Infrastructure Inputs Research Articles

The 2008 Sichuan Earthquake and Its Impacts on Economy

China, with one of the largest populations and the second-largest gross domestic product (GDP), experiences severe earthquake disasters. The Great Sichuan earthquake, one of the deadliest in Chinese history and the most devastating in China since the 1980s, occurred in 2008. This earthquake is characterized by its massive damage to the economy and the loss of a huge number of human lives. This study primarily focused on summarizing the existing studies related to the economic impacts of the Sichuan earthquake and specifically sought to identify the impacts of the Sichuan earthquake on the economy in the affected area. As a result, the earthquake had a significant long-term negative impact on the overall GDP. The earthquake greatly affected the tourist industry, and it has destructively influenced the development of the tourism industry in the quake-hit area. Also, this earthquake harmed the agricultural output in the damaged areas with different magnitudes in the Sichuan province. In addition, the Sichuan earthquake caused extensive damage to local critical infrastructure. The results implied that agricultural, tourism, and infrastructure inputs were reduced in the affected areas. Finally, it could serve as an important reference for the development program after a major earthquake.

Input Efficiency Measurement and Improvement Strategies of New Infrastructure under High-Quality Development

As a result of implementing new development concepts and absorbing new technical revolutions in the Intelligent Economy Age, new infrastructure is defined as a new driving force for high-quality development. However, as new infrastructure is constructed, there are problems such as the small scale of high-tech industries, weak economic support and human capital, and difficulty in carrying out new infrastructure construction projects, so it has become crucial to find solutions to these problems. Using the slacks-based measure model and Moran index, this study compares and analyzes the input efficiency of new infrastructure in 30 provinces of China from 2011 to 2020, alongside the analysis of temporal and spatial differences. China’s new infrastructure input generally shows a stable development trend in terms of efficiency, while the regional coordination still needs to be strengthened. Eastern China maintains a leading trend, Central China is developing rapidly, and the western region and Northeastern China do not form high-value agglomeration areas. This study puts forward relevant policy recommendations from four dimensions—optimizing the industrial structure, giving scope to government function, focusing on key areas, and compensating for weak links—to supply a powerful impetus for the development of new infrastructure.

Impact of digital infrastructure inputs on industrial carbon emission intensity: evidence from China's manufacturing panel data.

Digital infrastructure inputs (DIIs) are vital in strengthening the framework for developing the digital economy and encouraging economic growth. Nonetheless, the risks of environmental contamination are pervasively caused by the rapid expansion and utilization of digital infrastructure. Assessing the carbon emission intensity (CEI) and level of the DIIs of 18 manufacturing in China as the research subject, this study discusses the heterogeneous behavior of various input sources and industries. Furthermore, a two-way fixed effects model, threshold effects model, mediating effects model and moderated mediation effects model have been adopted to examine the nexus between DIIs and CEI of manufacturing. The results show that (1) DIIs raise China's manufacturing CEI and exert a non-linear threshold effect. (2) From the perspective of national attributes, the foreign DIIs will put more pressure on reducing the CEI in China. From the perspective of industry characteristics, DIIs are the most unfavorable for low-carbon development in capital-intensive industries. (3) Due to the mediating effect of total factor productivity (TFP), the positive influence of DIIs on CEI has dramatically diminished. (4) Participation in the global value chain (PAR) and foreign direct investment (FDI) exert moderating effects in the process of the direct effect and mediating effects. In light of the aforementioned conclusions, specific recommendations for developing digital infrastructure and reducing carbon emissions are proposed.

A PROPOSED FRAMEWORK FOR SURVEILLANCE OF DENGUE DISEASE AND PREDICTION

Abstract. Recurring outbreaks of dengue during past decades have affected public health and burdened resource constraint health systems across the world. Transmission of such diseases is a conjugation of various complex factors including vector dynamics, transmission mechanism, environmental conditions, cultural behaviours, and public health policies. Modelling and predicting early outbreaks is the key to an effective response to control the spread of disease. In this study, a comprehensive framework has been proposed to model dengue disease by integrating significant factors using different inputs, such as remote sensing, epidemiological data, and health infrastructure inputs. This framework for Dengue Disease Monitoring (DDM) model provides a conceptual architecture for integrating different data sources, visualization and assessment of disease status, and prediction analysis. The developed model will help forewarn the public health administration about the outbreak for planning interventions to limit the spread of dengue. Further, this forecasting model may be applied to manage the existing public health resources for medical and health infrastructure, also to determine the efficacy of vector surveillance and intervention programmes.

