Case Study In Jakarta Research Articles

Comprehensive Research Study of Challenges and Opportunities in Electric Vehicle Adoption: Case Study in Jakarta

This article delves into the potential of electric vehicle (EV) adoption in Central Jakarta, a densely populated area grappling with significant urban and transportation challenges. Trams are an environmentally friendly mode of transport that is environmentally friendly, efficient, comfortable, accessibility, and enhances the aesthetic value of the city. Trams do not produce exhaust emissions, so they can help reduce air pollution in big cities. This is important for improving air quality and public health. The research variables include cost implications, environmental impact, and other relevant aspects of transitioning from fuel-based cars and motorcycles to electric vehicles. The research extensively explores various reputable sources such as papers, journals, and research studies relevant to the chosen research variables, enhancing the credibility of the findings. The study reveals that while the adoption of EVs presents several opportunities, such as reducing traffic congestion and environmental pollution, it also poses significant challenges. These include high costs of EVs, lack of charging infrastructure, and consumers' unfamiliarity with the technology. The research suggests that addressing these challenges requires an integrated and comprehensive solution, including policy measures such as increasing public charging infrastructure, transforming tax schemes, and providing incentives for EV users. This research contributes to the ongoing discourse on sustainable urban transportation, providing valuable insights for policymakers, academia, and the local community in Jakarta and beyond.

Assessment of the sustainability of online food delivery from the perspective of CO2 emissions and transport intensity: A case study in Jakarta

This study examines the impact of online food delivery on CO2 emissions and transport intensity in Jakarta, Indonesia, by integrating data from both delivery drivers and customers. A total of 235 delivery instances were analyzed to discern typical distances and patterns inherent in these services. Additionally, insights into the demand side were obtained through customer surveys, yielding 203 valid responses, that included waiting times, costs, and behaviors related to alternative meal acquisition methods. CO2 emissions generated by delivery processes were estimated, utilizing travel distances recorded by drivers. The traffic impact was assessed by calculating the road occupancy of motorcycles used for deliveries. Furthermore, the assessment of CO2 emissions and transport intensity considered hypothetical emission scenarios without such delivery services based on customer indications of their alternative means of meal acquisition. This analysis revealed that frequent short journeys by delivery motorcycles significantly contribute to urban traffic congestion and CO2 emissions, highlighting the environmental and traffic pressures resulting from the rise of food delivery services. Results from the customer survey revealed a profound dependence on these services, indicating that their availability prompts a significant number of additional trips, thereby exacerbating these impacts. The findings suggest recommendations for mitigating these adverse effects, including promoting the use of electric motorcycles for deliveries and managing demand by reassessing delivery fees to reflect the actual environmental costs.

Using smart card data to develop origin-destination matrix-based business analytics for bus rapid transit systems: case study of Jakarta, Indonesia

Bus rapid transit systems (BRT) have been an indispensable public transportation pillar, especially in densely populated regions. Accurate insight into the BRT network's utilization is vital in BRT resource allocation planning contexts. This research focuses on how operators can utilize passengers’ smart card data to develop origin-destination (OD) matrix-based business analytics. This research proposes a hybrid approach combining trip chaining, direct pairing, mode estimation methods, and visual analytics development. The novel approach is robust in handling incomplete smart card data transactions to generate origin-destination matrices and corresponding visual analytics as decision support systems for the BRT operators. As a case study, we applied and validated the proposed analytics to more than 20.6 million smart card transactions in one of the largest global BRT systems in Jakarta, Indonesia.

