derhan/semantic-scholar-manajemen-proyek huggingface dataset:
An open source primer
Year: 2007

Design projects come in all sizes. Many interaction designers have responsibility for a part of a larger application; many have sole responsibility for the overall experience of an application; and many have responsibility for the care and nurturing of a user experience, where others are free to chime in and change things. This last point reflects the nature of open source: You never know what someone will think up next, or how someone may change what you have already done. Working successfully as a designer in an open source project means a huge amount of freedom and a lot of homework. You can do almost anything the technology will permit, because that's the point: It's an open and collaborative environment, where anyone can make a contribution. But it's not without rules, and that's where the homework comes in. For designers, it's imperative to understand where the flexibility lies and where the rules apply. The articles in this section address project management, licensing options, and some of the community issues around open source software from experts working in this field. We also have a case study from the OpenOffice project and a technical introduction to SMIL, an open format for interactivity. We extend our sincere thanks to all of our contributors, and we hope you enjoy this exploration into open source.
A Conceptual Approach to Improve the Continuity and Integrity of Information in Project Management
Authors: Marcello Presulli
Year: 2016

This article proposes a conceptual implementation by means of a suitable framework to improve the continuity and integrity of information in project management. It is argued that this methodology offers a comprehensive benefit in terms of a holistic project management. The benefit characterizes itself mainly by a focused representation of project sections in dependence of the desired detail degree, as well as the base of information restorable any time on the basis of the origin production data. It takes advantage of a collaborative act to declare the necessities like keywords and conventions in advance, which has the main purpose to avoid semantic misinterpretation between users and the accepted model of approach. The concept of this scheme offers generally a high flexibility with only few dependencies-hence it's easy to extend the framework on consensual agreed pragmatics. Furthermore, it is shown that in practice there is a loose coupling to the underlying host system, which promotes the exchange of other systems. Since the framework payload is based on pure keyword mechanisms with expandable notation, a high degree of user-driven specialization is offered. Finally, the keyword pragmatic is explained on four keywords which have been agreed by a collaborative collection with selected industry partners and represent on behalf a possible application to a software Repository.
Identifying Critical Tasks in the Kadiri University 4 Floor Building Construction Project Using the Critical Path Method
Authors: Mahardi Kamalika Khusna Ali; H. T. Tjendani; Budi Witjaksana
Year: 2024

This study aims to identify critical tasks in the construction of a 4-floor building at Kadiri University using the Critical Path Method (CPM). The project is planned to be completed within 43 weeks, from October 2023 to August 2024, with a budget of IDR 20,551,534,000. Data collection involved direct site visits for primary data and secondary data from project documentation, including the Cost Budget Plan (RAB) and project schedule. Using Microsoft Project software, a project network was mapped, and CPM analysis was performed to identify the critical path. The analysis revealed that several tasks, such as site cleaning, demolition, temporary project fencing, heavy equipment work, geotechnical work, and various structural works from the 1st to the 5th floors, are on the critical path. These tasks have zero slack time, indicating that any delays will directly impact the overall project timeline. Identifying the critical path is crucial for project managers to prioritize resources and efforts on these tasks to ensure the project stays on schedule. This study underscores the significance of CPM in project management for timely completion and effective resource allocation, providing valuable insights for managing similar construction projects.
A case study of exploiting enterprise resource planning requirements
Authors: Nan Niu; Mingzhou Jin; Jing-Ru C. Cheng
Year: 2011

The requirements engineering (RE) processes have become a key to conceptualising corporate-wide integrated solutions based on packaged enterprise resource planning (ERP) software. The RE literature has mainly focused on procuring the most suitable ERP package. Little is known about how an organisation exploits the chosen ERP RE model to frame the business application development. This article reports an exploratory case study of a key tenet of ERP RE adoption, namely that aligning business applications to the packaged RE model leads to integral practices and economic development. The case study analysed a series interrelated pilot projects developed for a business division of a large IT manufacturing and service company, using Oracle's appl1ication implementation method (AIM). The study indicated that AIM RE improved team collaboration and project management experience, but needed to make hidden assumptions explicit to support data visibility and integrity. Our study can direct researchers towards rigorous empirical evaluations of ERP RE adoption, collect experiences and lessons learned for practitioners, and help generate more effective and mature processes when exploiting ERP RE methods.
Warner Robins Air Logistics Center Streamlines Aircraft Repair and Overhaul
Authors: M. Srinivasan; W. D. Best; S. Chandrasekaran
Year: 2007

