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Scheduling is an important thing to do when completing a project. But sometimes the implementation deviates from the plan, so it is necessary to supervise and control the project so that the completion of the project is not delayed. Such was the case with the Langsa City Forest Park gate construction project where the completion of this project was pushed back a few days from scheduled. Delays occur due to hampered availability of materials needed, as well as weather and field conditions. So thatthis research was carried out with the aim of knowing the project control method in the Langsa City Forest Park gate construction project and to find out the comparison of project completion time using the CPM method with the Bar Chart method used by CV. Mechanical Structure. This study uses CPM (Critical Path Method) to determine network planning, critical activities, and critical paths, as well as analyze the optimal duration and cost needed for the Langsa City Forest Park gate construction project to avoid delays. Data collection techniques are carried out through interviews, direct observation, and documentation. In this study, it is known that the normal duration of the project is 21 weeks with a total cost of Rp 1,223,049,144.00. After using the CPM method, it is known that the critical path lies in activities A–C–E–G–H–I–J–K. The project can be completed with a duration of 11 weeks and costs Rp 1,488,737,722.90

Setiap bulan BPS mempublikasikan buku LBDSE Indonesia, dimana di dalam publikasi tersebut berisi perkembangan dari 18 topik data beserta visualisasinya. Namun, visualisasi data pada publikasi LBDSE tidak lengkap dan hanya bersifat statis, sedangkan data yang ada memiliki dimensi/variabel yang cukup besar. Sehingga peneliti berfikir untuk mengimplementasikan visualisasi data interaktif publikasi LBDSE pada SIVIS LBDSE agar memudahkan dalam memahami data-data nya. Untuk menilai keberhasilan tujuan pengimplementasian tersebut, peneliti akan melakukan evaluasi terhadap visualisasi data pada SIVIS LBDSE berdasarkan penilaian pengguna menggunakan 8 indikator penilaian yang diadopsi dari penelitian terdahulu. Tujuan penelitian ini yaitu untuk mengimplementasikan visualisasi data interaktif pada data LBDSE, mengevaluasi visualisasi data pada SIVIS LBDSE, serta mengetahui visualisasi data terbaik terhadap data kategorik publikasi LBDSE. Dengan bantuan 50 responden, mereka menilai bahwa visualisasi data pada SIVIS LBDSE memiliki keunggulan dan kekurangannya masing-masing berdasarkan 8 indikator penilaian yang digunakan. Namun secara keseluruhan responden mengurutkan visualisasi data terbaik untuk data kategorik secara berturut-turut yaitu, Bar Chart, Tree Map, Bubble Map, dan Pie Chart.

We present a system to visualize multiple time-dependent scalar fields defined on 3D surfaces as they arise from numerical simulations. Domain experts want to understand correlations between multiple scalar fields to verify underlying processes. However, existing visualization techniques require high exploration effort to perceive temporal changes and relations of multiple fields on 3D surfaces. This makes analysis time-consuming and carries a high risk of overlooking regions with specific correlations. Therefore, we introduce a novel concept to facilitate exploration of multiple time-dependent scalar fields simultaneously. The basic idea is to use a novel glyph-based depiction, called skyline visualization, which is inspired by the skyscraper metaphor from information visualization. The skyscrapers are represented by 2D and 3D bar charts, where their floors show the temporal behavior of scalar fields of the corresponding surface region. The user can interact with the skyline visualization to see at which surface areas the scalar fields take on striking values or whether correlations exist between them. Furthermore, the user can immediately see in which regions scalar fields change strongly over time or show strongly inverted behavior. We evaluated our system with several CFD engineers, radiologists and visualization experts. Compared to existing systems, they were able to find regions of interest quickly and with high accuracy.