Waste accumulation in Jakarta’s slums: Neoliberal flows of waste distribution

Urban slums in the Global South have a formidable challenge of mismanaged waste. Behind this challenge lies urban politics, creating disproportionate exposure to waste in marginalized settlements. This paper articulates an urban political ecology of uneven waste accumulation in slums with a case study of Jakarta, Indonesia. I apply a mixed-methods approach, by integrating a spatial regression model with a critical qualitative analysis, to draw the connection between the slums’ waste crisis and neoliberal waste infrastructure. Since the mid-2010s, Jakarta’s waste governance has shifted from a conventional collect-transport-dispose model to a circular economy model operating under a technocratic and neoliberal economy. Under the shifted governance, the informal sector has been strengthened through the integration of high-tech infrastructure to reduce waste and extract new profits from materials. However, the sector has been unevenly strengthened across the city, creating two flows of waste accumulation activities. First, the strengthening has been accelerated in low-income residential areas by introducing financial incentives for the informal sector to make up the shortfall created by public services. Consequently, the informal sector in slums—with its limited focus on recyclable materials—has led to the accumulation of mismanaged non-recyclable waste in unregulated dumpsites of slums. On the other hand, public services are relatively prevalent in capital-intensive areas to promote the economic growth. However, due to its compact land-uses in those areas, the services utilize the unregulated dumpsites in slums as semi-permanent landfills for storing the collected waste.

The Impact of Social Entrepreneurship on Reducing Economic Inequality, Community Self-reliance, and Business Innovation in Urban Areas: A Case Study in Jakarta, Indonesia

With an emphasis on Jakarta, Indonesia, this study examines the relationship between company innovation, community self-reliance, and economic gap reduction and social entrepreneurship success in metropolitan settings. Using a quantitative methodology, 170 participants in the sample shared details about their entrepreneurial endeavors. The measurement model was validated by confirmatory factor analysis, which also confirmed the validity and reliability of the chosen constructs. Significant positive correlations between closing the economic gap, fostering community self-reliance, corporate innovation, and the effectiveness of social entrepreneurship were found using structural equation modeling. The findings were shown to be robust, and the distinctiveness of the constructs was confirmed using discriminant validity analysis and bootstrapping approaches. The model's strong explanatory ability was demonstrated by the R-Square values. The practical implications of the study's findings for policymakers, entrepreneurs, and communities in Jakarta pertain to creating an environment that is favorable for social entrepreneurship.

Young Consumers Behavior in Consuming Honey During the Covid-19 Pandemi: Case Study in Jakarta

Honey is a natural liquid produced by honey bees from plant flower essences or other parts of plants that contain various nutrients and bioactive compounds that can increase the body’s immunity during the COVID-19 pandemic. This research was conducted with the aim of analyzing the behavior of Jakarta young consumers in consuming honey during the COVID- 19 pandemic. The method used in this study was a survey using a questionnaire. About 204 young consumers between 20-30 years old in Jakarta who had consumed honey were interviewed and filled out a questionnaire. The selection of respondents was determined using a probability sample with a disproportionately stratified random sampling technique. Honey consumer respondents agreed to consume honey because honey can increase body immunity and increase stamina during the COVID-19 pandemic. The relationship between knowledge and situational factors with the decision to consume honey was tested using the Rank Spearman correlation test. Knowledge level and situational factors have a significant relationship with the decision to consume honey. This study showed that the higher the level of knowledge and situations that support consumers, such as the COVID-19 pandemic situation, the higher the level of honey consumption.

The Implementation of Roots Program in Overcoming Bullying in Schools: A Case Study in Jakarta

The 2021 National Assessment showed that 24.4% of students potentially experience bullying in schools. The government decided on the Roots Anti-Bullying Program to prevent bullying in the school and to ensure a safe, comfortable, and enjoyful environment. Students are activated for this program as agents of change to enable better communication and interaction between peers. The Roots Program has been implemented since 2021 and will be implemented gradually in more than 15,000 schools by 2023. This study aims to determine the effectiveness of the Roots Program in solving the bullying issue at school, the factors that influence the implementation of the Roots Program, and the problems faced in implementing the program in Jakarta. This qualitative descriptive study used Van Meter Van Horn Policy Implementation Theory, focusing on size and policy objectives, resources, characteristics of agents of change, attitudes of implementors, communication between organizations and implementors’ activities, as well as the economic, social, and political environment. The data collection techniques used were observation, interviews, and literature reviews. The results of this study describe that Roots has been appropriately implemented and marked by the fulfillment of all indicators in each dimension of Van Meter Van Horn implementation theory. To improve the implementation of the Roots in the following year, the Roots can be carried out face-to-face; the number of agents of change is adjusted to the number of students in the school; socialization regarding guidelines for implementing government assistance, dissemination of anti-bullying content to agents of change, and adjustment of delivery times for the learning module.
 Keywords: policy implementation, education policy, bullying, roots program