INFRASTRUCTURE IN THE FRAMEWORK OF PRODUCTION FUNCTIONS: EVIDENCE OF EU MEMBER STATES AT THE REGIONAL LEVEL

Infrastructure development is seen as an essential tool for boosting economic growth. Infrastructure is funded under various programs to contribute to economic growth, and reduce regional disparities. Evaluations of the results achieved have to be carried out to develop efficient infrastructure development and investment allocation policy. This is highlighted in both the reports of policymakers and scientific publications. The main limitation of these studies is that they focus on assessing the return on infrastructure development at the national level, leaving the question of what outcomes were achieved at the regional level. This article aims to evaluate the economic outcomes of transport and ICT infrastructure development at the NUTS 2 regional level in the EU-28 countries, using 2000–2019 data. The research is based on the neoclassical production function complementing it with an infrastructure indicator. Based on previous research, it is hypothesized that economic outcomes may depend on the institutional environment of the region. Consequently, the research model specification is supplemented by government quality as a possible moderator. Research findings suggest just motorway and internet infrastructure are significantly positively related to production outcomes. Estimations show higher government quality and less corruption are related to the bigger production output of the infrastructure input.

Intelligent Nanoscopic Cyclist Crash Modelling for Variable Environmental Conditions

A cyclist is a vulnerable road user whose interaction with the road infrastructure depends on several factors, including variable environmental conditions of lighting and meteorological road surface. This paper is concerned with nanoscopic crash modelling under the riskiest environmental conditions. There are very few works in the literature dealing with such modelling. An intelligent methodological framework consisting of the data collection unit and a knowledge processing unit (KPU) is proposed. In the knowledge processing unit, a combination of a) Statistical, b) Data learning and c) Casual inference methods are applied for investigating crashes on the study area of Tyne and Wear county in North-East of England. Three predictive nanoscopic road safety models are constructed (with 86% accuracy) using a) Spatial, b) Personal, and c) Infrastructure input variables. The importance of each of the identified input variable is estimated by deep learning and statistically validated through chi-square test and Cramer’s <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> statistic. It is found that unsafeness of interaction between rider and infrastructure depends on lighting and road surface meteorological conditions. Different environmental conditions present a varying degree of risk to different types of infrastructure. The riskiest environment conditions are significantly affected by rider’s gender and age, traffic flow regime, specific riding manoeuvre, and the road hierarchy difference. The increase in the number of variables, a rider encounters during his entire trip, imparts risky riding behaviour, affecting its safe interaction with the infrastructure. A novel infrastructure variable, i.e. ‘functional road hierarchy level and direction’ introduced in this work, is found to be a critical road safety variable. A shift in road safety analysis towards nanoscopic modelling can help achieve zero-vision road traffic fatality. The study reinforces the need to plan and design infrastructure to move towards a more holistic approach while considering this vulnerable road user’s limitations.

Modeling driver’s braking and steering behavior along horizontal curves of two-lane rural highways for ADAS applications

Objective Drivers continuously manipulate the vehicle’s steering and pedals (throttle, brake) while driving. Inadequate or excessive manipulation leads to crashes, possibly leading to injuries. An Advanced Driving Assistance System (ADAS) can warn drivers of inadequate or excessive manipulation to avert risky situations. Such systems evolve continuously and need more road infrastructure inputs for better driving assistance. Rural highways showcased more fatalities than urban counterparts, with more road departure crashes along horizontal curves than straight sections. Hence, the present study explores drivers’ braking and steering behavior along the horizontal curves of two-lane rural highways and proposes a suitable runoff risk model. Methods Sixty-eight drivers participated in a driving simulator study, where they drove along fifty-two horizontal curves in free-flow conditions. Typical five brake and three steering measures found in past studies were evaluated. Based on data distribution of brake and steering measures, Tobit and mixed-effects multiple linear regression models were developed to understand the association of these measures with the approach speed and geometric parameters of horizontal curves. Further, a generalized linear mixed runoff (road departure) risk model with a logit link function was developed to identify the effective measures among all brake and steering variables. Results The brake and steering measures were significantly associated with the approach speed and the geometric parameters such as curve radius, gradient, and turn type (left or right). Further, the runoff risk analysis revealed a significant effect of braking distance (BD) and standard deviation of steering wheel position (SDSWP). The interaction between BD and SDSWP was significant, suggesting that the runoff risk increased with SDSWP; however, it decreased with BD. Conclusions The runoff risk intensified with higher steering instability along horizontal curves, while it can be reduced with effective brake pedal usage. The study suggests better usage of brakes than steering before entering the curve. It potentially reduces the vehicle speed, thus ensuring more time to perceive the curve and help reduce the driver’s steering instability. The models developed in this study can be used in the ADAS systems upon validation with the field observations.