Objective The purpose of this study was to evaluate the usability of a top-rated diabetes app. Such apps are intended to markedly support the achievement of optimal health and financial outcomes by providing patients with substantive and continual support for self-management of their disease between periodic clinician visits. Poor usability can deter use which is especially concerning in patients with diabetes due to prevalence of the disease and impact of self-management on long-term prognosis. Methods A diabetes app was selected due to the prevalence and seriousness of the disease. A heuristic evaluation was then performed to collect and analyze data on the usability of the app based on Nielsen's heuristics. Pareto analysis was used to illustrate the contribution of each type of heuristic violation, augmented by a stacked bar chart illuminating associated severity. Results There were 51 heuristic violations on the opening screen, violating 6 of Nielsen's 10 heuristics. Pareto analysis revealed 29 (57%) of the heuristic violations involved a match between system and real world and 8 (16%) aesthetic and minimalist design. Severity ratings ranged from 1.0 to 4.0 (mean: 3.01) with 80% comprising a major usability problem and 6% a usability catastrophe. Conclusion Studies show that people with diabetes are more likely to receive greater benefit from a diabetes app if they are easy to use. The number and severity of heuristic violations in this study suggest that the commercialization of mobile health apps may play a factor in bypassing experts in clinical informatics during the design phase of development. Usability and associated benefits received from mobile health apps can be enhanced by debugging the user interface of identified heuristic violations during design. Waiting to correct ongoing usability issues while apps are in production can result in patients disengaging from use of digital health tools engendering poorer outcomes.

Background Little is known about how physicians interpret data displays that depict preliminary or exploratory clinical data in physician-targeted sales aids for oncology drugs. Using three factorial experiments, we examined whether disclosures of data limitations and clinical uncertainty adequately communicate the limitations and practical utility of this type of data. Subjects, Materials, and Methods The studies used a 2 (disclosure of data limitations: technical, nontechnical) × 2 (disclosure of clinical uncertainty: present, absent) + 1 (control: no disclosure) between-subjects experimental design to examine the impact of disclosures as they relate to presentations of preliminary or exploratory data in promotional communications for oncology products. In each experiment, we randomized oncologists and primary care physicians with oncology experience to view one version of a two-page sales aid. Following this exposure, physicians completed a web-based survey. The design was replicated in three concurrently conducted experiments using sales aids for different fictitious oncology drugs, each featuring one of three common data displays: a forest plot (n = 495), a Kaplan-Meier curve (n = 504), or a bar chart (n = 532). Results Results provide initial evidence that in some contexts disclosures can improve understanding of the clinical utility of certain information about a drug and the limitations of results presented in a data display. Disclosures can also temper perceptions of how much evidence is presented that supports a conclusion that the drug is an appropriate treatment. In terms of the language used in the disclosure of data limitations, physicians in all three experiments strongly preferred the nontechnical disclosures. Conclusion The findings from the three experiments in this study suggest that disclosures have the potential to increase relevant knowledge, but more research is needed to establish best practice recommendations for using disclosures to convey contextual information relevant for interpreting data displays in promotional communications. Implications for Practice This article reports the results from three large, online experimental studies that address a growing concern that drug companies often share favorable clinical trial results with physicians in promotional materials that lack important context for physicians to interpret the data. This series of studies investigates whether strategic use of two types of disclosures (disclosure of data limitations and a disclosure of clinical uncertainty) improves understanding and reduces misinterpretations among physicians. The results from these studies help identify communication factors that impact how physicians critically appraise preliminary or exploratory clinical trial data to inform policy and regulatory efforts.

Visualizations have the potential to be a powerful means of communication, especially for quantitative data, helping managers to see significant patterns and deviations. To be effective, visuals need to be appropriate for the task and properly designed. Most organizations tend to limit themselves to a small repertoire of rather simplistic graphs and charts. More expressive and intuitive representations can be deployed to provide both useful and engaging formats. This article presents a new composite form of visualization that has been designed to better convey research and development budget and expenditure figures to senior executives. In addition to providing a summary overview of the data, this functionally designed visualization offers a means to structure discussions in management meetings and provoke examination of what the data means in terms of financial allocations, top budget holders, requested funds, potential shortfalls, and weak/strong performing areas. The visualization deploys a combination of Sankey flow streams, mini pie charts, technology readiness levels, bar charts, annotated tick-marks, and graphic equalizer-style tally bars. Using a real-world dataset, an illustrative example is provided. This novel combination of visual objects provides an exemplar, which other organizations can adapt and apply, to support funding reviews and investment decision-making.

