Mall Area Research Articles

The decision to use ShopeePay as a substitute for cash in the cashless era

The aim of this study is to evaluate the convenience, promotion, and security factors associated with the use of Shopee Pay electronic currency by visitors in malls in the Central Jakarta region. The study sample comprises persons who frequent shopping malls in the Central Jakarta Region. This survey includes a group of 103 persons who use Shopee Pay electronic money in the mall area of Centra Jakarta. The sample selection was carried out using the method of incidental sampling. The data used in this study include primary data, especially questionnaires that were distributed to respondents. The study results suggest that the convenience and promotional activities have a positive influence on the decision to use Shopee Pay digital currency. This suggests that the choice to utilise electronic currency is impacted by factors such as convenience and promotional offers. Before proceeding, consumers will evaluate whether a system would streamline their activities, considering the wide array of attractive offers offered by the shopeepay site, as well as compelling marketing about available specials on the platform. Furthermore, security concerns negatively affect the willingness to use Shopee Pay as a digital payment option. This text explores the relationship between security and the choice to use electronic money. Before choosing the Electronic Money platform, customers must ensure that the funds saved in the electronic wallet will be protected and resistant to unauthorised access, therefore reducing the likelihood of unwanted events.

Combining samples in small area estimation: An application to poverty mapping in Vietnam

AbstractSmall area estimation (SAE), which combines a population census and a sample survey, is widely used to estimate poverty and welfare indicators in small areas. A common situation in practice is that a population census is conducted using both short‐ and long‐form questionnaires. The short form is used to collect basic demographic information for the whole population, while the long form is used to collect additional information, such as employment, from a random sample. This study shows that combining both short‐ and long‐form data can improve estimation efficiency. This method is applied to poverty maps for the 2014–2019 period in Vietnam.

Thermoplastic polymer track with gearing mechanism to harvest green energy for sustainable development

Consumption of energy and its demand is increasing constantly. There are various ways to generate energy. Non-renewable energy sources are in high demand, which causes harmful effects on the atmosphere. So environmentally friendly energy sources are very much required. Recently various researchers have been working towards green and environment friendly renewable energy causes. Energy generation from renewable sources, India is within top five position throughout the world. Support towards enhancement of energy generation by renewable sources has been declared by our Honourable Prime minister. The present work deals with a designed model to generate electricity by utilizing energy from footstep movement and vehicle motion. The designed model consists of a gearing mechanism, lever, and thermoplastic polymer track attachment. Thermoplastic tracks are easy to use because of their easier attachment and smooth surface. It is required to attach our designed system in places where maximum mobility of people and vehicle motions is possible. Generally, the places are national highways, temple roads, mall areas, etc. Due to movements on the track, the pressure energy of the foot and vehicle wheels transfers to rotational energy through the gearing attachments of our designed system. This rotational energy is utilized to rotate the armature of the generator to generate electricity and that electricity is stored in the battery for utilization on demand. The lever arm and thermoplastic track are placed with a 10 mm gap so that when load is applied on the track, the thermoplastic will deflect and the load will be transferred to the lever. Due to the provision of a gearing mechanism in our designed system, less input on the track will produce the required rotation of the generator shaft. Natural walking on the track to harvest energy without disturbing the body is very suitable for the stability of this designed system due to the provision of thermoplastic tracks.

Urban sustainable intervention to address the physical factor for degradation of visual place quality in the hilly urban region: A case of Manali town, Himachal Pradesh.