At Warner Robins Air Logistics Center, long lead times for repairing and overhauling aircraft were a serious issue because some models were in short supply. In 2005, the center implemented Critical Chain, an operations research method for project management, to reduce lead time for repairing its C-5 transport aircraft. The implementation took eight months, without using any additional resources. The center returned five additional C-5 aircraft to the US Air Force's operational inventory and generated additional revenue to the Transportation Working Capital Fund estimated at $49.8 million annually. The replacement value for these aircraft is estimated at $2.37 billion. The center is implementing the method for the C-130 and the C-17 cargo aircraft to free up 11 dock spaces. With the additional dock space, the depot can accommodate additional work worth $65 million in 2006. The center expects the additional workload to total $248 million by 2009 (the current C-5 annual operating budget is $295 million). Nonquantifiable benefits include increased responsiveness and casualty avoidance during wartime.
DevEventTracker: Tracking Development Events to Assess Incremental Development and Procrastination
Authors: Ayaan M. Kazerouni; Stephen H. Edwards; T. Simin Hall; Clifford A. Shaffer
Year: 2017

Good project management practices are hard to teach, and hard for novices to learn. Procrastination and bad project management practice occur frequently, and may interfere with successfully completing major programming projects in mid-level programming courses. Students often see these as abstract concepts that do not need to be actively applied in practice. Changing student behavior requires changing how this material is taught, and more importantly, changing how learning and practice are assessed. To provide proper assessment, we need to collect detailed data about how each student conducts their project development as they work on solutions. We present DevEventTracker, a system that continuously collects data from the Eclipse IDE as students program, giving us in-depth insight into students' programming habits. We report on data collected using DevEventTracker over the course of four programming projects involving 370 students in five sections of a Data Structures and Algorithms course over two semesters. These data support a new measure for how well students apply "incremental development" practices. We present a detailed description of the system, our methodology, and an initial evaluation of our ability to accurately assess incremental development on the part of the students. The goal is to help students improve their programming habits, with an emphasis on incremental development and time management.
How to conduct successful business process automation projects? An analysis of key factors in the context of robotic process automation
Authors: Dennis Schlegel; Bernhard Rosenberg; Oliver Fundanovic; Patrick Kraus
Year: 2024

PurposeIn recent years, the robotic process automation (RPA) technology, a software-based method to automate routine tasks in business processes, has gained significant interest and adoption. However, many implementation projects fail and current literature lacks a synthesis and comprehensive overview of factors that challenge the implementation of RPA, have an impact on success or failure of projects, or, play an enabling role in an RPA project. Hence, the purpose of this research is to identify key factors that should be considered by organizations when conducting an RPA project.Design/methodology/approachThe paper adopts a qualitative methodology based on data collected in a systematic literature review (SLR) and interviews with 10 RPA experts. Using inductive coding, an integrated framework of key factors is developed.FindingsThe results suggest that the key factors for a successful RPA introduction can be divided into human, organizational and technical factors. Important aspects include for example project management techniques, capabilities and skills of employees, as well as data security considerations.Originality/valueThe paper contributes to knowledge by synthesizing previously dispersed knowledge into an integrated framework, as well as by complementing previous results with new qualitative, empirical data. Additionally, the RPA-specific factors are put into the perspective of persistent problems in information systems development.
Predicting Issue Resolution Time of OSS Using Multiple Features
Authors: Yu Qiao; Xiangfei Lu; Chong Wang; Jian Wang; Wei Tang; Bing Li
Year: 2024

Developers utilize issue tracking systems to track ideas, feedback, tasks, and bugs for projects in the open‐source software ecosystem of GitHub. In this context, extensive bug reports and feature requests are raised as issues that need to be resolved. This makes issue resolution prediction become more and more important in project management. To address this problem, this paper constructed a multiple feature set from the perspectives of project, issue, and developer, by combining static and dynamic features of issues. Then, we refine a feature set based on the feature's importance. Furthermore, we proposed a method to explore what features and how these features affect the prediction of issue resolution time. Experiments are conducted on a dataset of 46,735 resolved issues from 18 popular GitHub projects to validate the effectiveness of the refined feature set. The results show that our prediction method outperforms the baseline methods.
The Use of Project Management Tools to Support the Coordination of Collaborative Learning
Authors: Marcelo Augusto Rauh Schmitt; L. Tarouco
Year: 2018