Assessing Public Acceptance of Autonomous Vehicles for Smart and Sustainable Public Transportation in Urban Areas: A Case Study of Jakarta, Indonesia

This study examines the benefits and drawbacks of autonomous public transit vehicles among 210 Indonesians. Some 25% of respondents knew nothing about driverless vehicles, whereas 14% did. The average 5-point Likert scale response was 3.12 (SD = 1.05), indicating intermediate expertise. Some 42% of respondents used autonomous vehicle sources such as public transport, 47% had no experience, and 11% were doubtful. The survey items’ Cronbach’s alpha score is 0.873, indicating strong internal consistency and reliability. Most respondents supported the deployment of autonomous road vehicles for public transportation and said they would improve public transportation quality and accessibility. Technical issues and legal liabilities worried responders. The mean scores for the seven autonomous car benefits were similar, showing that respondents did not strongly prefer any benefit. After assessing the socioeconomic status and concerns, the study indicated that people who saw greater benefits were more tolerant of autonomous vehicles. Most respondents also wanted a clearer explanation of their legal responsibilities in case of an accident, thought human operators should play a major role in the future, and supported government trials of autonomous vehicles before their widespread usage. The study’s findings can help policymakers and stakeholders increase public acceptance of new transportation solutions such as autonomous vehicles, and improve future mobility safety and sustainability.

Developing DPSIR Framework for Managing Climate Change in Urban Areas: A Case Study in Jakarta, Indonesia

From an environmentally conscious and ecological perspective, the sustainability of cities within the effects of climate change are closely related to the wise use of resources and modifications in the ecological status of the environment. In terms of the ecological environment, the sustainability of smart cities entails meeting present and future societal demands for the environment of the water, land, and air, among others. Environmental and the ecological concerns that arise from rapid climate change and monetary developments are shown in the inconsistency between ecological assets, environmental pollution, and the destruction of nature. In this study, the authors aim to develop a strategy to deal with climate change in urban areas using Remote Sensing and the Driver-Pressure-State-Impact-Response (DPSIR) Framework with a case study in Jakarta Smart City. The DPSIR framework, which will be developed and implemented in the city of Jakarta, is a smarter and more sustainable framework that is evaluated through a systematic evaluation of sustainability with quantitative research using the entropy weight method and Partial Least Square-Structural Equation Modeling (PLS-SEM). These methods evaluate 58 representative elements of environments at the urban level, including the shortcomings of earlier research such as data availability, spatial and temporal constraints, and several related ecological indicators, such as soil pH, wind speed, air quality index as well as land changes in the spatial (spatiotemporal) time series. The results of the study show that in the metropolitan city of Jakarta, the Drivers that are related to climate change are the rate of population growth and the rate of industrial growth which, although increases people’s income and GRDP in Jakarta; it also creates Pressures, namely an increase in the amount of water consumption and in the amount of wastewater. Based on these pressures, the environmental conditions (State) of Jakarta city have undergone several environmental changes, such as loss of water supply, changes in wind speed, changes in rainfall, and increasing concentrations of the Air Pollutant Standard Index. The Impact of these three elements resulted in the increase in household and industrial water consumption, an increase in annual electricity consumption, and deteriorating air quality. Hence, the Response to these four interrelated causal variables is that the Jakarta Provincial Government must increase annual funds for the construction of urban community facilities, increase the production capacity of clean water supply, build environment-friendly wastewater treatment facilities, increase the capacity of waste processing infrastructure and transportation fleets, and educate people to use water wisely to reduce the level of water use.