This article is an excerpt from a master’s research that aimed to investigate the learning of students in the 5th grade of elementary school in relation to understanding the construction of graphs from tables with or without the aid of Excel software. In this article, we are interested in analysing the students’ learning from the sequence of activities developed in two days of intervention with the aid of the Excel software. Two classes of public schools in the municipality of Paulista, in Pernambuco, Brazil, participated in this study involving an initial diagnosis, an intervention and a post-test regarding the understanding of representations in single and double entry tables with subsequent registration in bar graphs. The results showed that the Excel software, besides motivating, allowed contents to be worked in a more interactive way, allowing a rich discussion about different units of the scales, and highlighting the need to explain all the elements that make up the information of a table or a graph. This software presented itself as feasible to be worked with 5th grade students, promoting new pedagogical experiences for them in the elementary school about the understanding of different statistical skills by students.

In today’s digital era, the importance of digital marketing has increased from one year to another as a way of providing novel properties for informing, engaging, and selling services and products to clients. The research’s aim is to investigate trends and patterns in the area of digital marketing research from 1979 to June 2020 through a bibliometric analysis technique. A total of 924 articles published were obtained from the Scopus database for the analysis. In this paper, we examine variant bar charts including the year of publication, writer, publication, keyword, and country to provide more insights. Results indicated that digital marketing research steadily increased during the study period and the maximum publications occurred in the year 2019 that reach to 163 documents. The trend of publications is still growing. The top 20 documents based on the times cited per year (TCpY) were qualitatively analyzed. The largest number of multiple (MCP) and single (SCP) publications was from the USA, followed by the UK and China. The top 20 most repeated authors’ keywords out of 1909 with their trends illustrated. The “real-time bidding”, “machine learning”, “big data”, “social media marketing”, and “influencer marketing” are the emerging keywords in the digital Marketing area. This bibliometric study generally provides the whole image of the field and suggests that researchers focus on novel areas to add new findings and knowledge in the literature if they conduct digital marketing research.

Women are highly underrepresented in the construction industry. In line with the sustainable development goals (SDGs) of the United Nations of gender quality and reducing inequalities, there is a need to think of innovative and sustainable frameworks to increase women's quota in the construction trade, especially in architecture. The study investigated the mentor-mentee relationship between female Architects and female Architectural students. The study utilized a research survey approach using a questionnaire data instrument. Using a purposive sampling technique, 84 research participants, consisting of female Architects and female Architecture students, participated in this study. The data collected are presented using bar charts, mean scores, principal component analysis (PCA), and categorical regression (CAT-REG). The study identified characteristics associated with good Mentors and good Mentees in the design profession. Mentees identified the main features that make a good mentor as the ability to teach, listen attentively, and communicate effectively. On the other hand, Mentors identified the qualities of a good mentee who communicates, is focused and demonstrates intelligence. The study showed that the significant negative experiences in a mentor-mentee relationship include a clash of personalities between the mentors and mentees, stealing credit for work done by both parties, and unrealistic expectations. Furthermore, these negative experiences result from poor attitude, wrong emotions, and loss of motivation. In conclusion, the study showed that proper implementation of Women mentoring programs among design professionals could lead to potential outcomes such as improved productivity, empowerment of inexperienced personnel, attracting likely female students, retaining women professionals, higher salaries, higher job satisfaction, and an increase in role models/mentors.

Almajiri is an education system practiced in northern Nigeria whereby Almajiri pupils are only exposed to Quranic learning. For these pupils to become relevant and valuable in this modern society, the Federal Government of Nigeria formulated a formalizing their Almajiri education system and integrated Western education without jeopardizing Quranic learning. To find out if Almajiri education is not being negatively affected because of the policy, this study assessed Almajiri Integrated School Pupils' performance in Quranic subjects in Sokoto State, Nigeria. The research method employed was a descriptive survey. Using the purposive sampling technique, four schools (2 urban and 2 rural schools) where the needed data were readily available were sampled. Two hundred seventy-three (273) subjects (94 from urban and 179 from rural areas) were purposively tested for the study. Pro-forma was designed as a research instrument and collected the 2013/2014 primary 3 Promotional Examination Results. The Percentage, Mean and Standard deviation, Bar Chart, and t-test statistical tools were used for data analysis. The study revealed, among others, that the general performance of Almajiri Integrated Model School pupils in the Qur'anic subjects was below average. The paper concluded an urgent need to empirically explore factors responsible for the low performance to improve it.

