Indonesian Tsunami Research Articles

Prediction of Tsunamis in Indonesia Using an Optimized Neural Network with SMOTE

Tsunamis have the potential to have a large impact on the environment, therefore early detection and preparation for tsunami need to be carried out to reduce the impact of casualties and losses incurred. This research aims to predict tsunami events due to large earthquakes in Indonesia as a form of early detection. The optimized neural network method is used in research to classify tsunami events in Indonesia in 2000-2023 for large earthquakes with strength more than 5 magnitudes. The research results show that the neural network structure formed consists of an input layer, a hidden layer, and an output layer. The results of the evaluation of the neural network model with SMOTE obtained an accuracy value of 99.43%, precision of 96.31%, and an F1 score of 97.86%, which means the resulting model is good. Therefore, an optimized neural networks can be applied as a warning system in various regions to detect potential tsunami events in the future.

A New Multi-Purposes Flume Experiments Facility: Challenges and Opportunity for Tsunami and Coastal Engineering in Indonesia

A New Multi-Purposes Flume Experiments Facility: Challenges and Opportunity for Tsunami and Coastal Engineering in Indonesia

Preliminary study of tsunami simulations on megathrust earthquake scenarios in Pacitan Regency, East Java

During the period 1600 to 2007 there have been approximately 109 tsunamis in Indonesia with 90% caused by tectonic earthquakes. Pacitan located in an east java segment subduction area which is very prone to earthquakes and tsunamis. The coastal morphology of Pacitan has great potential for tsunami hazard. This research is focused on conducting numerical modeling of the tsunami generated by the hypothetical megathrust earthquake in the East Java segment with a magnitude of Mw 8.7. The method used is Cornell-Multi Grid Coupled applied shallow water equation with COMCOT 1.7 software. The nested grid system uses 4-layer consisting of 1-layer GEBCO, 2-layer bathymetry, and 1-layer integration of bathymetry and topography to produce tsunami modeling with high resolution. The results showed that the megathrust hypothetical earthquake scenario for the East Java segment caused a vertical displacement at sea level of -4.599 m to 7.019 m. The tsunami propagation northwards towards the Pacitan coast had a maximum amplitude of 33.16 m with a travel time of 23 – 29 minutes and then spreads in all directions. The farthest inundation range occurred in Pacitan Subdistrict as far as 4.189 km to the north of Ranuharjo Beach, while the maximum run-up of 21.82 m occurred in Soge Beach, Ngadirojo Subdistrict. The farthest affected area of inundation occurs on a gently sloping morphology with a slope of 0-8%, the highest run-up is on a moderate to steep sloping morphology with a slope of more than 25%. The results of tsunami simulation can be used for planning tsunami disaster mitigation in Pacitan.

Disaster cultures and the Indonesia Tsunami Early Warning System: (mis)alignments revealed by the 2018 non-tectonic tsunami in Labuan

This study examined the (mis)alignments between multiple disaster cultures, the Indonesia Tsunami Early Warning System (InaTEWS) and local risk profiles as revealed by the 2018 non-tectonic tsunami triggered by the Anak Krakatau Volcanic eruption in Labuan. The research assessed to what extent the tsunami warning system was adapted to local needs and characteristics. Based on qualitative data collection, this study showed that before the 2018 tsunami (and notwithstanding memories of the 1883 Krakatau tsunami) different local groups shared a strikingly homogeneous understanding of tsunamis as exclusively triggered by earthquakes. After the 2018 tsunami, study participants reported increased awareness of different tsunami types and earthquake risks. However, this rarely translated into practical actions and changes at the local level as structural and cultural factors significantly hampered the work of local government and emergency management agencies. This research identified steps to improve alignment, for example by involving community members in warning technology maintenance, tailoring awareness-raising materials to local hazard profiles and connecting awareness-raising with local cultural traditions. However, a reform of the InaTEWS is necessary, including overcoming sectoral silos and incorporating local knowledge and experiences into policymaking. By addressing these (mis)alignments, authorities can better support communities to understand tsunami risks and respond to future event, ultimately enhancing preparedness.

