Didit Adytia

760 total citations · 1 hit paper
94 papers, 479 citations indexed

About

Didit Adytia is a scholar working on Oceanography, Atmospheric Science and Earth-Surface Processes. According to data from OpenAlex, Didit Adytia has authored 94 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Oceanography, 28 papers in Atmospheric Science and 27 papers in Earth-Surface Processes. Recurrent topics in Didit Adytia's work include Ocean Waves and Remote Sensing (30 papers), Coastal and Marine Dynamics (27 papers) and Tropical and Extratropical Cyclones Research (22 papers). Didit Adytia is often cited by papers focused on Ocean Waves and Remote Sensing (30 papers), Coastal and Marine Dynamics (27 papers) and Tropical and Extratropical Cyclones Research (22 papers). Didit Adytia collaborates with scholars based in Indonesia, Netherlands and Malaysia. Didit Adytia's co-authors include Sri Redjeki Pudjaprasetya, E. van Groesen, Semeidi Husrin, Adiwijaya Adiwijaya, Ardhasena Sopaheluwakan, C.J. Lawrence, Andry Alamsyah, Kemas Muslim Lhaksmana, Gegar Prasetya and Putu Harry Gunawan and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Energies.

In The Last Decade

Didit Adytia

80 papers receiving 457 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach

2023 77 citations Sri Redjeki Pudjaprasetya, Didit Adytia et al. profile →

Peers

Didit Adytia

OCEAN

EP

AS

EE

EEE

Paul Elmore United States

Jinah Kim South Korea

Hsien‐Kuo Chang Taiwan

Justin Davis United States

Sri Redjeki Pudjaprasetya Indonesia

Kyu-Han Kim South Korea

Xinwei Chen China

Ove Tobias Gudmestad Norway

Paul Elmore United States

Didit Adytia

150 ×0.8

OCEAN

161 ×1.3

EP

61 ×0.6

AS

40 ×0.4

EE

35 ×0.5

EEE

Citations per year, relative to Didit Adytia Didit Adytia (= 1×) peers Paul Elmore

Countries citing papers authored by Didit Adytia

Since Specialization

Citations

This map shows the geographic impact of Didit Adytia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Didit Adytia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Didit Adytia more than expected).

Fields of papers citing papers by Didit Adytia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Didit Adytia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Didit Adytia. The network helps show where Didit Adytia may publish in the future.

Co-authorship network of co-authors of Didit Adytia

This figure shows the co-authorship network connecting the top 25 collaborators of Didit Adytia. A scholar is included among the top collaborators of Didit Adytia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Didit Adytia. Didit Adytia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Adytia, Didit, et al.. (2025). Modelling of spatially correlated weather-based electricity forecasting using combined frequency-based signal decomposition with optimized boosting approach. International Journal of Electrical Power & Energy Systems. 169. 110698–110698. 1 indexed citations

2.

Pudjaprasetya, Sri Redjeki, et al.. (2024). An efficient two-dimensional non-hydrostatic model for simulating submarine landslide-generated tsunamis. Ocean Engineering. 310. 118750–118750. 2 indexed citations

3.

Adytia, Didit, et al.. (2024). Water Level Time Series Forecasting Using TCN Study Case in Surabaya. SHILAP Revista de lepidopterología. 9(1). 61–69. 2 indexed citations

4.

Kasim, Abdul Rahman Mohd, et al.. (2024). Mathematical Model of Reiner-Philippoff Embedded with Al2O3 and Cu Particles over a Shrinking Sheet with Mixed Convection and Mass Flux Effect. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences. 111(2). 195–213. 1 indexed citations

5.

Adytia, Didit, et al.. (2023). Modelling of Deep Learning-Based Downscaling for Wave Forecasting in Coastal Area. Water. 15(1). 204–204. 11 indexed citations

6.

Adytia, Didit, et al.. (2023). Time Series Wave Forecasting with GRU with Attention Approach, Case Study In Jakarta Bay, Indonesia. 49–54. 1 indexed citations

7.

Adytia, Didit, et al.. (2023). Time Series Forecasting of Electricity Load Using Hybrid CNN-BiLSTM with an Attention Approach: A Case Study in Bali, Indonesia. 460–464. 1 indexed citations

8.

Adiwijaya, Adiwijaya, et al.. (2023). Implementation of CRNN Method for Lung Cancer Detection based on Microarray Data. SHILAP Revista de lepidopterología. 7(2). 600–600. 3 indexed citations

9.

Adytia, Didit, et al.. (2023). Forecasting of GPU Prices Using Transformer Method. SHILAP Revista de lepidopterología. 12(1). 136–144. 1 indexed citations

10.

Kasim, Abdul Rahman Mohd, et al.. (2023). Combined Convective Transport of Williamson Hybrid Nanofluid over a Shrinking Sheet. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences. 110(2). 219–235. 1 indexed citations

11.

Adytia, Didit, et al.. (2023). Tsunami Signal Classification Based on Sea Level Data using Extreme Gradient Boosting Method for Tsunami Early Warning System Modeling. 38. 373–378.

12.

Adytia, Didit, et al.. (2022). A Deep Learning Approach for Wave Forecasting Based on a Spatially Correlated Wind Feature, with a Case Study in the Java Sea, Indonesia. Fluids. 7(1). 39–39. 22 indexed citations

13.

Adytia, Didit, et al.. (2022). Time Series Temperature Forecasting by using ConvLSTM Approach, Case Study in Jakarta. SHILAP Revista de lepidopterología. 6(4). 563–569. 1 indexed citations

14.

Adytia, Didit, et al.. (2022). Time Series Wave Forecasting with Transformer Model, Case Study in Pelabuhan Ratu, Indonesia. 430–434. 2 indexed citations

15.

Adytia, Didit, et al.. (2020). PREDIKSI GELOMBANG EKSTRIM AIR LAUT DI PELABUHAN TANJUNG PRIOK MENGGUNAKAN ALGORITMA ID3. eProceedings of Engineering. 7(1). 4 indexed citations

16.

Gunawan, Putu Harry, et al.. (2019). Openmp and MPI Architectures for Simulating 1D Water Oscillation on Parabolic Domain. International Journal of Engineering & Technology. 8(1.9). 230–236. 2 indexed citations

17.

Adytia, Didit, et al.. (2019). Numerical Studying of Soliton in the Korteweg-de Vries (KdV) Equation. Journal of Physics Conference Series. 1127. 12065–12065. 4 indexed citations

18.

Lhaksmana, Kemas Muslim, et al.. (2018). Pembangunan dan pengujian protokol MQTT & WebSocket untuk Aplikasi IoT Rumah Cerdas berbasis Android. eProceedings of Engineering. 5(2). 4 indexed citations

19.

Lhaksmana, Kemas Muslim, et al.. (2018). Aplikasi IoT untuk Rumah Pintar dengan Fitur Prediksi Cuaca. eProceedings of Engineering. 5(1). 6 indexed citations

20.

Adytia, Didit, et al.. (2007). Near coast tsunami waveguiding: simulations for various wave models. University of Twente Research Information. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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