In-Company Smart Charging: Development of a Simulation Model to Facilitate a Smart EV Charging System

Current electric vehicle (EV) charging systems have limited smart functionality, and most research focuses on load-balancing the national or regional grid. In this article, we focus on supporting the early design of a smart charging system that can effectively and efficiently charge a company’s EV fleet, maximizing the use of self-generated Photo-Voltaic energy. The support takes place in the form of the Vehicle Charging Simulation (VeCS) model. System performance is determined by operational costs, CO2 emissions and employee satisfaction. Two impactful smart charging functions concern adaptive charging speeds and charging point management. Simulation algorithms for these functions are developed. The VeCS model is developed to simulate implementation of a smart charging system incorporating both charging infrastructure and local Photo-Voltaics input, using a company’s travel and energy data, prior to having the EVs in place. The model takes into account travel behaviour, energy input and energy consumption on a daily basis. The model shows the number of charged vehicles, whether incomplete charges occur, and energy flow during the day. The model also facilitates simulation of an entire year to determine overall cost and emission benefits. It also estimates charging costs and CO2 emissions that can be compared to the non-EV situation. With the VeCS model, the impact of various system design and implementation choices can be explored before EVs are used. Two system designs are proposed for the case company; a short-term version with current technology and a future version with various smart functionalities. Overall, the model can contribute to substantiated advice for a company regarding implementation of charging infrastructure.

Overcoming Disabilities Through Sports: The Inspiring Story of Rahul Ramugade

Parasports, and sports for disabled persons, has been a lesser known area in India, with all efforts to support disabled individuals focusing on broader social and health infrastructure inputs and employment avenues. This article looks at how sports for disabled people (parasports) can be a powerful enabler and tool for empowerment, through the journey of Rahul Ramugade, a Mumbai-based parasportsperson who has been part of the national wheelchair cricket team, and has also formed and led the Mumbai Wheelchair Cricket team.

AVUBDI: A Versatile Usable Big Data Infrastructure and Its Monitoring Approaches for Process Industry

The amount of sensors in process industry is continuously increasing as they are getting faster, better and cheaper. Due to the rising amount of available data, the processing of generated data has to be automatized in a computationally efficient manner. Such a solution should also be easily implementable and reproducible independently of the details of the application domain. This paper provides a suitable and versatile usable infrastructure that deals with Big Data in the process industry on various platforms using efficient, fast and modern technologies for data gathering, processing, storing and visualization. Contrary to prior work, we provide an easy-to-use, easily reproducible, adaptable and configurable Big Data management solution with a detailed implementation description that does not require expert or domain-specific knowledge. In addition to the infrastructure implementation, we focus on monitoring both infrastructure inputs and outputs, including incoming data of processes and model predictions and performances, thus allowing for early interventions and actions if problems occur.

The Sino-Laos Railway and the Connectivity Potential for a Small State

The Laos National Railway network is a milestone in the country’s transportation history. From the Chinese perspective, the China–Laos Economic Corridor (CLEC) is a vital sub-component of China’s Belt and Road Initiative (BRI). From the Laotian perspective, the Southeast Asian country intends to transform from a land-locked country (the only country within ASEAN or the Association of Southeast Asian Nations) into a land-linked country with Chinese equipment and infrastructure inputs. Through the railway system, Laos will be connected to maritime ports in China, Cambodia, Thailand and Vietnam, potentially benefiting its tourism industry, workforce mobility, land sales, services/retail outlets and intra- as well as extra-ASEAN trade and investments. Laos has proven to be the most politically stable, regime-reliable, perhaps complementary entity that has a stake in the success of the pan-Asian railway for the sake of its own economic development at the moment. At least, it does not require complicated diplomatic efforts, unlike the cases of Vietnam and Myanmar at this point of time. Thus, it may turn out to be a win–win situation for both the Laotians and the Chinese.