Tsunami tide prediction in shallow water using recurrent neural networks: model implementation in the Indonesia Tsunami Early Warning System

Near-field tides prediction for tsunami detection in the coastal area is a significant problem of the cable-based tsunami meter system in north Sipora, Indonesia. The problem is caused by its shallow water condition and the unavailability of an applicable model or research for tsunami detection in this area. The problem foundation of shallow water area is its ambient noise level-dependent property that requires preprocessing to improve its feature representation. Moreover, because this shallow water is close to the land area, we must consider a model that can accommodate low prediction time for a Tsunami Early Warning System. Therefore, we propose a recurrent neural network (RNN) model because of its reliable performance for time series forecasting. Our report evaluates variants of the RNN model (the vanilla RNN, LSTM and GRU models) in tides prediction and z-score analysis for tsunami identification. The GRU model overwhelms the other two variants in error scores and time processed (training and prediction). It can achieve median error score distribution of 7.8×10-5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$7.8 \ imes 10^{-5}$$\\end{document} on the L1000-P250 configuration with time prediction under 0.1 s. This lower-time prediction is necessary to ensure the early warning system is going well. Moreover, the GRU model can identify all synthetic tsunami tide spikes (compared with the ground truth result) from magnitude 7.2–8.2 by applying a z-score on the GRU’s prediction.

Reinforcement learning for humanitarian relief distribution with trucks and UAVs under travel time uncertainty

Effective humanitarian relief operations are challenging in the aftermath of disasters, as trucks are often faced with considerable travel time uncertainties due to damaged transportation networks. Efficient deployment of Unmanned Aerial Vehicles (UAVs) potentially mitigates this problem, supplementing truck fleets in an impactful manner. To plan last-mile relief distribution in this setting, we introduce a multi-trip, split-delivery vehicle routing problem with trucks and UAVs, soft time windows, and stochastic travel times for last-mile relief distribution, formulated as a stochastic dynamic program. Within a finite time horizon, we aim to maximize a weighted objective function comprising the number of goods delivered, the number of different locations visited, and late arrival penalties. Our study offers insights into dealing with travel time uncertainty in humanitarian logistics by (i) deploying Unmanned Aerial Vehicles (UAVs) as partial substitutes for trucks, (ii) evaluating dynamic solutions generated by two deep reinforcement learning (RL) approaches – specifically value function approximation (VFA) and policy function approximation (PFA) – and (iii) comparing the RL solutions with solutions stemming from mathematical programming and dynamic heuristics. Experiments are performed on both Solomon-based instances and two real-world cases. The real-world cases – the 2015 Nepal earthquake and the 2018 Indonesia tsunami – are based on locally collected field data and real-world UAV specifications, and aim to provide practical insights. The experimental results show that dynamic decision-making improves both performance and robustness of humanitarian operations, achieving reductions in lateness penalties of around 85% compared to static solutions based on expected travel times. Furthermore, the results show that replacing half of the trucks with UAVs improves the weighted objective value by 11% to 56%, benefitting both reliability and location coverage. The results indicate that both the deployment of UAVs and the use of dynamic methods successfully mitigate travel time uncertainties in humanitarian operations.

Social capital and community integration in post-disaster relocation settlements after the 2004 Indian Ocean Tsunami in Indonesia

