JURNAL ILMIAH PENELITIAN MarKa, ISSN: 2580-8745
A Methodology of Participative Socio-spatial Data Collecting for Urban Poor in Jakarta 1
Ariel Shepherd , Yantri Dewi
2
1
Spatial Planner Researcher and Community Liason of PetaJakarta.org , Independent Researcher for Spatial Planning at Urban Poor 2 Consortium (UPC)
Abstrak Program-program kemiskinan di Indonesia seringkali tidak efektif dalam pelaksanaannya dikarenakan terbentur dengan akurasi data statistik dan demografi dasar. Tidak ada metode pembaharuan data seiring dengan waktu yang bisa mewakili kondisi sosio-spasial sebenarnya di lapangan. Metode pengumpulan dan pengelolaan data dasar secara partisipatif diperlukan dimana warga akar rumput sebagai penerima manfaat program-program yang ditargetkan bisa bertanggung jawab dalam -mengumpulkan/ -membuat/ -melihat / memperbaharui data mereka sendiri. Selain meningkatkan efektivitas program, sifat partisipatif dalam pengumpulan data ditujukan untuk meningkatkan kesadaran warga akan kondisi mereka sendiri. Teknik pengambilan data dan pemetaan yang kami formulakan adalah kombinasi antara GPS (Global Positioning System) yang diikuti oleh teknik visualisasi arsitektural/ lanskap. Metodologi ini digunakan di tiga kampung miskin perkotaan Jakarta sebagai studi kasus dan makalah ini akan memberikan analisis deskriptif kualitatif tentang bagaimana sebuah sistem pengumpulan data open source dan partisipatif pada skala lokal dapat menjadi alat keterlibatan dalam dialog kritis seperti; kesiapsiagaan dalam penanganan bencana, perencanaan lingkungan spasial, dan program-program perumahan untuk skala kota. Kata Kunci : kemiskinan kota, metode partisipatif, data terbuka, ketahanan, pemetaan spasial
Abstract Programs specifically targeted to alleviate poverty in Jakarta are not effective due to the difficulty in achieving accurate baseline statistics and demographic data. No database or data collection method exists yet which is easily updatable, and properly represents the existing socio-spatial conditions. A participatory method of baseline data collection and management is needed as a bottom-up channel for targeted beneficiaries to be responsible in -collecting/ -inputting/ -viewing/ -updating their own data. In addition to increasing the program's effectiveness, participatory in data collection is designated for awareness in the communities. The rapid mapping technique is a combination of GPS (Global Positioning System), followed by an automated representation of settlement architecture / landscape visualization technique as an appending value. The above methodology will be used in three urban poor kampungs in Jakarta as study cases. This paper will provide qualitative descriptive analysis of how the participatory socio-spatial open-source data at the local scale can be a tool of engagement in critical dialogues such as; Disaster preparedness and response, spatial environmental planning, and housing programs at the city scale. Keywords : urban poor, participatory methods, open data, resiliency, spatial mapping
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Ariel Shepherd dan Yantri Dewi
Introduction The biggest threats to people’s safety and security in cities today is insecurity of tenure and natural and man-made disasters; with the most insecure of those people living in slum areas (Source: Global Report on Human Settlements, UN Habitat1). For most of the cases in Indonesia there are always gaps, gaps between the good intentions of programs and projects aimed to reduce urban poor vulnerability, and their real impact, rarely achieving their best result because a lack of recognition of the real needs of the communities (so called - kampung). Sometimes the programs/ projects (local and international) can give negative impact on the beneficiaries afterward. In achieving the basic core value of urban poor alleviation programs, putting people in the center of their own development is as important as doing policy development.
Socio-spatial Data Collecting 1.
Methodology
Numerous data collection methods have been made for urban poverty alleviation programs at the national and international scale. In the eyes of the decision makers data collecting remains a tool to make a better decisions for the future. Ideally data does not sit in isolation, but provides is powerful and comprehensive in its multi-dimensionality, to tackles the causes of poverty itself. In our methodology of data collection, back and forth between scales is necessary. Scaling is the first point that is profoundly need to be understood by the facilitators of mapping team and the kampung people itself. The combination of individual data and household data as we called socio-data is as important as kampung scale bolstering with radius of five kilometers public facilities provided from the initiate location to be mapped to produce a complete profile that we called spatial-data.
