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Questions related to Jakarta
Aulia Alamsyah
Aulia Alamsyah
  • asked a question related to Jakarta
How can we define track quality classifications for Jakarta’s LRT after obtaining the final TQI value using the TUG_TQI method?
Question
1 answer
  • 18 Feb 2025
Hi everyone,
We’re implementing the Track Quality Index (TUG_TQI) from Graz University of Technology to evaluate track conditions on Jakarta’s Light Rail Transit (LRT) network. The method aggregates track geometry parameters (gauge, cant, twist) into a single index, but we’re facing a couple of challenges:
1. Adapting TUG_TQI to Local Conditions
  • Jakarta’s LRT has tight curves and low speeds (≤80 km/h).
  • We collect data using a continuous measurement trolley, but longitudinal level (versine) is measured manually, leading to gaps.
Question: How can we tweak the TUG_TQI formula to work with fewer parameters and discontinuous versine data while keeping it reliable?
2. Establishing Track Quality Classifications
TUG_TQI itself doesn’t define quality thresholds like “good,” “fair,” or “poor.” We’re exploring ways to set these thresholds, such as:
  • Statistical methods (e.g., quartiles, standard deviations of TQI distributions).
  • Historical correlation, linking TQI to past maintenance records.
Questions:
  • Are there case studies on defining TQI thresholds for similar networks?
  • How can we adjust normalization and aggregation methods when data is incomplete?
  • Would a hybrid approach (e.g., mixing EN standards with statistical analysis) be a good way to improve classification accuracy?
Any insights, references, or examples from similar rail systems would be greatly appreciated!
Thanks in advance for your thoughts.
References:[1] Offenbacher, S.; Neuhold, J.; Veit, P.; Landgraf, M. Analyzing Major Track Quality Indices and Introducing a Universally Applicable TQI. Appl. Sci. 2020, 10, 8490. https://doi.org/10.3390/app10238490
Relevant answer
  • 1 Mar 2025
Answer
You're tackling a practical and important problem in railway infrastructure management. Adapting the TUG_TQI to your specific context and defining meaningful quality classifications are crucial steps. Here's a breakdown addressing your questions, combining methodological considerations with practical advice:
1. Adapting TUG_TQI to Local Conditions:
  • Fewer Parameters: The TUG_TQI, as described in [1], uses multiple parameters. Since you have limitations (specifically with longitudinal level/versine), you must modify the formula. The core idea is to maintain the spirit of the TQI – a single, aggregated measure of track geometry quality – but adapted to your data. Here's a step-by-step approach: Parameter Selection: Identify the parameters you reliably have: gauge, cant, and twist. These will form the basis of your adapted TQI. Normalization: The original TUG_TQI normalizes each parameter based on its standard deviation (SD) within a defined track segment (usually 200m). You must still normalize. Calculate the SD for each of your available parameters (gauge, cant, twist) within your chosen segment length. The segment length should be chosen based on operational considerations and data availability (shorter segments might be needed if your versine data is very sparse). Aggregation: The original TQI uses a weighted sum of the normalized parameters. You'll need to decide on weights. Several options: Equal Weights: Simplest approach – assign equal weight to each of your three parameters (1/3 each). This assumes they contribute equally to track quality, which may not be true. Expert-Based Weights: Consult with railway engineers and track maintenance experts to assign weights based on their judgment of the relative importance of gauge, cant, and twist in your specific context (tight curves, low speeds). Document the rationale for the weights. Data-Driven Weights: If you have historical data linking track geometry defects to maintenance interventions or operational issues (e.g., speed restrictions), you could use statistical methods (e.g., regression analysis) to estimate the relative importance of each parameter and derive data-driven weights. This is the most rigorous approach but requires sufficient historical data. Modified Formula: Your adapted TQI (let's call it TQI<sub>Jakarta</sub>) could look like this (using equal weights as an example):TQI<sub>Jakarta</sub> = (1/3) * (|Gauge - Gauge<sub>mean</sub>| / SD<sub>Gauge</sub>) + (1/3) * (|Cant - Cant<sub>mean</sub>| / SD<sub>Cant</sub>) + (1/3) * (|Twist - Twist<sub>mean</sub>| / SD<sub>Twist</sub>)Where: Gauge, Cant, Twist are the measured values. Gauge<sub>mean</sub>, Cant<sub>mean</sub>, Twist<sub>mean</sub> are the mean values within the segment. SD<sub>Gauge</sub>, SD<sub>Cant</sub>, SD<sub>Twist</sub> are the standard deviations within the segment. The absolute value (| |) is important. Discontinous Versine: Imputation (Not Recommended): You could try to impute the missing versine data (e.g., using interpolation), but this introduces uncertainty and could bias your TQI. It is generally not recommended unless you have a very strong justification and a reliable imputation method. * Omission (Preferred): Given the challenges, it's best to omit the versine from the TQI calculation in your initial implementation. Focus on getting a robust TQI based on the reliably measured parameters. * Future Consideration: If, in the future, you improve your versine data collection, you can incorporate it back into the TQI, re-evaluating the weights and normalization.