The permanent relocation of persons from areas threatened by environmental stress is widely seen within the international humanitarian sector as problematic due to negative social and economic impacts. However, relocation is increasingly seen as a likely, if unfortunate, response to climate change as rising sea-levels, changing ecological conditions, and increasingly intense disasters create powerful push factors. The more dramatic examples of environmental migration focus on long-distance movements, including crossing national borders, which raise issues about the importance of social capital for migrants trying to build community cohesion and integrate into different cultural contexts. However, it is likely that most relocation because of environment stress will occur at sub-national to very local geographic scales, similar to what happens after large-scale disasters, meaning that persons might be resettled within familiar cultural, linguistic, and religious contexts. In this paper we use qualitative data collected in 12 resettlement complexes built in Aceh, Indonesia for persons displaced by the 2004 Indian Ocean Tsunami to analyze the importance of social capital for building cohesion within resettlement complexes and between resettlement complexes and host communities. We find that even though tsunami-affected persons were generally relocated less than 20 km from their pre-tsunami homes, there were clear social distinctions between resettled persons and host communities, which had practical impacts on integration, access to resources, and participation within local governance structures. We found shared cultural and religious traditions and social practices served as important sources of bonding capital within resettlement complexes. However, the same attributes were less effective as bridging capital between resettlement complexes and their host communities. These findings show that governments and NGOs need to be cautious about underestimating the negative social disruptions caused by short-distance relocation and the importance of bonding social capital for fostering stable and sustainable resettlement communities.

Development of a tsunami early warning system on the coast of Palu based on maritime wireless communication

Indonesia, located in the “Ring of Fire” zone, is a tsunami-prone area, especially those earthquake-induced. Therefore, a tsunami early warning system is crucial for reducing potential damage. Ina-TEWS is an Indonesian tsunami early warning system that relies on buoys, uses seismic sensors to detect a tsunami, sends out its warning within 5 min. Ina-TEWS requires maintenance and supervision, especially since 22 buoys were declared lost or damaged in 2012–2018. Therefore, Indonesia needs a faster and more reliable backup early warning system. This study proposes a new method by integrating maritime wireless communication between ships on the open sea and ship-to-coastal radio stations in the Palu Port. The ships used are passenger ships equipped with VHF radio communication which is the main working frequency for signal propagation. Numerical modeling of tsunamis was carried out using Delft3D and Delft Dashboard, using earthquake and fault parameters from PUSGEN. The output of this study is the required VHF signal propagation times for each tsunami scenario less than 1 min. Standard operating procedure (SOP) has also been developed based on the worst scenario. The development of this system is expected to enhance tsunami mitigation systems in Indonesia by replacing the buoys in the future.

PERANCANGAN APLIKASI PEMBELAJARAN BENCANA TSUNAMI DI INDONESIA BERBASIS WEB

The Web-Based Design of a Tsunami Disaster Monitoring Application in Indonesia aims to make it easier for users to obtain information related to Tsunami Disasters in every province in Indonesia. This application aims to provide information ranging from total cases, active cases, dead victims, survivors, missing victims and information related to the Tsunami in Indonesia. Users can see data visualization in the form of a map of Tsunami cases and the total number of survivors in Indonesia. The design of this application uses the Waterfall model System Development Life Cycle (SDLC) development methodology. The database used in this application is MySQL.
 Mapping in this application uses the Leaflet system
 which can display data and map visualization of Indonesia. The programming languages used are HTML and PHP. The test results show that this application can be understood and used to find information from the Tsunami Disaster in Indonesia.

Developing pedestrian evacuation path parameters based on the requirements of Indonesia National Agency of Disaster Management and the Indicators of the Global Walkability

The tsunami incident in 2004, in Aceh, was killed around 230,000 people and destroyed more than 1,000 buildings. Many accidents also occurred related to the earthquakes and tsunamis in Indonesia. For example, when the big earthquakes happened in Padang City, people evacuated themselves by using cars or motorbikes (motorized movement). It created a problem; and became worse when the movement was not effective. All research related to evacuation movement suggested that walking is better than moving using vehicles. Thus, people who will evacuate by walking should be supported by good and sufficient infrastructure, such as the path. Up to recent time, there has been no research conducted in relation to finding the solution this problem. Therefore, this article reports on the research that focused on the parameters of the path design. The validity and reliability of the test, were measured by experts. The research respondents filled the form and their responses were taken as the data analyzed to get the parameters, indicators, and levels based on the adjustment of BNPB (National Agency of Disaster Management) and GWI (Global Walkability Indicators) guidelines. In conclusion, the four parameters: walking path mode conflict, availability of walking path, amenities, and obstruction were found.