This research is a quantitative descriptive research. The method used is the method of analysis. The subjects of this study were 24 SSB Abhiseva U-16 players in Bengkulu City. The instrument used was the Bleep Test. The analysis technique used is to pour the frequency into the form of a bar chart. The results of this study indicate that the level of endurance of SSB Abhiseva Kandang Limun players in Bengkulu City is very low considering the highest frequency with very low category with 18 people or 75%. Analysis of the Physical Endurance of football players at SSB Abhiseva Kandang Limun in Bengkulu City which is categorized as very good 0 people or 0%, either 0 people or 0%, moderate 0 people or 0%, less 6 people or 25%, less 18 people or 75 %.

PurposeThis purpose of the study is to evaluate areas of application of internet of things (IoT) in the construction industry, with the view of increasing the level of usage of technology. This will help in understanding the areas where IoT can be applied in the construction industry for better improvement.Design/methodology/approachA quantitative approach was adopted for this study, and the adopted questionnaire was structured on a five-point Likert scale to elicit the opinion of respondents in the areas of application of IoT in the construction industry. The respondents included are quantity surveyors, land surveyors, builders, architects and engineers. Bar chart, mean item score, one sample t-test and Kruskal–Wallis H test were used in analyzing the retrieved data.FindingsThe results showed that building information modeling, construction management, remote usage monitoring, equipment services and repair, construction tools and equipment tracking are areas where IoT is mostly applied in the industry. Site monitoring is the only factor that has significant difference in the opinions of professionals, while others do not have. One sample t-test revealed that three factors out of 12 do not have significance attached by professionals.Originality/valueThe study gives insight into different areas where IoT can be applied in the construction industry. It also highlights how its application can be improved through workshops, training, seminar and conference for construction professionals to keep themselves abreast of information and communication technology trends, especially in the aspect of IoT. The IoT adoption helps in accomplishing sustainable infrastructural projects with more convenience.

Data visualizations and graphs are increasingly common in both scientific and mass media settings. While graphs are useful tools for communicating patterns in data, they also have the potential to mislead viewers. In five studies, we provide empirical evidence that y-axis truncation leads viewers to perceive illustrated differences as larger (i.e., a truncation effect). This effect persisted after viewers were taught about the effects of y-axis truncation and was robust across participants, with 83.5% of participants across these 5 studies showing a truncation effect. We also found that individual differences in graph literacy failed to predict the size of individuals’ truncation effects. PhD students in both quantitative fields and the humanities were susceptible to the truncation effect, but quantitative PhD students were slightly more resistant when no warning about truncated axes was provided. We discuss the implications of these results for the underlying mechanisms and make practical recommendations for training critical consumers and creators of graphs.

Stasiun Geofisika Kepahiang merupakan unit perwakilan BMKG yang berada di wilayah Kabupaten Kepahiang Bengkulu. Dalam menjalankan tugasnya diperlukan aplikasi pengolahan data meteorologi dan geofisika yang cepat, efektif dan efisien. Penelitian ini bertujuan untuk mengembangkan aplikasi pengolahan data meteorologi dan geofisika. Pengolahan ini terkait dengan parameter statistik data meteorologi dan geofisika yang ditampilkan dalam grafik. Aplikasi ini dapat menghasilkan keluaran berupa 13 grafik dan 2 peta. Grafik yang dihasilkan adalah grafik suhu rata-rata, suhu maksimum dan minimum, kelembaban, curah hujan, durasi penyinaran matahari, gempa yang tercatat, gempa bumi berdasarkan magnitudo (diagram batang dan lingkaran), gempa berdasarkan kedalaman (diagram batang dan lingkaran), gempa dirasakan, gempa berbasis sumber, RMS gempa, peta seismisitas dan peta seismisitas serta penampang melintangnya. Waktu pemrosesan sekitar 3 - 5 menit. Waktu proses dengan aplikasi ini lebih cepat jika dibandingkan dengan software Microsoft Excel dan software ArcGis.

International audience; Expressive design environments enable visualization designers not only to specify chart types and visual mappings, but also to customize individual graphical marks, as they would in a vector graphics drawing tool. Prior work has mainly investigated how to support the expressive design of a wide range of charts generated from tabular data: bar charts, scatterplots, maps, etc. We focus here on an expressive design environment for node-link diagrams generated from multivariate networks. Such data structures raise specific challenges and opportunities in terms of visual design and interactive authoring. We discuss those specificities and describe the user-centered design process that led to Graphies, a prototype environment for expressive node-link diagram authoring. We then report on a study in which participants successfully reproduced several expressive designs, and created their own designs as well.