The depletion of urban aesthetics is a major issue in the urban hill town due to the rapid growth in urban infrastructure. The potential for growth in the urban hill town is at a very rapid state, which affects the local population and its ecological environment. Urban sustainable development in urban hill towns is a crucial challenge. This type of uneven development leads to a degradation of the visual quality of place in hill towns, which defines the overall evaluative image of the town’s urbanscape. Manali is located in the northern part of the Kullu Valley in Himachal Pradesh, India. This study intends to investigate the physical parameters of this decline and assess possible solutions for improving hill towns’ visual quality. The study’s thorough grasp of the problem and its possible solutions is based on the author’s integration of concepts from several different domains, such as urban design, planning, and architecture. This research emphasises the vital role of visual aesthetics in enhancing quality of life of both inhabitants and visitors to the region. Furthermore, it determines the adverse effects of decreased perception. The research proposes approaches to enhance the deteriorated visual quality of the urban environment in Manali, a hilly town. These strategies comprise augmenting public spaces, giving priority to pedestrian infrastructure, and encouraging community participation in the design procedure. The research is based on enhancing the visual place quality of areas within Manali town, including Manali town, old Manali, the ISBT, the Tibetan colony, and the mall area, utilising surveys based on questionnaires and dimensions of visual place quality. The study implemented the Analytic Hierarchy Process methodology to evaluate and rank various physical factors. The results yielded viable solutions, such as the enhancement of street squares, sidewalks, and widths, as well as the revision of planning and development regulations and legislation. The findings of the research may have potential applications in identical topographically undulating areas.

Conjugate Modeling Approaches for Small Area Estimation with Heteroscedastic Structure

AbstractSmall area estimation (SAE) has become an important tool in official statistics, used to construct estimates of population quantities for domains with small sample sizes. Typical area-level models function as a type of heteroscedastic regression, where the variance for each domain is assumed to be known and plugged in following a design-based estimate. Recent work has considered hierarchical models for the variance, where the design-based estimates are used as an additional data point to model the latent true variance in each domain. These hierarchical models may incorporate covariate information but can be difficult to sample from in high-dimensional settings. Utilizing recent distribution theory, we explore a class of Bayesian hierarchical models for SAE that smooth both the design-based estimate of the mean and the variance. In addition, we develop a class of unit-level models for heteroscedastic Gaussian response data. Importantly, we incorporate both covariate information as well as spatial dependence, while retaining a conjugate model structure that allows for efficient sampling. We illustrate our methodology through an empirical simulation study as well as an application using data from the American Community Survey.

Diversity and composition of ant species in different urban areas in Bogor, West Java, Indonesia

Abstract. Harahap IS, Asnan TAW, Widayanti S, Widhiastuti H. 2022. Diversity and composition of ant species in different urban areas in Bogor, West Java, Indonesia. Biodiversitas 23: 4090-4096. Land use change, from natural to urban areas, is a threat to biodiversity because the disturbance created by human can destroy the habitat and decrease species richness. Ant is one of the most abundant animals in tropical habitats and most intrusive in an urban area. This research aims to determine the types of ants commonly found in various urban ecosystems in Bogor, West Java, Indonesia. Ant observation and sampling were carried out in Bogor City Areas at four different urban ecosystems, i.e., office area, shopping mall, housing area, and bus station. At each sampling location, ten observation plots were taken under different environmental conditions. Sampling was carried out for 6 months, from April to October 2021 with the direct collection and trapping method. The sample was then carried out to the laboratory for identification and data analysis process. The results of the species inventory obtained 7532 individuals and 28 species from 4 subfamilies, namely Dolichoderinae, Formicinae, Myrmicinae, and Ponerinae. The diversity of ant species at each location showed that the ant species in the bus station were not significantly different from the mall area. However, the diversity of ant species in three locations, namely bus stations, malls, and housing estates, showed significant differences with the diversity of ant species in office habitats. Anoplolepis gracilipes which is an invasive tramp species, is one type of ant found in all sampling locations with a relatively high abundance.

P2-Loc

On-demand delivery is a fast developing business where gig couriers deliver online orders within a short time from merchants to customers. Couriers' accurate indoor locations play an essential role in the business. Most of the existing indoor localization methods cannot be applied in practice due to the high cost or data unavailable on off-the-shelf smartphones. This paper explores a new angle to solve the problem in a relative and infrastructure-free fashion. We design a person-to-person localization system that can (1) detect encounter events via Bluetooth on couriers' smartphones, and (2) infer couriers' relative locations to all the indoor merchants via deep learning on a graph neural network. The system is infrastructure-free, map-free, and compatible for off-the-shelf devices. We deploy the system on a real-world industry platform. The system runs on the smartphones of 4,075 couriers around 79 merchants for a month. The evaluation in a mall area shows that P2-Loc improves the mean average error compared with state-of-art infrastructure-based, report-based, and encounter-based methods. We also use an application analysis based on real-world orders and trajectory data to show that the P2-Loc can save around $40,000 for the platform every day with improved indoor localization results.