Figure 1. Rizka presenting the results of mapping. Kampung Budi Dharma (Shepherd and Dewi, 2015)
It is well recognised data collecting increases the visibility of informal settlements, and brings the community into the decision-making processes. For that, we are developing a combination of relevant data collecting (participative and kampung-led based) and spatially mapping. The data collecting and spatially mapping uses of the most common and accessible technology in phases, mixing quantitative and qualitative data producing an accurate representation of baseline conditions of the kampung. Producing not only material for suggested improvements of the kampung, but a way of increasing awareness of the necessity of improvement of the kampung itself. This methodology we called, socio-spatial data. To provide a framework can visualize the comprehensive socio-spatial data, we led community meetings in a form of Forum Discussion Group (FGD) at the beginning, before conducting the surveys needed. FGD is a crucial step, important for the community members to reach the understanding and level of awareness, so that the next step would be run easier. The next simple step is using the most open softwares (googleMaps, Open Street Maps (OSM), googleForms, Pictochart, and cartoDB) for mapping that is available on standard common devices such as smartphones, tablets. It is highly encouraged that the software is user friendly. Apart from the FGD and use of commonly accessible Volume 1 Nomor 1 Agustus 2017 | 9
A Methodology of Participative Socio-spatial Data Collecting for Urban Poor in Jakarta
technologies, we are conducting a community-led collecting data that is immediately visible, and can be verified live in the field. This minimizes as much as possible the need for back-end manipulation, management, and visualization. 2.
Time-framing
Our methodology ideally needs two full days (nonconsecutive) in the field,. Here is the designed timeframe that could be used as a standard itinerary, but does not need to be followed strictly. Day-1 Activities:
1. FGD
Introduction phase to the kampung; why we do data collecting and why accurate socio-spatial data is important. This step is performed with a forum group discussion at the kampung scale 2. Data collecting and mapping
FGD can be used as a chance to divide the people into two thematic working groups to carry out data collection, ideally the teams can work in-parallel. Working Group 1 : spatial-data group. Tools are simple paper and pens to draw and write; (1) history, (2) kampung map and (3) aerial map of kampung with public amenities and/or facilities within five kilometres circumference of. Working Group 2 : socio-data group. Tool is a prepared online gForm survey, accessible by devices such as smartphones, tablets, etc. Printed versions of the form to be filled manually are printed as a back up.
categorized as poor (sources by Central Bureau of Statistics (BPS)), already held a relation with UPC, and suffered from insecure tenure. We selected the kampungs of Kampung Budi Dharma, Kampung Kebon Bayam, and Kampung Asahi. All the three kampungs were were scheduled to do data collecting and mapping in two days, as the timeframe has planned. 1.
Methodology is Robust
Methodology is robust because it was built over time with trial and error, with feedback mechanisms from the community and the team. Such that the order of steps, use and integration of different software has been crafted in a way that it is easy to replicate, while producing the best results. Sharper accuracy, transparent in process, multi-dimensional and able to be verified are ways of getting a sustainable problem identification in a holistic way. So by the chance of implementing this method to the three kampungs, we were to evaluate which scale, which part, which steps that we would not be able to skip or which part that we could skip for best socio-spatial data, in a relatively short-time period.
In between Day 1 and Day 2, facilitators (in this case Urban Poor Consortium (UPC)) ; (1) leaves the community to complete the gForms for all the families, (2) preparation for FGD-2. Day-2 Activities:
After finishing the forms and maps, the community presents their mapping, and verifies the socio-spatial data that has been collected. In the format of FGD, they could make open discussion of future planning of proposal for programs/ projects for their upgrading kampung needs. Figure 2. Map of locations of three kampungs of pilot projects (GoogleMap redrawn, 2015)
Analysis As pilot projects we implemented and tested this methodology in three kampungs in North Jakarta. The selection of the 3 Kampungs was based on the pre-requisites conditions; kampungs were 10 | Volume 1 Nomor 1 Agustus 2017
2.