Evaluating the spatial spillover effect of farmland use transition on grain production – An empirical study in Hubei Province, China

Farmland resources are the most basic material for grain production. Therefore, the impact of farmland use transition (FUT) on grain production is receiving increasing attention from scholars. However, only a few studies have explored the spatial spillover effects of FUT on grain production and investigate the impact difference under topographical constraints. To fill this gap, this study uses county-level panel data of farmland use and grain production in Hubei Province from 2005 to 2017 and constructs a spatial econometric model to investigate the spatial spillover effects of FUT on grain production at the macro level and different topographical areas. The conclusions are as follows. (1) In the entire Hubei Province, there is a positive spatial spillover effect on grain production in the counties, and the spatial spillover effect is mainly driven by transition of the farmland quantity, machinery input, and farmland irrigation infrastructure input. (2) The topographical constraints lead to the heterogeneity of the spatial spillover effects of FUT on grain production. In plain areas, the spatial spillover effects of grain production mainly depend on transition of farmland quantity, machinery, fertilizers, and farmland irrigation infrastructure input. In hilly-mountainous areas, labor input is the main factor that affects grain production. (3) This study concludes that promoting the coordinated development of regional farmland use and grain production is one of the effective ways to achieve food security. Therefore, policy makers should formulate agricultural support policies based on the trends of FUT in different topographical areas.

AN ASSESSMENT OF FACTORS DETERMINING LAND USE COMPETITION BETWEEN ENSET (PERENNIAL) AND CEREAL (ANNUAL) CROPS IN HADIYA ZONE THE CASE OF LEMO WOREADA (SNNPR)

This study is about assessment of factors determining land use competition between cereals and enset crops in Hadiya zone, Lemo woreda. The main objective of the study was to assess changes in land use and cropping pat-tern, farmers’ perception on land use and cropping pattern as well as factors that determine land use competition between cereals and enset crops. A substantial section of this paper discussed the trends of land use and cropping pattern changes since 2000 and the determinant factors of the changes. Attempts are also made to explore the responses of peasants on causes of land competition between cereals and enset. The findings indicated that there are changes in land use and cropping pattern in the study area. It revealed that land use changes in the study area in the last 20 years, 2000 to 2019, specifically cultivated land and residential area expanded by 0.34% and 0.019% annually respectively. On the other hand, grazing and wood lands has decreased by 0.143% and 0.11% annually respectively. There were changes in the cropping pattern. The land use competition in dega area was among barely, wheat, enset and bean, whereas, in woinadega area the competition was amongst wheat, teff, chats and enset. These crops were dominant crops in dega as well as woinadega areas. The major determinant factors of the changes in land use and cropping pattern were population pressure, farm size, profit maximization, access to market, access to extension services, damages caused by wild animals, distance of plots from home, pests and diseases, land ragmentations, physical infrastructure and crop specific input requirements.

Supply chain finance credit risk evolving intelligent analysis system based on system dynamic model

Supply chain finance (SCF) plays a prominent role in solving the small-middle enterprises financing difficulties. But its credit risk is easy to conduct and magnify by the supply chain relation to develop into system risk. In the paper the main structure and causal relationship of SCF credit risk s ystem are analyzed. And then the intelligent analysis system model of SCF credit risk evolving mechanism is constructed based on systematic dynamic, which simulates how the key factors act to each other and how they function to SCF credit risk. The intelligent analysis results show that: (1) The sub-system of bank, core enterprise, small-mid enterprise and risk intermediary interact and constitute the SCF credit risk system. (2) The credit risk management strategy execution and the management infrastructure input of the bank sub-system can promote improving the management base of core enterprise and small-mid enterprises. (3) To increase the management efficiency of core enterprise and small-mid enterprises can improve enterprises operating level and solvency, and then decrease the SCF credit risk. And also, the core enterprise influences the SMEs’ solvency by actively function to the operation ability. (4) The increasing of risk intermediary can accelerate to the SCF loan quantity, and at the same time, reduce the credit risk.