Perbandingan Suhu pada Ruang Terbuka Hijau (RTH) dan non RTH di Area Megamas Manado

This study was conducted with the aim of knowing changes in temperature in the urban forest green open space (RTH) area and in non-green open space areas in the Megamas Manado complex. This study uses a descriptive analytical design. In this study, there are microclimate variables and the determination of the sample using purposive sampling method. This study aims to test the hypothesis whether it is true that the temperature in the green open space area is lower than the temperature in the non green open space area. There are three data collection points, namely in the urban forest area, the Mega Mall area, and the Marina-2 Manado area. Based on the average temperature value, it shows that the temperature in the green open space is lower than the temperature in the non green open area. The statistical test results also state that there is a significant (significant) difference between the temperature in the green open space and the temperature in the non green open space. Therefore, this research concludes that the Green Open Space Area (RTH) can reduce solar energy, so that the temperature in the green open space area is lower than the temperature in the non-RTH area.

The Effect of Customer Loyality and Satisfaction's Factors in Visiting Mall XYZ

Mall Success can be seen with a large number of mall visitors and visitors coming. In this case, one of the malls in the Tidar area of Surabaya is more important than most of the malls in general in the city of Surabaya. At the XYZ mall area, visitors are seen lonely from day to day, this is a big question mark whether visitors are satisfied to receive a compilation of visiting the mall. For this reason, the satisfaction of visitors and customers in the mall is an important factor in determining the buying and selling activities in the mall. The research offered suggests about customer satisfaction and customer loyalty proposed by, hedonic value, Relaxation Value, socialization value, Utilitarian Value. This can affect the purchasing power of consumers to buy at the mall. Satisfaction can provide a supported spending will, thus providing a significant turnover of money. By creating a sense of satisfaction can generate customer loyalty in the mall. This research was conducted by distributing questionnaires to visitors or customers who have come to the XYZ mall. The method used in this research is Structural Equation Modeling. by Processing data using Smart PLS software because the research model is complex. The findings in this study are the outcome variable, Hedonic Value, Relaxation Value, and Socialization Value regarding customer satisfaction and customer loyalty, while the Utilitarian Value only has a significant effect on customer satisfaction. The results of this study are expected to make the mall management considerations to develop the right strategy in increasing the number of visitors and customers to come to the mall.

Implementation of Intelligent Parking System Using IoT-Based Devices (case Study of Galaxy Mall Surabaya)

Many parking spaces available today generally require drivers to find their own location empty parking. Especially in parking lots located in large areas such as the Galaxy Mall area Surabaya. This will cause problems getting parking location information because drivers are not uncommon have to circle the parking building to get an empty parking location. The problem can avoided if the driver already knows the state of the parking location in the area to be seven. Driver can find out the availability of vacant parking locations in the destination area. In this case, we need a a system that can help drivers find vacant parking locations. Internet of things is a a concept or program by which an object has the ability to transmit or transmit data through the network without using the help of computers and humans. Internet of things or often called IoT is currently experiencing many developments. From the test results it can be concluded that the average Raspberry Pi boot delay on this system is 221.1 seconds. Sensor, From the test results it can be concluded that the average delay in scanning the QR Code using a Raspberry Pi camera at the entrance bar is 59.3 seconds, From the test results it can be concluded that the average delay in scanning QR Code using a camera The Raspberry Pi on the exit bar is 59.4 seconds