Assessing tsunami vertical evacuation processes based on probabilistic tsunami hazard assessment for west coast of Aceh Besar, Indonesia

BackgroundTsunamis are rare events compared to other disasters but have devastating consequences. In the last 100 years, more than 24 tsunamis and more than 235,000 fatalities have occurred globally. Indonesia has a high risk of a tsunami disaster. Since the devastating 2004 tsunami in the Indian Ocean, much research and preparatory work have been done to reduce the impact of future tsunamis in Indonesia, including in the province of Aceh, especially along the western coast where West Aceh is located. This coastal area was destroyed by a tsunami as high as 15–30 m, resulting in the loss of life, housing, tourist areas, industrial areas, and other public facilities. Given that tsunami disasters are rare and sometimes occur long in advance, human memory and awareness are reduced, making research on the level of tsunami awareness of disasters a challenging task.MethodProbabilistic Tsunami Hazard Assessment (PTHA) is a method that has been developed to predict tsunami hazards with a return period of hundreds to thousands of years, beyond the limited availability of historical data. The PTHA method can provide important information that supports tsunami risk management measures. This study aims to estimate recurrence period-based tsunami risk on the west coast of the district of Aceh Besar using the PTHA method. In this study, the source of the tsunami is caused by fault activity at sea. Seven tsunami scenarios based on fault parameters (earthquakes of magnitudes Mw 8.0 to 9.2 with interval 0,2) with the fault location focusing on the Aceh-Andaman Mega Thrust Segment, as applied in this study. This segment was a similar source to the 2004 Indian Ocean tsunami that created a rupture area along a distance of 1155 km, with six parts of the fault.ResultThe maximum inundation distance reached 6 km for the flat area, with a flow depth of 13 m. The site has a cliff that is close to the shoreline, with an inundation distance shorter than the distance across the flat area. With an arrival time of less than 25 min, it is recommended to have an evacuation building and evacuation road in a wide inundated area, and an arrangement of hills close to the beach as an evacuation area, in order to reduce the number of casualties. For 100 years return period or exceedance probability rate 0.01, the average flow depth on the coast may exceed 5 m, and the maximum flow depth for a 1000-year return period or annual probability of 0.001 is 12 m. With the potential tsunami in the future, continuous tsunami drills and tsunami education are needed so that people can maintain an awareness of the threat posed by tsunamis.

MBKM Project: The Filmaking Process of "Indonesia Tsunami Alert" Campaign Video for Disaster Education

The Indonesian government continues to strive to reduce the risk of disasters including tsunamis disaster. In the case of earthquakes that have occurred in Aceh, in the southern region of Java to Bali, there is a layer of sediment that is suspected to be strongly used by tsunamis from different times. This fact requires special attention and effort in risk communication. Previous studies have shown that there is an important role for the mass media to influence perceptions for disaster preparation. Therefore, the campaign video "Indonesia Tsunamy Alert" as one of the disaster mitigation efforts. This paper describes the process of making a video from the corner of the filmaker field.

In response to crisis: the use of songs to respond to multiple crises in Yusuf Islam (Cat Stevens)' post-conversion lyrical compositions

Yusuf Islam, also known as Cat Stevens, is a well-known singer and songwriter. He had decided to avoid the music industry for many years. He focused more on humanitarian activism as well as building educational institutions in London. In 2006, through the release of the album entitled "An Other Cup", Stevens marked his return to popular music with a strong intention to carry his Islamic vision. Furthermore, he connected his humanitarian activism with his lyrical compositions. The artist has shown very intense participation in crises that happened across countries. In dealing with these crises, the use of a single seemed very rational since such crises need a fast response and a single song is easier to compose than an album. The result of those circumstances is Stevens' releasing several songs in response to multiple crises across different countries. He released "The Little Ones" to voice the misery of the genocide in Bosnia. Similarly, Islam released "Indian Ocean" for the victims of the tsunami in Indonesia, "My People" to support people's freedom regarding political turmoil in the Arab world, such as Egypt and Tunisia, and "He Was Alone" to show sympathy for children's refugees at the Syrian-Turkish border. These responses were all released in his post-conversion phase. This essay argues that Islam, also known as has used his post-conversion lyrics, particularly his singles, to help voice the misery of the victims of multiple crises.