  • Tight Curves and Low Speeds: These factors should influence your choice of weights (expert-based or data-driven) and, importantly, your thresholds for quality classifications (discussed below). Tight curves and low speeds might mean that smaller deviations in certain parameters are more critical than they would be on a high-speed, straight track.
2. Establishing Track Quality Classifications:
  • Statistical Methods: This is a good starting point. Quartiles/Percentiles: Calculate the 25th, 50th, and 75th percentiles (or other relevant percentiles) of the TQI<sub>Jakarta</sub> distribution across your entire network. You could define: "Good": Below the 25th percentile. "Fair": Between the 25th and 75th percentiles. "Poor": Above the 75th percentile. "Very Poor": Above 90th or 95th Percentile. Adjust these percentiles based on your engineering judgment and operational needs. Standard Deviations: Calculate the mean and standard deviation of the TQI<sub>Jakarta</sub> distribution. You could define: "Good": Within one standard deviation of the mean. "Fair": Between one and two standard deviations from the mean. "Poor": More than two standard deviations from the mean. Clustering: Use clustering algorithm to determine the classifications.
  • Historical Correlation: This is highly recommended if you have the data. Maintenance Records: Link your calculated TQI<sub>Jakarta</sub> values to historical maintenance records (e.g., track repairs, tamping, grinding). Identify TQI ranges that consistently correspond to different levels of maintenance intervention. This provides a practical basis for your classifications. Operational Data: If you have data on speed restrictions, derailment incidents, or passenger comfort complaints, correlate these with your TQI<sub>Jakarta</sub> values. This can help you establish thresholds that are directly related to operational performance and safety.
  • Hybrid Approach (Best Practice): Combining statistical methods with historical correlation is the most robust approach. Start with Statistics: Use quartiles/percentiles or standard deviations to establish initial classifications. Refine with Historical Data: Use your maintenance and operational data to validate and refine these initial classifications. For example, if you find that tracks classified as "Good" based on statistics frequently require maintenance, you might need to adjust the threshold for "Good." Expert Judgement: Involve railway engineers.
  • EN Standards (EN 13848-5): While EN standards provide valuable guidance, they may not be directly applicable to your specific context (tight curves, low speeds, different track construction). However, you can use them as a reference point. Compare your statistically derived thresholds and historically correlated thresholds to the limits specified in EN 13848-5 for similar track parameters. This can help you assess whether your thresholds are reasonable. Don't blindly apply EN standards; adapt them based on your local data and expert judgment.
  • Case studies: Look for case studies of TQI on Light Rail Transit.
Some Considerations and Recommendations:
  • Documentation: Carefully document your methodology: how you adapted the TQI formula, your choice of weights, your normalization procedure, and the rationale for your quality classifications. This is crucial for transparency and reproducibility.
  • Regular Review: Your TQI<sub>Jakarta</sub> and its classifications should be reviewed and updated periodically. As you collect more data, your understanding of the relationship between track geometry and performance will improve.
  • Iterative Approach: Start with a simplified TQI based on the available data, establish initial classifications, and then iteratively refine your approach as you gather more data and gain experience.
  • Software Tools: Use appropriate software (e.g., Python with libraries like pandas, NumPy, scikit-learn) to automate the TQI calculation, data analysis, and visualization.
  • Communication: Communicate results to stakeholder.
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Olivier Serrat
Olivier Serrat
  • asked a question related to Jakarta
What are the environmental and socio-economic implications of relocating Indonesia's capital city, Jakarta, to Nusantara in eastern Borneo?