The University of Texas's “Racial Geography Tour,” designed by Dr. Edmund Gordon

The University of Texas's “Racial Geography Tour,” designed by Dr. Edmund Gordon

DESIGN AND USABILITY OF FACE RECOGNITION BASED ANNOUNCEMENT SYSTEM

The rapid developments in technology have an increasing impact and use on biometric person recognition systems. Facial recognition-based systems, one of the biometric person recognition systems, have been widely used in recent years thanks to their easy implementation, fast integration and simple usage as they do not require any additional equipment. Especially the widespread use of computer vision and cloud-computing based applications, smart face recognition systems have become an indispensable part of our lives in recent years. The use of these systems, which have become widespread in security, health, education, military, shopping mall and industrial areas, has increased more during the pandemic period. Institutions and organizations do not want to allocate time and cost to write their own software for face recognition based systems. The services offered by major cloud computing providers can be used to solve this problem. In this context, the article presents a smart announcement system design using cloud computing based face recognition technology. In the past, making an announcement has been seen as a difficult task. It was thought to be a time consuming task, both because of the cost of printing and because all the operations had to be repeated when there were changes in the announcement. Today, signs have left their places to digital screens. It will especially ensure that announcements, warnings, promotions, and notifications are performed effectively at the developed system for large scale institutions, organizations, factories, universities, shopping malls and health institutions. Facial recognition based smart announcement system detects features such as person recognition, gender, and age estimation at a rate of 100% and displays personal announcements according to their priority status. In addition, according to the experimental studies, it was observed that the person recognition and the presentation of the announcements on the screen took an average of 1.3 seconds. According to the announcement system survey, 85% of those who use the system stated that it is useful and user-friendly.

Between Natural and Anthropogenic Coastal Landforms: Insights from Ground Penetrating Radar and Sediment Analysis

Both natural and anthropogenic coastal landforms characterize Penang Island. As years have passed it is a challenge to differentiate the genuineness of landmasses created by natural geological formations or by coastal reclamation projects. An account is given of the environmental impact of solid wastes used for reclaiming land in coastal areas of Penang and of the impact of a major sewage outfall in the western channel. Leaching of heavy metals was shown to be one of the main sources of contamination from solid wastes. This paper presents eight lines of ground penetrating radar (GPR) surveys and sediment analysis to identify the anthropogenic interventions that shaped the urban landscape of Penang Island by excavations, filling, and embankment construction along the coastline and differentiate it from the natural one. The surveys were implemented in two locations, the Batu Ferringhi area, representing the natural coastline, and Persiaran Bayan Indah (the Queensbay Mall area), representing the anthropogenic coastal landform. The apparent depth of penetration that was achieved using a 250-MHz antenna is limited (less than 5 m). The results show between natural and anthropogenic sediment recorded different radar facies. In complement mode, mean grain size distribution, sorting, skewness, and kurtosis graphics of sediment samples from both sites correspond with the GPR data. This technique can likely be applied to the developing coast, where natural and anthropogenic coastal landform data is incomplete, considering future coastline development.

Comparison of FairMOT-VGG16 and MCMOT Implementation for Multi-Object Tracking and Gender Detection on Mall CCTV

The crowd detection system on CCTV has proven to be useful for retail and shopping sector owners in mall areas. The data can be used as a guide by shopping center owners to find out the number of visitors who enter at a certain time. However, such information was still insufficient. The need for richer data has led to the development of more specific person detection which involves gender. Gender detection can provide specific information on the number of men and women visiting a particular location. However, gender detection alone does not provide an identity label for every detection that occurs, so it needs to be combined with a multi-person tracking system. This study compares two tracking methods with gender detection, namely FairMOT with gender classification and MCMOT. The first method produces MOTA, MOTP, IDS, and FPS of 78.56, 79.57, 19, and 24.4, while the second method produces 69.84, 81.94, 147, and 30.5. In addition, evaluation of gender was also carried out where the first method resulted in a gender accuracy of 65\% while the second method was 62.35\%.

Comparison of Naive Bayes Algorithm and Support Vector Machine using PSO Feature Selection for Sentiment Analysis on E-Wallet Review