A new dual earthquake and submarine landslide source model for the 28 September 2018 Palu (Sulawesi), Indonesia tsunami

ABSTRACT The September 2018 Palu (Sulawesi, Indonesia) tsunami has been a heavily debated event because multiple source models of three different types have been proposed for this tsunami: (i) The Mw 7.5 earthquake, (ii) landslides, and (iii) dual earthquake and landslide. Surprisingly, all of these three types of models were reported as being successful in the literature in terms of reproducing the existing tsunami observations. This can be partly attributed to the limited observations available for this tsunami. This study is motivated by the results of a marine bathymetric survey, which identified evidence for submarine landslides within the Palu Bay. Our modeling shows that the tsunami cannot be exclusively attributed to the Mw 7.5 earthquake. Inspired by the results of the marine survey, we propose a dual source model including a submarine landslide although most of the existing models include subaerial coastal landslides. Our dual model comprises an earthquake model, which has a length of 264 km, a width of 37 km, and a slip of 0–8.5 m, combined with a submarine landslide with a length of 1.0 km, a width of 2.0 km, and a thickness of 80.0 m located at 119.823°E and −0.792°S.

Seismic Noise Analysis in InaTEWS Earthquake Station Network (Case Study: Flores Earthquake 7.4, 14 December 2021)

Meteorological, Climatology and Geophysics Agency (BMKG) is the agency responsible for providing information on earthquake parameters in Indonesia. BMKG has installed 411 seismometers network spread across Indonesia, this network is known as the Indonesia Tsunami Early Warning System (InaTEWS) network. The dense distribution of the seismometer is expected to be able to provide accurate earthquake parameter results. However, the accuracy of earthquake parameters does not only depend on many stations but also on the quality of the data recorded by the seismometer. In this study, an analysis of 15 data quality was carried out at the nearest station that recorded the Flores earthquake on December 14, 2021. Analysis of data quality using the power spectral density (PSD) and probability density functions (PDFs) methods, where good data quality can be seen in the spectrum of the seismograph recordings that are between the Peterson’s new high noise model (NHNM) and new low noise model (NLNM).

Seismic Data Quality Analysis Based on Image Recognition Using Convolutional Neural Network

Seismometer monitoring and evaluation activities at the Indonesia Tsunami Early Warning System (InaTEWS) station can be carried out through a seismometer sensor calibration system with the use of the software of Seismic Data Quality Analysis. The software output is in the form of a spectrum image that represents the conditions of the seismometer following the spectrum results. The identification of the seismometer condition can be made by pattern recognition in the spectrum image. This study employed a neural network, specifically the Convolutional Neural Network (CNN), to analyse the pattern condition. The test results show that the performance of the system will be excellent if 1024 hidden layers are used. In addition, the epoch test shows that the system works well when given a maximum epoch value of 50. The test of image size gives the result that the system performance will result in good using input with a size of 30x20 pixels. The final results of the classification of spectrum images using CNN will exhibit the identification of seismometer. For the validation, the confusion matrix test shows that the corresponding findings are 80%, while the conflicting results are 20%.

Children or adolescents who lost someone close during the Southeast Asia tsunami 2004 - The life as young.

IntroductionTo lose a person close suddenly, during childhood or adolescence, can be devastating. Many children or adolescents experienced the 2004 Indonesian tsunami when they were between 10‐ and 15‐years‐old. This study, from Stockholm, Sweden, describes the long‐term effects of loss, eight‐ or nine‐years post disaster, in young adulthood.MethodA mixed‐method approach was used including statistical analyses (n = 210) and interpretative phenomenological analysis (IPA).ResultsIt was shown that there was a significant difference between bereaved (n = 34) and nonbereaved (n = 176) respondents concerning, psychological distress, posttraumatic stress symptoms, and self‐rated health. Three themes were found by using the IPA approach (n = 9): Living in traumas, carrying heavy baggage, and living with change.ConclusionThe respondents described personal feelings of grief that are not expressed in their outward appearance or behavior in their daily living. When meeting young adults that have lost someone close in childhood or adolescence, this is important to have in mind.