Economic viability of pitaya (Hylocereus sp.) Cultivation in Tomé-Açú Municipality, Pará State, Brazil

Pitaya (Hylorereus sp.) is a fruit from the botanical family Cactaceae, originally from Latin America. In Brazil, pitaya cultivation is promising due to the fruit’s reputation of being nutritious and having many uses. This study’s objective was to analyze the economic viability of two pitaya production systems in Tomé-Açu municipality, the largest producer of pitaya in the Pará state, Brazilian Amazon. The data were obtained through interviews with two producers, along with field observations of their production systems, which are representative of the cultivation norms in Tomé-Açu. The data were used to estimate the planting and maintenance costs for 1 ha of land using different cultivation methods, identified as: 1) extensive production system and 2) intensive production system. The two systems’ cash flows were estimated over a 20-year period, then analyzed to estimate the net present value, internal rate of return, benefit-cost index, payback period, and break-even point. The intensive production system was found to have a higher implementation cost, due to its irrigation system, while the extensive production system was found to have lower investment and maintenance costs. The economic viability indicators show that both production systems are economically viable, with the extensive production system being more attractive, especially for family farmers who cannot invest in expensive irrigation infrastructure and chemical inputs. In conclusion, the investment in pitaya cultivation is economically viable and constitutes an alternative to agricultural cultivation in Pará state, which can contribute to fruit diversification.

Sensitivity of urban flood simulations to stormwater infrastructure and soil infiltration

Flooding from intense rainfall is a major hazard in many urban areas. One of the major challenges in urban flood simulations is lack of data about the location and properties of stormwater infrastructure and land cover. In this paper, we investigate the sensitivity of urban flood simulations to inputs of stormwater infrastructure and soil characteristics. We use a 2D hydrodynamic model (MIKE URBAN) to simulate flood events on the University of Alabama (UA) campus in Tuscaloosa U.S.A. Infiltration rate, soil moisture, and soil texture were measured in the field. Soil texture was found to be homogeneous across campus (sandy loam) but with a high degree of spatial and temporal variation in infiltration rate and soil moisture. Comparison between different storm event return periods (10, 25, 50, and 100 years) shows that the same flooding hotspots are persistent but with considerable variation in water depth and flood extent. To investigate the sensitivity of the simulations to stormwater infrastructure, simulations without the stormwater infrastructure input were conducted. The results show that stormwater infrastructure decreases flooding volume of RP 10, 25, 50, and 100 by factors of 20, 14, 12, and 8, respectively. This shows that urban flood simulation is highly sensitive to the inclusion of stormwater infrastructure, though with decreasing relative impact for larger events. To investigate the sensitivity of the simulations to soil characteristics, four land-cover simulations (actual, uniform, entirely pervious, entirely impervious) were compared. The results show flood simulation predictions are sensitive to both the value and spatial explicitness of the soil input data. We discuss challenges in urban flood simulation and their potential solutions in the context of emerging frameworks for national and global hyper-resolution flood forecasting and analysis.

ANALISIS PENYEBAB KETERLAMBATAN MULAI OPERASI PERTAMA PASIEN ELEKTIF DI INSTALASI BEDAH SENTRAL RSAM

&lt;p&gt;&lt;strong&gt;&lt;em&gt;Abstract&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Introduction&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; : Operating room eficiency can be assessed using 6 indicators, one of which is the delay in starting the first elective surgery. From the results of preliminary research in the operating room of the Central Surgical Installation (CSI) R&lt;/em&gt;&lt;em&gt;SUD dr. Achmad Mochtar &lt;/em&gt;&lt;em&gt;(RSAM) Bukittinggi in January and February 2019 showed that 81% of elective surgeries were delayed. Delay ranged from 30 minutes to several hours. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Objective&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: To find out what causes the delay in begining the first elective surgery in the operating room of the Central Surgery Installation at RSAM in 2019 in terms of input, process and output.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Method&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Qualitative research using the Framework Analysis method was conducted in the operating room of the CSI RSAM. The study began in April until October 2019&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Conclusion&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: The reason for the delay in begining the surgery in terms of HR input is that the leadership in CSI is not maximized, lack of discipline and commitment of the operator doctor and anesthesiologist, the anesthesiologist's schedule is not optimized, lack of registration officers, no optimal settings for radiographer for operating rooms and the lack of skills. The problem with SOP inputs is that there are still incomplete SOPs and not yet optimal implementation of existing SOPs. In the infrastructure input the problem is in the distance from the patient's ward to the operating room, CSSD is not integrated to the operating room and picking up surgery clothes and linen to CSSD is late. From the process factor, there are obstacles in the process of delivering patients to the operating room, the arrival time of the surgeon/operator and anesthesiologist are behind schedule, the lack of optimal monitoring and evaluation, and the lack of optimal implementation of reward and punishment. Output shows that from 40 firsts surgery schedules, 35 surgeries were delayed (87.5%) and only 5 operations were carried out on time according to the schedule (12.5%).&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: &lt;/em&gt;&lt;em&gt; Efficiency, Operating Room, Monitoring, Reward, Punishment&lt;/em&gt;&lt;/p&gt;