Cashless payment habits have been widely applied to the transportation system, restaurants and shops in the mall area. So, it is normal if the growth of mobile payment services is currently very rapid. The ease of doing transactions and promotional offers in the form of points and cashback in digital wallet applications (e-wallets) is very beneficial for its users. One of the most popular e-wallets is OVO. With so many reviews about OVO customer opinions on social media, there has also been a lot of public opinion. These opinions can produce negative or positive statements. Sentiment analysis is the mining of opinions or text to classify opinions or user reviews, of a brand reviews, product reviews, or service reviews into the category of positive or negative opinion. The methods used in this research are Naive Bayes and SVM. Both of these algorithms are the best algorithms widely used in text classification research. However, both of these algorithms have weaknesses in several parameters. So, in this study Feature Selection is used to improve its performance. The evaluation was carried out using 10-fold cross validation. Measurement accuracy is measured by confusion matrix and ROC curves. This study uses 500 positive reviews and 500 negative reviews as data training. The results of this study indicate that the use of PSO-based Naive Bayes algorithm produces an accuracy value of 93.10 percent with an AUC value of 0.750. While the results of research from the PSO-based SVM algorithm are 91.30 percent with an AUC value of 0.970. Based on these results the accuracy value generated by the Naive Bayes algorithm is classified as Fair Classification and SVM is classified as Excellent Classification. The AUC value generated by the Naive Bayes algorithm is also smaller than SVM. Therefore, in this study found that SVM is the best algorithm in classifying text.

ANALISIS FAKTOR KEMACETAN TERHADAP KINERJA LALU LINTAS DI RUAS JALAN JENDERAL BASUKI RAHMAT (STUDI KASUS: MALL BASSURA)

Commercial buildings in the Bassura Mall area (Jalan Jenderal Basuki Rahmat) have resulted in congestion in the area. Vehicles use road bodies to park their vehicles, sidewalks that are used as trading places by street vendors, and the position of the entrance / exit of Bassura Mall for four-wheeled vehicles that is not strategic. These things have caused the author to choose a location in the Bassura Mall area (Jalan Jenderal Basuki Rahmat), East Jakarta which is a local route, where East Jakarta as one of the big cities in the Special Capital Region of Jakarta also experiences high vehicle growth, p. This can be seen on roads in East Jakarta which often experience congestion during rush hour. The purpose of this research is to determine the traffic performance in the area. The method used in this research is direct observation method at the research location and field data collection in the form of parking volume data, pedestrian volume, vehicle volume entering / exiting Mall Bassura, traffic volume, and road performance. Observations were made on weekdays and holidays. The results of the analysis of the performance of the road sections show that the traffic volume on the roads around Mall Bassura is 32,433 SMP / hour on weekdays and 22,577 SMP / hour on holidays, with the service level index being in the F category on weekdays and holidays. Thus, the congestion factors mentioned above have resulted in a decrease in road capacity which has an impact on road performance.

Impact of Job Insecurity and Work Overload on Employee Performance With the Mediating Role of Employee Stress: A Case of Pakistan’s Fast-food Industry

The fast-food industry is one of the booming industries in Pakistan with rapidly developing human resources. However, quick growth has become impeded by numerous human resource management challenges. The purpose of this study is to investigate factors/variables that cause stress among employees in the workplace which consequently affect their performance. Pakistan’s fast-food sector has been taken into account and a comprehensive study has been carried out to find out which variables result in employee stress and affect their overall job performance. Primary data was collected through three hundred and fifty questionnaires disseminated throughout various areas of Lahore, Karachi and Islamabad including Emporium Mall, Packages Mall and Dolmen Mall, Lucky One Mall, Centaurus, and key areas popular for fast-food in those cities. Several statistical tools including; Reliability and Validity Analysis, Factor Analysis, Regression analysis, KMO, Cronbach Alpha and the Bartlett Test, are used for data analysis on SPSS and Smart PLS. Results of the analysis show that Work Overload, Job Insecurity (independent variable) and Employee Stress (mediating variable) have a significant impact on Employee Performance (dependent variable). The relationship of Job Security and Work Overload with Employee Stress is positive. Similarly, the relationship between Employee Stress and Employee Performance is also positive and significant. The study described in this paper thoroughly focuses on all the major causes of employee’s stress and its impact on employee performance, it also suggests how Fast-food sector of Pakistan should consider these factors in order to address these issues and provide favorable workplace environment.