Forum Group discussions (FGD) and community engagement
One critical part of the methodology is the FGD's at the scale of the community, we found this can not
Ariel Shepherd dan Yantri Dewi
be removed. Community data, and preparedness, including perceived threats and perceived solutions, and possible ways forward, can not be separated from 'baseline data' of persons. By combining and representing household data with infographic helps facilitate the FGD an also triggering descriptive analysis of the outcomes from the data collecting. Soon this awareness raising, for example 75% of people say their quality of water is unsatisfactory, and the source of most water is from well, the facilitator could fish for a communal answer through questioning back, if most of kampung people are happy with the conditions or not, and what they feel are the possible further actions which could be taken. Possible options are raised from community scale FGD by working together or so. This approach has never been used before, and proven to empower people to think together about what could be done to change their situation in kampung scale. If the community can calculate, and say only four drinking towers would be enough to supply us with safe drinking water 'if only we had the money' their perception of needs can be linked to the availability programs and/or projects targeted to increase water quality. Facilitators, in this case from UPC (Urban Poor Consortium), could assess what communities were most in need, or which people within the community. Some needs cannot be gathered from household surveys alone, or remotely, community engagement in kampung scale is needed.
Figure 3. Sample of final poster visualization for Kampung Budi Dharma. Mapping result by QGIS. Basemap: Google Map (Shepherd and Dewi, 2015)
In Kampung Kebon Bayam, with a population more than five-hundreds head of families, it was necessary
to divide the work into groups for effectivity and efficiency. And we needed to hold an initial FGD twice, to get the assurance of people involvement in the data collecting. After the second FGD, we were reaching a point where we would not be able to continue further and stopped the process half-way because the kampung voice divided into several opinions about the necessity of data collection. With a collective voice, a community that presents itself with a united front has much greater political force than a series of detached voices2. Lesson learnt is, the kampung itself needs to sure about the meaning, urgency and relevance of socio-spatial data collecting themselves as a group. 3.
Common Technologies
Our method strives to maximize participation by crowd- sourcing while minimizing the behind the scenes work or computation, relying on easy to access user-friendly software on basic smartphones. Such that as much data as possible can be input by the kampung people themselves. This is important for them to feel as sense of ownership of their own data, and not feel the data collection is for the government or other parties. As well as for validity purposes. Another critical need for the use of common technology is for scalability, if the software is open- access and easy to use, the community can continue to manage their own data in the future without facilitators. For example, in Kampung Asahi/Volvo, we were conducting 4-5 young people that were friendly with smartphones and tablets. The process was happening smoothly and almost without any difficulties. In the same day of the first FGD, they started data collecting using gForms and mapping with GPS tracker. The lesson learnt is not only to involve youngsters, but also the scale of the Kampung Asahi/ Volvo with forty two head families it was manageable by 4-5 data collectors, with two people kampung scale mapping. For the needs of visualization, the map made by the community together with the collected socio-data by handy devices, is merged into one platform using QGIS. This step is not necessary, but gives a further level of socio-spatial representation, and better for making a presentation to the stakeholders/ decision makers in the future.
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A Methodology of Participative Socio-spatial Data Collecting for Urban Poor in Jakarta
4.
Forecasting the improvements
needs
and
future
Issues which need addressing before scaling out the method is providing good facilitators. The philosophy “training the trainers” are necessary to be prepared before prototyping the method for it is not always easy to access common technology. While the technology can theoretically be provided by the community themselves, the program would have to be support by increasing the number of trained and reliable facilitators. At the same time, a strategy for dealing with large communities, our method worked best with a community of 30-40 head families, more than that it was difficult to handle the holistic. community engagement. Lastly, a question of data protection and safety is raised. When the idealism of open data is important so the kampung people are always be able to -see/ - edit/ -update their own data, should it be under a supervision of an authorized facilitator? What if someone wipes clear or decides to fill the database with erroneous data? How to ensure the safety of the data? Is the community as the owner need to do further step in managing it? For this question there is in-need another step of kampungled data protection.
Conclusion The methodology of this innovative participatory socio- spatial data collection are hoped would increase the ability and capacity of the kampung to make some (in)formal decisions about their own future, either relocation with collaboration with government or on-site upgrading in some basic infrastructure aspects. People-powered in the kampung scale is easily scalable when it is facilitated by number of trained-facilitator more than using high-tech devices. This particular method also has potential to integrate with stakeholders related to the urban poor alleviation, and for sure with international organization. Hence, the security of data appearance after using open -datas/ - software still in need for further investigation.
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References Tudehope (2013). " Mapping the urban poor: 12 reasons why you should conduct enumerations of your settlements". Global Urbanist. [Accessed 27 September 2015]. http://globalurbanist.com/2013/03/05/ mappingthe-urban-poor UN-Habitat (2003). "The Challenge of The Slums: Global Reports of Human Settlements." UN-Habitat.