Time Series Temperature Forecasting by using ConvLSTM Approach, Case Study in Jakarta

Climate change has occurred in several countries, especially in tropical countries such as Indonesia. It causes extreme temperature changes in several Indonesian areas, especially Jakarta, one of the world's most populated cities. The population of Jakarta causes the activities carried out by residents to be disturbed by extreme temperature changes. In addition, drastic temperature changes also affect the energy consumption used by residents. Therefore, it is necessary to predict temperature to determine future temperature conditions so that residents can plan their activities. Temperature forecast can be done in several ways, one of which uses a machine learning approach. This research uses a deep learning model called the Convolutional Long Short-Term Memory (ConvLSTM). Moreover, we also compare the model with Multi-Layer Perceptron (MLP), and Long Short-Term Memory (LSTM). We use temperature data taken from the ERA-5 period years 2018 to 2020 located in Kemayoran, Jakarta, Indonesia. This research aims to investigate the accuracy of short-term temperature forecasting by using these three models. The model is built to predict short-term temperatures for 1, 3, and 7 days ahead. The performance of the three methods is measured by calculating the Root Mean Square Error (RMSE), Mean Square Error (MAE), and Coefficient Correlation (CC). The result shows that the LSTM performs better than the other methods to forecast 1, 3, and 7 days, i.e., with the lowest RMSE, MAE, and higher CC. 

The challenges of implementing green factors in urban greening schemes in Indonesia

Recently, new planning tools have emerged to support urban landscape planners in achieving sustainability through optimizing the urban greening scheme. Some cities have approved the green factor tool to increase the quantity and quality of urban green spaces. This greening scheme is considered suitable for a relatively dense city where challenging to provide adequate urban green areas. This short communication challenges the usefulness of the green factor tool and how it relates to the existing urban green space planning procedures through a qualitative case study in Jakarta, Indonesia. The result shows that while the green factor tool performs well, improvements could be made primarily in convincing stakeholders regarding the new paradigm in calculating green areas in relatively dense urban areas. Furthermore, trials in actual cases need to be carried out to examine the formula’s effectiveness. Regarding the usefulness of this tool, we conclude that while increasing the number of green areas, improving its quality is more necessary to build resilient infrastructures.

Optimizing Response Strategies of Healthcare System in a Large-scale Disaster

Urban infrastructures are invariably constituted by social and technical components whose capacity to withstand crisis is determined by the resilience of their sociotechnical structures. This study aims to apply the principles of sociotechnical resilience in modeling and simulating disaster response in urban areas. Drawing on a case study of Jakarta, Indonesia, our study focuses on the role of hospitals as part of healthcare infrastructure in response to a large-scale disaster. Each hospital is modeled as a coordinated location with a certain amount of resources, primarily in terms of medical staff. We perform sensitivity analysis through Monte Carlo simulations to observe the impacts of various response strategies, disaster severity, and communication duration on system resilience. The results show that centralized systems are generally more suitable for dealing with low disaster severity, while the decentralized strategy performs better during a disaster with worse impacts. Additionally, the time taken for communication and coordination can significantly affect the performance of centralized systems. By simulating various scenarios, parameters, and recovery protocols, the model we developed can help policymakers, city planners, and other stakeholders design proper response strategies suitable to their structural conditions and available resources during a large-scale disaster in urban cities.

Location-inventory-routing Problem in a Context of City Logistics: A Case Study of Jakarta

Location-inventory-routing Problem in a Context of City Logistics: A Case Study of Jakarta

Assessment of the obesogenic environment in primary schools: a multi-site case study in Jakarta