Indonesia paleotsunami database as an effort to reduce the tsunami disasters in Indonesia

Indonesia’s tectonic activity is one of the most active in the world. These conditions make Indonesia prone to earthquakes, tsunamis, and volcanic eruptions. Tsunamis are large ocean waves that are formed through several processes such as underwater earthquakes, underwater landslides, volcanic activity, and asteroid impacts. Indonesia has been hit by various tsunami events. However, not all characteristic tsunami events are well known and recorded. Knowing the characteristics of a tsunami occurrence is very important to understand the frequency and intensity of tsunamis in the present. This research create a WebGIS database for paleotsunami in Indonesia. Tsunami incident data comes from literature related to tsunami events such as books, journals, reports, final projects, and others. Making WebGIS in this study will be developed using website programming, namely HTML, CSS, and JavaScript. The research results obtained 302 tsunami data. The period of tsunami in this research is from Late Miocene to the last tsunami in 2018. The WebGIS created presents a database of tsunami events in Indonesia, a dashboard of Indonesian tsunami statistics, and a tsunami learning educational feature. It is hoped that the results of this database will serve as a means of information for future paleotsunami research needs and as a means of education regarding the potential for tsunamis in Indonesia.

Fatigue Life Prediction of Mooring Line on Indonesian Tsunami Early Warning Systems (Ina-TEWS) Buoy

Ina-Buoy Gen 3.1 is one of the application of the program that has been developed by BPPT (Agency for the Assessment and Application of Technology) in order to reduce the risk of a tsunami disaster in Indonesia. This Indonesian Buoy for Tsunami Early Warning System (INATEWS - Buoy) consists of a tsunami buoy, an ocean bottom unit (OBU), a satellite and a ground station. This paper discuss about calculation of fatigue life due to wave loads for the mooring line that used to hold the buoy position in the sea. A taut mooring system is applied to the buoy until sinker at seabed. Calculation of operational tension at mooring line obtained using numerical simulation fully licensed software Orcaflex ver 11 owned by Centre Technology for Maritime Industrial Engineering (PTRIM), BPPT with wave input of Hs=2.5m and Tp=10.5sec. The depth of sea is varied at 2088m (Sunda Strait), 3563m (Cilacap Sea) and 4082m (Bali Strait). By knowing those tension forces, stress at time history on the mooring line can be obtained. This stress time history is then applied to Palmgren – Miner formula that based on SN-Curve of the mooring line material to predict the life of the mooring line. By applying a safety factor of 2.5 it is found that the fatigue life of the mooring line at water depth of 2088m in Sunda Strait is 6,9 years, then, at water depth of 3563 m in Cilacap Sea is 15,8 years, finally at water depth of 4082 m in Bali Strait is 10 years.

Application of the clarke-wright algorithm in determining tsunami disaster evacuation route in Purworejo district

The potentials for tsunami in Indonesia are spread over many areas, one of which is Purworejo. Purworejo has a high tsunami potential because it is located on the Indo-Australian plate. In Central Java, Purworejo occupies the 3rd position in the tsunami-prone area. Therefore, a route is needed to evacuate the population to mitigate the tsunami. This research focuses on two sub-districts, namely Ngombol and Purwodadi. The problems in this paper are: (1) Which points can be used as evacuation sites (2) How to model tsunami evacuation routes with graphs (3) What are the optimal evacuation routes. The method used to find the evacuation route is the VRP with time window. The algorithm used is Clarke Wright algorithm. The optimal evacuation route is obtained if all points are evacuated with minimal time and distance. From nine final evacuation points, only 4 points that fulfill criteria for the shortest distance and can be accessed by vehicles. There are eight final routes with minimum time of 42 minutes. Each of depots B3 and C2 has 3 routes. Whereas each of depots C4 and C5 has 1 route.