Objective This study examined the perspectives on the use of data visualizations and identified key features seriously ill children, their parents, and clinicians prefer to see when visualizing symptom data obtained from mobile health technologies (an Apple Watch and smartphone symptom app). Materials and Methods Children with serious illness and their parents were enrolled into a symptom monitoring study then a subset was interviewed for this study. A study team member created symptom data visualizations using the pediatric participant’s mobile technology data. Semi-structured interviews were conducted with a convenience sample of participants (n = 14 children; n = 14 parents). In addition, a convenience sample of clinicians (n = 30) completed surveys. Pediatric and parent participants shared their preferences and perspectives on the symptom visualizations. Results We identified 3 themes from the pediatric and parent participant interviews: increased symptom awareness, communication, and interpretability of the symptom visualizations. Clinicians preferred pie charts and simple bar charts for their ease of interpretation and ability to be used as communication tools. Most clinicians would prefer to see symptom visualizations in the electronic health record. Discussion Mobile health tools offer a unique opportunity to obtain patient-generated health data. Effective, concise symptom visualizations can be used to synthesize key clinical information to inform clinical decisions and promote patient-clinician communication to enhance symptom management. Conclusions Effectively visualizing complex mobile health data can enhance understanding of symptom dynamics and promote patient-clinician communication, leading to tailored personalized symptom management strategies.

Background In the United States, all 50 state governments deployed publicly viewable dashboards regarding the novel coronavirus disease 2019 (COVID-19) to track and respond to the pandemic. States dashboards, however, reflect idiosyncratic design practices based on their content, function, and visual design and platform. There has been little guidance for what state dashboards should look like or contain, leading to significant variation.Objectives The primary objective of our study was to catalog how information, system function, and user interface were deployed across the COVID-19 state dashboards. Our secondary objective was to group and characterize the dashboards based on the information we collected using clustering analysis.Methods For preliminary data collection, we developed a framework to first analyze two dashboards as a group and reach agreement on coding. We subsequently doubled coded the remaining 48 dashboards using the framework and reviewed the coding to reach total consensus.Results All state dashboards included maps and graphs, most frequently line charts, bar charts, and histograms. The most represented metrics were total deaths, total cases, new cases, laboratory tests, and hospitalization. Decisions on how metrics were aggregated and stratified greatly varied across dashboards. Overall, the dashboards were very interactive with 96% having at least some functionality including tooltips, zooming, or exporting capabilities. For visual design and platform, we noted that the software was dominated by a few major organizations. Our cluster analysis yielded a six-cluster solution, and each cluster provided additional insights about how groups of states engaged in specific practices in dashboard design.Conclusion Our study indicates that states engaged in dashboard practices that generally aligned with many of the goals set forth by the Centers for Disease Control and Prevention, Essential Public Health Services. We highlight areas where states fall short of these expectations and provide specific design recommendations to address these gaps.

Differential Privacy is an emerging privacy model with increasing popularity in many domains. It functions by adding carefully calibrated noise to data that blurs information about individuals while preserving overall statistics about the population. Theoretically, it is possible to produce robust privacy-preserving visualizations by plotting differentially private data. However, noise-induced data perturbations can alter visual patterns and impact the utility of a private visualization. We still know little about the challenges and opportunities for visual data exploration and analysis using private visualizations. As a first step towards filling this gap, we conducted a crowdsourced experiment, measuring participants' performance under three levels of privacy (high, low, non-private) for combinations of eight analysis tasks and four visualization types (bar chart, pie chart, line chart, scatter plot). Our findings show that for participants' accuracy for summary tasks (e.g., find clusters in data) was higher that value tasks (e.g., retrieve a certain value). We also found that under DP, pie chart and line chart offer similar or better accuracy than bar chart. In this work, we contribute the results of our empirical study, investigating the task-based effectiveness of basic private visualizations, a dichotomous model for defining and measuring user success in performing visual analysis tasks under DP, and a set of distribution metrics for tuning the injection to improve the utility of private visualizations.