Blessing or curse? Impact of land finance on rural public infrastructure development

While land revenue has played an important role in China’s fiscal revenue and expenditure, little is known of the linkage between land revenue and rural infrastructure inputs and its impact on the landscape of fiscal spending on rural infrastructure. To investigate this further, we study the effect of land finance on rural infrastructure inputs by a regression analysis of a panel data set collected for 30 provincial-level regions over a ten-year period. The results show that the effect is jointly determined by the amount of land revenue and degree of reliance on land finance. Increases in land revenue contributed to an increase in rural infrastructure inputs while an increase in reliance on land finance decreased rural infrastructure input. Whether this is a blessing or a curse depends on how dependent the region is on land revenue and the region’s long-term development strategy. Although land finance has mixed effects on rural infrastructure input, it does not influence the “market town-biased” allocation of fiscal spending on rural infrastructure. Land finance can be used to support rural infrastructure development. The challenge for land financed rural public infrastructure development is how to augment land revenue and avoid a heavy dependence on land finance in the long run.

Extending and operationalizing construction productivity measurement on building projects

Measuring construction productivity in an accurate, repeatable and reliable way represents a significant problem at a building project level of enquiry. The research develops a measurement framework that balances simplified data gathering against explanatory ability. It aims to assist analytically driven process improvement. Debate and discourse are used to draw upon the extant literature in creating a logic-based flow of ideas to develop the framework. Targeted use of empirical cost and site process data from case studies are presented to punctuate the discourse. The derived approach advocates multifactor measurement inclusive of labour and temporary production infrastructure inputs, set against Gross Floor Area outputs. Emphasis is placed on separately measuring homogenous and heterogeneous parts of work processes. A reductionist approach is used to operationalize measurement where projects are categorized according to fitness-for-purpose criteria and links made between systems, activities and tasks. Emphasizing measurement of homogenous parts of the work is new to the literature. It enables delineated measurement between work involving mass economies of scale (homogenous work), versus customized work (heterogeneous work). The approach enables improved benchmarking, diagnostic and predicative options. A course of ongoing research is provided to assist ongoing development and implementation.

ENHANCING ENGLISH SPEAKING SKILL THROUGH JIGSAW COOPERATIVE LEARNING (Action Research In X Class of MIA SMA Negeri 2 DKI Jakarta)

Abstract&#x0D; Many factors make quality education or not. These factors include the professionalism of educators, educational inputs both in the form of student input and facilities (infrastructure input), learning process, environment and others. This paper attempts to confirm the process of improving students' speaking skills on English subjects through cooperative learning of Jigsaw models on students in X Class of MIA SMA Negeri 2 DKI Jakarta. The subjects were 108 students studying speaking English The subjects then were randomly assigned into experimental group and control group The experiment lasted for nine weeks started with pre-test in the beginning and ended with a post - test in the last meeting. During the treatment, the teacher applied planning, drafting, revising and editing stages in learning. The result shows Learning outcomes in students, especially speaking skills in students in SMA Negeri 2 DKI Jakarta has increased. This is evident through the experiments on cycles I and II both for class 10 Mipa 1, from the mean of 70.9167 to 84.2778. class 10 Mipa 2, from the average 71.8056 to 86.2222 and for class 10 Mipa 3 from the average 70.5833 to the average 84.2222 so that the total increase during applying the Jigsaw type cooperative learning model from the initial value.&#x0D; Keywords: skill speaking english, jigsaw cooperative learning