BackgroundChildhood overweight and obesity have increasingly been recognized as a significant global public health crisis, including in Asia. This study aimed to assess the obesogenic environment in primary schools in Jakarta, Indonesia.MethodsA qualitative, multi-site, case study design was used to capture different elements of the school environment and policies related to obesity, with a focus on nutrition and physical activity. An adaptation of the Primary School Environmental Assessment tool was used. Six primary schools in Jakarta were purposively selected based on their location, socioeconomic status, and type (public or private). In addition to direct observation at each school, interviews were conducted with the principal, physical education teacher, canteen staff, street food vendors, and students.ResultsAmong the six schools, two were private and four were public. The most popular foods consumed by students were unhealthy, such as deep-fried foods and sugar-sweetened beverages. Students had easy and constant access to unhealthy foods, whereas only limited variation of healthy foods were available in the school canteen. Some schools also allowed the student to have access to street food vendors. School policies related to healthy eating and physical activities had been implemented, mainly in the form of teaching these topics as part of the school curriculum. However, promotion of healthy eating and physical activities by the schools was still limited.ConclusionsThis study showed the usefulness of the Primary School Environmental Assessment tool in identifying obesogenic factors in urban area of Indonesia. Effective implementation of guidelines to foster good nutritional practices and healthy lifestyles at school should be prioritized to improve the health and nutritional status of the students.

Effect of sludge sewage quality on heating value: case study in Jakarta, Indonesia

Effect of sludge sewage quality on heating value: case study in Jakarta, Indonesia

Cloud Kitchen Development Analysis in Food and Beverage Industry: A Case Study in Jakarta

This study aims to analyze the development of the concept of "Cloud Kitchen" or "Dark Kitchen" or "Virtual Kitchen" in DKI Jakarta. In addition, exploration of each brand is carried out so that the potential of each brand can be seen. Empowerment of Micro, Small and Medium Enterprises (MSMEs) also needs to be considered as one of the motives for cooperation in the concept of "Cloud Kitchen" or "Dark Kitchen" or "Virtual Kitchen" in DKI Jakarta. Actually, the concept of cloud kitchen is not a new thing in DKI Jakarta and its surroundings. Currently, in DKI Jakarta there are at least 7 cloud kitchen players, namely Dapur Bersama GoFood, GrabFood Kitchen, Everplate, Yummykitchen, Kita Kitchen, Telepot, and Eatsii. In the Stars position, the GoFood and Yummykitchen Joint Kitchens are in that quadrant. Meanwhile, in the Question Marks position, there are GrabFood Kitchen, Everplate, Kita Kitchen and Telepot. However, for Eatsii it is still difficult to map considering that it has just established since 2021. The development strategies of these players are varied, one of which is the effort to support the empowerment of MSMEs in DKI Jakarta. The large potential of MSMEs in DKI Jakarta is a strategy for cloud kitchen players to increase their market share and growth potential. However, considering that this research is still qualitative and on desk research, further research is needed.

Revealing the Students’ Self-Regulated Learning Levels During the Covid-19 Outbreak: a Single Case Study in Jakarta

This study aims to identify the level, describe and analyze the self-regulated learning of class XI students during the COVID-19 pandemic at SMAN 63 Jakarta. The research method used quantitative descriptive with a survey design. The technique of collecting data through the MSLQ Likert learning strategies subscales by Pintrich 1991 with total technic sampling. The results showed that the self-regulated learning conducted by XI students during the covid-19 pandemic is in the moderate category with an empirical mean of 54.29 and a standard deviation of 6,933. The conclusion of this research is all of the students in class XI who tend to have the ability to manage resource management strategies are in the medium category. All indicators of resource management strategy were time management and learning environment (52.7%), effort regulation (67.3%), peer learning (62.4%), and help-seeking (53.7%).
 Abstrak
 Penelitian ini bertujuan untuk menggambarkan tingkatan, mendeskripsikan dan menganalisis self-regulated learning siswa kelas XI pada masa pandemi covid-19 di SMAN 63 Jakarta. Metode penelitian yang digunakan adalah metode penelitian kuantitatid deskriptif dengan desain penelitian survei. Teknik pengumpulan data menggunakan subskala learning strategies The MSLQ Scales karya Pintrich 1991 dengan teknik total sampling. Hasil penelitian menunjukkan bahwa self-regulated learning yang dilakukan siswa kelas XI pada masa pandemic Covid-19 berada pada kategori sedang dengan mean empiris sebesar 54.29 dan standar deviasi sebesar 6.933. Simpulan dari penelitian ini adalah seluruh siswa kelas XI cenderung memiliki kemampuan berdasarkan resource management strategies berada pada kategori sedang. Indikator dari resource management strategies adalah time and study environment (52.7%), effort regulation (67.3%), peer learning (62.4%), dan help seeking (53.7%).