Question
1 answer
  • 1 Mar 2024
The planned relocation of the seat of Indonesia’s government was announced by President Joko Widodo in 2019 and Indonesia's parliament passed a law enabling that in 2022. Home to more than 11 million people, Jakarta sits on swampy land: it has become crowded, polluted, and is sinking at an alarming rate owing to the over-extraction of groundwater. The question is underpinned by subsidiary sub-questions in the following areas:
  • How will the infrastructure of Nusantara be developed to accommodate 1.5 million civil servants from Jakarta?
  • How will the relocation of Indonesia's capital city to Nusantara be managed to ensure minimal disruption to governmental operations?
  • What strategies are being implemented to ensure that Nusantara will be a sustainable and smart city?
  • What are the implications of the relocation of Indonesia's capital city for indigenous communities in Nusantara?
  • What will happen to the population of Jakarta after Indonesia's capital city has relocated to Nusantara?
  • How will the relocation of Indonesia's capital city to Nusantara affect the socio-economic dynamics of Jakarta and the rest of Indonesia?
The sub-questions address a different aspect of Indonesian capital's planned relocation to Nusantara, providing a holistic view of potential impacts and challenges.
Responses to the question and any of the sub-questions are welcome. Suggestions for further reading, especially technical reports and lessons from comparable relocations in other countries, would be appreciated.
Relevant answer
  • 13 May 2024
Answer
may be of interest. That article casts environmental and socio-economic perspectives on the relocation of Indonesia's capital city from Java to eastern Borneo, the first instance of large-scale, anticipatory, and managed environmental migration in the Anthropocene.
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Mehdi Zare
Mehdi Zare
  • asked a question related to Jakarta
How the real earthquake risk assessment in megacities, with different day/night population is possible?
Question
2 answers
  • 19 Mar 2021
According to the latest global seismic risk map (developped in GEM project, 2018) there are currently 17 megacities around the world with a population of more than 10 million that are placed at the highest risk level, including Tokyo, Jakarta, Delhi, Beijing, Manila, Mexico City, Osaka, Los Angeles, Dhaka, Chengdu, Karachi, Tehran, Istanbul, Lahore, Nagoya, Bogota, and Lima. One of the best efforts to address the impact of earthquakes on a region, especially in densely populated urban areas, is to conduct earthquake risk assessments. The megacities has normally a changing day/nith population. The population increases even up to 50% during working day time. This means that there are specially the periferal and suburban marginal towns around these megapoles. Therefore these towns are mostly the resting locations for the worker in the megapoles. The assessment of earthquake risk is mostly complicated specially in the megapoles in the underdevelopping countries. What are the major peririties for such assessments?
Relevant answer
  • 25 Apr 2021
Answer
Good afternoon Professor Zare,
You are quite right that it is a very important question, as well as an exceptionally difficult one to respond to. Even more so, one would expect that a country specific approach would be required to come with some relevant answers.
I would suggest that one possible approach would be to consider first the earthquake risk associated with the existing buildings stock in this megacities with a view to identify where the major risk lies. The second tier would be the risk assesment associated with the public spaces and associated infrastructure. Both of these would have to be considered in the light of the time and day specific analysis.
I recall that there is a book from the 1980s which listed the daily life pattern in different countries. If exist, an updated version of the book or a sample survey in the optimal periods might provide a good indication of the distribution of people within certain period of time during each day of the week.
Combining the building, infrastructure and environment risk analysis with the daily living pattern should provide snapshots of risk for different time of the day in the week. This should allow to identify how the earthquake risk shifts within a day. Naturally this should assit in identifiying locations and periods where the highest risk exist which could be used to develop relevant mitigation policies.