Coordination plays a fundamental role in collaborative learning. When collaboration is supported by computers, automatic coordination mechanisms must be deployed. This paper aims to study the possibility of transfering project management tools commonly used in work contexts to learning contexts. We propose a coordination model that makes the change of area feasible, and that favours learner’s autonomy. Two case studies were carried out and a new tool was built in order to test the hypothesis. The results of the current research suggest that project management tools are viable alternatives to automatic coordination support, as long as they are used under a proper paradigm.
Modeling Long- and Short-Term Project Relationships for Project Management Systems
Authors: Yongqiao Zhang; Guangyu Bai; Zhanchao Gao; Pengyuan Zhu; Shiwen Li
Year: 2024

In modern power grid project management, project management systems have become indispensable. However, the intricate and mutable nature of relationships among power grid projects presents significant challenges to accurate modeling using traditional approaches. To tackle this problem, we propose a sequential management model that consolidates long-term and short-term potential relationships between power grid projects, aiming to enhance the efficiency of the project management system. Specifically, we develop a project relationship network, which leverages graph convolutional neural networks and attention mechanisms to dynamically capture and integrate project relationship information. This innovative method enables a more refined representation of inter-project relationships within the power grid domain. Furthermore, to account for temporal shifts in project execution, we devise a method incorporating project temporal information to predict project progress. The method employs separate modules for long-term and short-term project execution, allowing us to distinguish between enduring and immediate impacts among power grid projects, thereby enriching the portrayal of project relationships. Experiments on public recommendation system datasets validate the efficacy of our proposed method in the context of power grid project management.
Application of GAN to Resolution Enhancement of LWD Real-Time Image Logs to Support Decision Making
Authors: W. Trevizan; Candida Menezes de Jesus
Year: 2023

In the current scenario of project management, where the agility and optimization of operations have been prioritized, the practice of logging while drilling (LWD) has gained space compared to traditional wireline logging. In theory, acquiring quality petrophysical properties during drilling brings greater agility in decision making about completion and optimizes operation costs. However, regarding borehole image logs, due to limitations in transmission capacity, the actual available data in real time contain about 50% (for resistivity images) of the full azimuth information, being insufficient for the identification of critical geological structures capable of impacting the communication between production or injection zones or the quality of cementation, such as fractures, caves, and geomechanical collapse zones. The tool’s memory data with the full information may take a few days after the end of drilling to be delivered by the service company, which in some cases is not enough for fast decision making regarding completion. In this work, we tested models based on generative adversarial neural networks (GANs) to reconstruct the complete memory data based on real-time input. As in conventional GAN schemes, a generator is trained to receive a real-time input and create a “memory-like” image, while a discriminator is trained to tell real and fake images apart. To regularize the convergence of training, we used an architecture known in the literature as CycleGAN, where another generator-discriminator pair is trained simultaneously to do the reverse process, recreating the real-time data. Variations of the training process and data sets were used to generate different CycleGAN models. They were trained using logs of presalt reservoirs in Buzios Field, and performance was assessed on logging intervals not seen by the algorithms during training. The results achieved so far have been very promising, as in certain intervals, resultant models were able to capture the presence of fractures and caves. This methodology represents a way of circumventing telemetry limitations, where missing information is added indirectly to the real-time data as the artificial intelligence (AI) algorithm learns the main characteristics of a field/reservoir. Therefore, previous knowledge from the field can be used to continuously optimize future operations, efficiently incorporating the available database into the workflow of petrophysicists for the recognition of geological and geomechanical structures in time to support decision making in completion operations.
A Theoretical Validation of Component Point
Authors: T. Wijayasiriwardhane; R. Lai
Year: 2019

The system-level size measures are important in software project management as tasks such as planning and estimating the cost and schedule of software development can be performed more accurately when a size estimate of the entire system is available. However, due to the black-box nature of software components, traditional software measures are not adequate for Component-Based Systems (CBS). We have developed a Function Point (FP) like measure, named Component Point (CP), for measuring the system-level size of a CBS specified in Unified Modeling Language. In this paper, we present a theoretical validation of the CP measure using mathematics and show that not only the CP measure holds all the mathematical conditions necessary for a size measure, but it can also be used in Component-Based Software Development (CBSD) in a similar way that FP and its extensions are used in other software development paradigms.
SCIENTIFIC PROJECT TEAMS MANAGEMENT IN WARTIME REALITIES: PERSONNEL SECURITY ENSURING ASPECTS
Authors: N. Zachosova
Year: 2024

