that the model was able to represent existing daily water quality dynamics. Hopefully, the model can be used as a tool for lake restoration and as a part of sustainable lake management.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Aprilina_2023,

title = {The comparison of relationship between climate variables and rice productivity in the clustering area on Java Island, Indonesia},

author = {K Aprilina and A Sopaheluwakan and A Susandi and T W Hadi and N J Trilaksono and A Lubis and W Dayantolis and D S Permana and D E Nuryanto and R Anggraeni and K E Komalasari and Y Fajariana and M S Yuliyanti and U Haryoko and N Hidayanto and U A Linarka},

url = {https://dx.doi.org/10.1088/1755-1315/1167/1/012016},

doi = {10.1088/1755-1315/1167/1/012016},

year  = {2023},

date = {2023-05-01},

journal = {IOP Conference Series: Earth and Environmental Science},

volume = {1167},

number = {1},

pages = {012016},

publisher = {IOP Publishing},

abstract = {This study aims to compare the relationship between climate variables and rice productivity under different irrigation systems (irrigated and rainfed) in the clustering area on Java Island, Indonesia. This study used the clustering areas resulting from the previous study. The climate variables used are bias-corrected MERRA2 data from the period 1987–2017, cropped for Java Island. The rice productivity and reference evapotranspiration data used in this study are the results of the simulation of Aquacrop modeling. The result from the cluster method used tends to divide Java Island into 2 clusters with different altitudes (lowland and highland) areas. The results show that the correlation values between the precipitation variable and rice productivity from Aquacrop simulation (both irrigated or rainfed) in cluster 1 (dominated lowlands) are higher than in cluster 2 (dominated highlands), contrary to that the correlation values between the reference evapotranspiration variable with rice productivity from Aquacrop simulation (both irrigated or rainfed) are higher in cluster 2 (dominated highlands) areas, compared to cluster 1 areas (dominated lowlands). R-square values from response surface methodology (RSM) on the rainfed system in both clusters are higher than those on the irrigated system. This indicates that rainfed agriculture is highly dependent on climate variables, especially precipitation and reference evapotranspiration variables compared with the regular irrigated agricultural system. The RSM result also shows that climate variables significantly contribute to the variation of rice productivity generated by Aquacrop modeling in irrigated and rainfed systems and in all clusters.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vatresia_Utama_2023,

title = {Pemodelan Runtun Waktu pada Pola Kemunculan Penyakit dengan SARIMA},

author = {Arie Vatresia and Ferzha Utama},

url = {https://jurnal.fkmumi.ac.id/index.php/woh/article/view/739},

doi = {10.33096/woh.vi.739},

year  = {2023},

date = {2023-04-01},

journal = {Window of Health : Jurnal Kesehatan},

volume = {6},

number = {2},

pages = {154-166},

keywords = {},

pubstate = {published},

tppubtype = {article}

}