With Best Wishes
Vladimir
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Adhitya Trenggono
Adhitya Trenggono
  • asked a question related to Jakarta
November 2020 Untirta Online Seminar Series# on Metallurgy and Materials Topics or Research
Question
2 answers
  • 20 Oct 2020
SERIES#9 (Monday, 2nd of November 2020 at 1-3 PM Jakarta)
#Speakers#
Rifan Hardian, MIL, MSc, MSc, PhD King Abdullah University of Science and Technology (KAUST), Physical Science and Engineering Department-Saudi Arabia/ Metal-Organic-Frameworks (MOFs), Polymer Membrane and Machine Learning
Hasfi Fajrian Nurly,S.T., M.Eng*University of Science and Technology of China/*4D printed hydrogels
Zoom registration: https://zoom.us/meeting/register/tJYkfuCpqDkrGNdi1OsSupZEbt9ApSgVPuDC
SERIES#10 (Monday, 9th of November 2020 at 1-3 PM Jakarta)
#Speakers#
Yus Rama Denny,PhD Department of Physic Education, Sultan Ageng Tirtayasa University*Transparent Conducting Oxide : History and Challenge for advance material applications*
Fatwa Firdaus Abdi,PhD Institute Solar Fuels Helmholtz-Zentrum Berlin-Germany* Semiconductor and photoelectrochemistry for water splitting and solar fuels*
Zoom registration: https://zoom.us/meeting/register/tJwtcuuvrj4rHNKwtH1zh17_P9yt39T7Bpge
SERIES#11 (Wednesday, 18th of November 2020 at 8:30-11:30 PM Jakarta)
#Speakers#
Dr. Chander Prakash Department of Mechanical Engineering, Lovely Professional University, Punjab-India Surface functionalization of biomaterials
*Prof. Dr. A Ali Alhamidi, S.T.,M.T*Department of Metallurgy Engineering, Sultan Ageng Tirtayasa University *Severe Plastic Deformation *
Nandang Mufti, PhD Department of Physics, Universitas Negeri Malang Advanced materials for renewable energy
Zoom registration: https://zoom.us/meeting/register/tJUtcemorzIiEtUpw2c3gQ-hPWRQsK7BFFJW
FML WEBINAR SERIES#3 (Wednesday, 18th of November 2020 at 2-5 PM Jakarta)
#Speakers#
Dr. Enzo Liotti Senior Fellow of Departmental Lecturer in Processing of Advanced Materials,Department of Materials/Oxford University-UK Synchrotron X-Ray Techniques for Understanding Metal Alloys Structures and Its Evolution
Michal Rejdak, PhD * Laboratory of Cokemaking Technologies, Institute for Chemical Processing of Coal, Poland *Cokemaking Technologies
Zoom registration: https://zoom.us/meeting/register/tJYld-2rrzorEt1i0sinVHX9vBn2fcjwJtme
SERIES#12 (Monday, 23th of November 2020 at 2-5 PM Jakarta)
#Speakers#
Prof. Paula Maria Vilarinho Department of Materials and Ceramic Engineering (DEMaC), University of Aveiro-Portugal *Electrical Polarization Phenomena and Advanced Nano and Microelectronics Devices *
Bobby Aditya Darmawan,S.T.,M.Eng Department of Mechanical Engineering , Chonnam National University, Korea and Korea Institute of Medical Microrobotics The future prospects of microrobots in biomedical applications
Zoom registration: https://zoom.us/meeting/register/tJ0lcuCupjkqHNXDAK2jR7CueKHetay0fYAP
SERIES#13 (Monday, 30th of November 2020 at 2-5 PM Jakarta)
#Speakers#
Dr. Ir. Hermawan Judawisastra, M.Eng Department of Material Engineering, Bandung Institute of Technology-Indonesia *Polymer Composites *
Sampo Tuukkanen, PhD Tampere University of Technology-Finland Nanocellulose piezo-sensors
Zoom registration: https://zoom.us/meeting/register/tJYofuyhpz4sG9ysTw4SNbGDKPe1HcJmC8js
Relevant answer
  • 29 Oct 2020
Answer
@abdella. No, it's free. You will receive e-certificate and the slides.
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Gian Carlo Palacio Reyes
Gian Carlo Palacio Reyes
  • asked a question related to Jakarta
What can be used as a disinfectant spray for use in disinfecting booths?
Question
3 answers
  • 27 Mar 2020
Hello everyone.
I've been asked to formulate a disinfecting solution that can be used in walk through booths for people entering our facility. I've searched the internet but sources are pretty vague:
1. In China they refer to it as a hospital grade disinfectant
2. In Jakarta they refer to it as similar to hand sanitizers
3. In Vietnam they say its an anolyte solution using sodium chloride.
4. Others suggest it is chlorine based.
Any insight to this would be greatly appreciated!
Thank you.
Relevant answer
  • 15 May 2020
Answer
I agree with WHO in stating that spraying disinfectants on clothes or body does not kill the virus already inside the body. However, I believe that walk-in booths are contributing to eliminating the transmission of the virus from one person to the other, the same way as putting a mask is avoiding transmission from the person already infected to others.