Performance Analysis of Resource Scheduling Techniques in Homogeneous and Heterogeneous Small Cell LTE-A Networks

The purpose of LTE-A technology is to provide high spectral efficiency, lower delay and stronger intercell interference control for a multi- user environment. The architecture of LTE basically contains E-UTRAN and evolved packet core. E-UTRAN is the combination of UE and ENodeB (enhanced node B) used to control the radio network. EPC provide end to end connection and backward capability with previous networks. Major entities included in EPC are P-GW, S-GW, HSS and MME. This new architecture fulfil the requirement of next-generation mobile networks for high connectivity and multiple type of networks. Heterogeneous network is one of them in which different power base stations like femtocell, picocell, and radio remote head deployed in a geographical area with in macrocell cell. It is one of the cost effective solution to provide high throughput and spectral efficiency and fairness for cell edge user. Deployment of femtocell improved the data rate and coverage in small regions like office, home, shopping mall and dense areas. Along with this an efficient fair sharing of resource allocation plays an important role in improving the performance of networks. This paper analysed the performance of round robin, resource fair, Max-throughput, best CQI and proportional fair LTE-A resource scheduling techniques on homogeneous networks. For heterogeneous networks a new cluster based proportional fair resource scheduling technique is proposed, which provides an efficient resource to the most sufferer user and improved fairness and cell edge user throughputs. In heterogeneous networks multiple femto cell were deployed in macro cell area. Access policies are applied on open and closed group. The performance is measured in terms of cell edge throughputs, peak throughputs, average throughputs, wideband SINR, spectral efficiency, and fairness index for homogeneous, heterogeneous networks and for user mobility. The performance result showed that Best CQI and MaxTP scheduler outperforms in throughput level and attains highest average cell throughput of 83 Mbps and UE average throughput of 20 mbps in homogeneous networks and approximately 43 Mbps in heterogeneous networks. Comparative result in heterogeneous network indicates that the proposed scheduler increases 2% gain in fairness and 1–1.89% gains in edge throughputs with respect to proportional fair scheduler and allocates 79% fair share resources among UE. Round robin scheduler delivered very poor throughput and fairness index in both homogeneous and heterogeneousnetworks.

The Taste of Peranakan Tionghoa in Listening to Indonesian and Chinese Music and Their Relation to Cultural Identity

This research discussed the taste of Peranakans Tionghoa in listening to Indonesian and Chinese music and its relation to cultural identity. The history of the settlements in Chinatown at Glodok, Jakarta, Indonesia, brought ethnic and cultural issues. Then, the assimilation was inadequate that caused the elimination of the original culture and finally form a new culture. This research questioned how the Peranakans Chinese cultural identity was formed and related to the taste of listening to Chinese and Indonesian music using Hall’s perspective of cultural identity. A qualitative method was used to describe, explain, and analyze data. Data in the research consisted of observation and interview of the 30 Peranakans Tionghoa at Glodok, covering the area of mall, café, and restaurant. The collected data were classified into similarities and differences from each aspect. The classification was linked to the three groups who preferred to listen to music and find their cultural identity. The result shows that the taste of Peranakan Tionghoa in listening to Indonesian and Chinese music depends on the elements and the function of music. Those aspects emphasize the language to understand what the song tells about. Further, the music could be an intermediary for cultural unification from both origins of (Chinese and Indonesia) who are fused to the relation of the cultural identity. Related to identity, Peranakans Tionghoa is becoming an identity.

Applying innovation attributes to predict purchase intention for the eco-labeled products

PurposeThis paper aims to make use of the innovation diffusion theory to predict the purchase intention for eco-labeled products.Design/methodology/approachData are collected from 180 individuals in the Mid Valley shopping mall area in Malaysia. It is then analyzed using SPSS and Smart PLS. The measurement model is analyzed using composite reliability, convergent and discriminate validity, while the structural model is used to predict the relationships between variables.FindingsResults indicate that the relative advantage, trialability and observability are positively related to eco-labeled products purchase intention, while the complexity is negatively related to eco-labeled products purchase intention. However, compatibility is not positively related to eco-labeled products purchase intention.Practical implicationsMarketers should enhance the observability of eco-labeled as it is the most influential attribute affecting eco-labeled products purchase intention. Relative advantages of eco-labeled products are also important to stimulate purchase intention. Marketers could best relate the innovation to context-specific use situations enabling consumers to evaluate the use consequences of the innovation, and therefore, may assess its particular benefits.Originality/valueIt explores the potential of a theoretical framework based on innovation diffusion theory to explain eco-labeled products purchase intention.