Nature-based solutions for integrating flood and land subsidence: A case study in Jakarta and Semarang

Floods in Jakarta and Semarang are more frequent and impact more expansive areas. So far, flood management has been done mainly by increasing the capacity of drainage channels and draining water into the sea more quickly. This flood management needs to be evaluated because it leads land subsidence in Jakarta and Semarang to deepen. Thus, this research aims to identify the extent to which land subsidence causes the expansion of floods and alternative solutions to deal with floods and land subsidence in an integrative manner, especially in Ciliwung (Jakarta) and Garang (Semarang) watersheds. The method used was a review of various publications concerning findings of land subsidence, flooding, and the experiences of several countries in dealing with these problems. The results showed that land subsidence has occurred in Jakarta and Semarang. As a result of land subsidence, the flooding areas have increased due to the increase in lowlands, and therefore, it is difficult for the existing water to flow into the sea. Handling floods and land subsidence cannot be conducted locally but must be carried out in an integrative manner with a watershed and groundwater basin approach. One of the causes of land subsidence is excessive groundwater extraction. On the other hand, the groundwater must be increased. The increase in groundwater supplies not only reduces land subsidence but also reduces flooding, seawater intrusion and prevents drought in the dry season. A nature-based solution for reducing flood and land subsidence can be achieved by increasing vegetation cover and constructing water conservation buildings in the upstream areas.

Using open data to detect the structure and pattern of informal settlements: an outset to support inclusive SDGs’ achievement

ABSTRACT The detection of informal settlements is the first step in planning and upgrading deprived areas in order to leave no one behind in SDGs. Very High-Resolution satellite images (VHR), have been extensively used for this purpose. However, as a cost-prohibitive data source, VHR might not be available to all, particularly nations that are home to many informal settlements. This study examines the application of open and freely available data sources to detect the structure and pattern of informal settlements. Here, in a case study of Jakarta, Indonesia, Medium Resolution satellite imagery (MR) derived from Landsat 8 (2020) was classified to detect these settlements. The classification was done using Random Forest (RF) classifier through two complementary approaches to develop the training set. In the first approach, available survey data sets (Jakarta’s informal settlements map for 2015) and visual interpretation using High-Resolution Google Map imagery have been used to build the training set. Throughout the second round of classification, OpenStreetMap (OSM) layers were used as the complementary approach for training. Results from the validation test for the second round revealed better accuracy and precision in classification. The proposed method provides an opportunity to use open data for informal settlements detection, when: 1) more expensive high resolution data sources are not accessible; 2) the area of interest is not larger than a city; and 3) the physical characteristics of the settlements differ significantly from their surrounding formal area. The method presents the application of globally accessible data to help the achievement of resilience and SDGs in informal settlements.

The Possibilities for an Urban Community Action Plan and Collaborative Work Support for Slum Improvement: A Case Study in Jakarta

This study describes community development in the preparation for a community action plan for slum management in DKI Jakarta. The case study chosen for this research is the Akuarium village. The existence of slums is an inseparable part of the development of a city. The slum area contributes to several problems such as population density, building conditions, ventilation, sanitation, garbage, drainage, environmental roads, lighting and building layout. In an effort to overcome these problems, it is important to develop a community development concept that emphasizes the participation of the community through collaborative work between the government and citizens in the development process. The research that has been done has not touched on the substance of the problem faced by the urban poor and how the community plays a role in supporting the program. The purpose of this research is to find out how community-based development patterns can encourage collaborative work of each actor in structuring slum villages in DKI Jakarta. In this study, the method used is qualitative with in-depth interviews and data processing using the Nvivo 12+ application. The results showed that the principles of community development, including integrated development, participation, sustainable development, empowerment, and human rights, greatly influence the collaborative work of various stakeholders in planning an Akuarium development action plan.