Think of it, if the virus is already on your body or clothes, you are likely to pass it on to other people who might touch you accidentally. So, any form of eliminating such kind of transfers should be welcomed.
Unfortunately different people will have different allergies to different chemicals, but as long as "Warnings" are displayed on these walk-in booths, it is acceptable. In this instance, I suggest that full "Formulation Assessment" should be done on any formulation that is going to be used for this purposes. This is to ensure that experts evaluate the toxicity of such mixtures against what is scientifically acceptable/tolerated.
The formulation assessment will also determine the compatibility of such mixtures with other chemicals or materials. For example, the mixture might react with some components of the walk-in-booth, or some incompatibles on people walking through the booth.
My suggestion is the following:
1. Develop your formulation (use literature to check what has already proven to work);
2. Have your formulation tested for:
(a) bactericidal efficacy
(b) chemical testing, e.g. corrosivity; chemical damage to cotton
(c) formulation assessment for toxicity
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Jake Nelson
Jake Nelson
  • asked a question related to Jakarta
Does anyone know where (or if its even possible) to get Jakarta census data?
Question
1 answer
  • 10 Jan 2019
Working on a new project and looking for census data for Jakarta at the district or sub-district level. Particularly interested in the break-down of race/ethnicity or religious affiliation. Thanks!!
Relevant answer
  • 11 Jan 2019
Answer
A place to start: http://www.indonesiainquiry.com/research-resources/census-data-and-statistics/
Additional data at http://worldpopulationreview.com/world-cities/jakarta-population/
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Sarah Amanda Palilingan
Sarah Amanda Palilingan
  • asked a question related to Jakarta
Do you have the adapted and translated version of ATSPPHS by FIscher and Farina?
Question
2 answers
  • 4 Sept 2018
Dear Princen Tsai,
I'm currently researching on masculinity and its correlation with help-seeking behavior in Jakarta, Indonesia. Do you by any chance adapted and translated ATSPPHS into bahasa Indonesia?
Thank you!
Best regards,
Sarah Amanda
Relevant answer
  • 10 Sept 2018
Answer
Thank you for your respond Princen Princen Princen Princen Have you back translate it too? If so, would you be so kind to e-mail it to me? I'll make sure to cite your research appropriately and accordingly.
My e-mail is amandakonstantia@gmail.com
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Prasetyo Putra Bangsa
Prasetyo Putra Bangsa
  • asked a question related to Jakarta
Anyone can you please tell me what this species? and are those species affect in coral health?
Question
2 answers
  • 18 Oct 2017
i found this in pramuka island in 4m depth, north jakarta.
Relevant answer
  • 19 Oct 2017
Answer
This is Lampert's sea cucumber Synaptula lamperti. It lives at the surface of a sponge: Xestospongia.
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Gerrit Peters
Gerrit Peters
  • asked a question related to Jakarta
Where can I find a current open source vector map of Jakarta that includes the drainage network?
Question
13 answers
  • 31 Mar 2015
I would like to use it as a base map for my own mapping purposes. Eventually, these maps would get published, therefore I need the base map to be open source. Thanks a lot! 
Relevant answer
  • 7 Apr 2015
Answer
Hi Gerrit,
did you had a look at OSM already? As far as I know, the Humanitatrian OpenStreetMap Project (http://hot.openstreetmap.org), helped to improve the Indonesian and in particular the Jakarta maps of OSM.
Here is a Blog post about flood response in Jakarta facilitating OSM data:
http://hot.openstreetmap.org/updates/2013-01-18_openstreetmap_usage_in_jakarta_flood_response
I can help with getting the OSM data into a GIS..
Cheers,
Christian
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Herdiyan Maulana
Herdiyan Maulana
  • asked a question related to Jakarta
Could I get total Subjective Well-being score by sum all the SWLS, Flourishing Scale, and SPANE scores?
Question
6 answers
  • 21 Jul 2014
I am doing my preliminary research involving 230 respondent with low-economic status in Jakarta, Indonesia
http://internal.psychology.illinois.edu/~ediener/scales.html
Relevant answer
  • 24 Jul 2014
Answer
I agree with the colleagues, you shouldn't sum them up. If you plan on performing structural equation modeling, you can have factors for each dimension load on a second-order factor that would represent participants' SWB.
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