The study is devoted to the scientific project teams management in the realities of wartime and personnel security ensuring aspects. The purpose of the work was to identify features that should be taken into account by personnel management and scientific and pedagogical personnel who are heads of scientific projects during the management of project teams engaged in research work under the influence of wartime risks. The research methodology means the use of content analysis and specialized literature processing, as well as taking expert opinion on modern features of scientific project management into account. As a result of the study, features were identified that should be taken into account by managers and scientific and pedagogical staff , including heads of scientific projects, when managing project teams mission is to provide research work under the influence of wartime risks; the characteristic features of the scientific projects management in comparison with applied research were investigated; the peculiarities of the scientific project team formation are determined, personnel risks accompanying the process of implementing a scientific project both in peacetime and in wartime are determined, and proposals are made for optimizing the management of scientific projects in the realities of wartime. The peculiarities of the scientific project team formation have been established, which include: the need for a team member to belong to the work team of a scientific institution or institution of higher education, the team members' compliance with the characteristics of active researchers, their availability of professional publications on the topic of the project; search for people with scientific degrees and scientific titles and united by common scientific interests. The field of application of research results is science management, project management, flexible management and team management in scientific and educational institutions, critical infrastructure enterprises and business structures.
Experiences with managing student software projects using the internet
Authors: E. Rodgers
Year: 2005

Declining funding sources for courseware creates problems for providing adequate technology in the classroom for many institutions [1], [3]. In addition, the changing nature of the student population and the increased use of distance learning courses require new approaches to course delivery and control [7]. The use of the Internet as a project management environment provides the potential to solve some of the problems with existing methods for managing software projects. This paper describes experiences in the use of readily available Web-based technologies as an effective and economical alternative to a commercial, network-based project management environment to manage software and other computer-related projects in an educational setting.
Analisis Teori Pengambilan Keputusan Berbasis Risiko dalam Manajemen Proyek
Authors: Damara Altaf Alawdin; Reghina Rahma Kamila; Muhammad Wildan Khasanu; R. Hidayat N; I. Kusumasari
Year: 2024

Penelitian ini bertujuan untuk mengeksplorasi teori pengambilan keputusan berbasis risiko serta aplikasinya dalam lingkungan manajemen proyek. Pendekatan yang digunakan adalah studi literatur dan analisis data sekunder yang relevan dengan proses pengambilan keputusan strategis. Hasil penelitian menunjukkan bahwa pendekatan berbasis risiko meningkatkan efektivitas keputusan melalui identifikasi proaktif, evaluasi probabilitas dan dampak risiko, serta pengembangan strategi mitigasi. Selain itu, penggunaan alat bantu seperti matriks risiko dan perangkat lunak manajemen risiko terbukti mempercepat pengambilan keputusan yang berbasis data. Penelitian ini menyimpulkan bahwa teori pengambilan keputusan berbasis risiko tidak hanya mendukung keberhasilan proyek tetapi juga memberikan kerangka kerja yang sistematis untuk meningkatkan efisiensi operasional. Bahkan dalam situasi sulit, manajer proyek dapat membuat keputusan yang lebih tepat waktu dan akurat dengan memahami ancaman dan peluang yang tersedia. Penelitian ini juga menekankan betapa pentingnya komunikasi tim dalam proses pengelolaan risiko, di mana setiap anggota tim dilibatkan untuk memberikan saran yang akan membantu memperbaiki analisis risiko secara kolektif. Teori pengambilan keputusan berbasis risiko meningkatkan keberhasilan proyek dengan mengurangi kemungkinan kegagalan dan meningkatkan efisiensi operasi dengan proses yang lebih terstruktur. Implikasi dari penelitian ini diharapkan dapat menjadi panduan praktis bagi manajer proyek dalam menghadapi tantangan kompleks dalam pengelolaan risiko proyek di tengah keadaan yang semakin kompleks dan tidak menentu dalam lingkungan bisnis. Pada akhirnya, metode ini dapat membantu perusahaan membuat strategi manajemen proyek yang lebih fleksibel dan kuat untuk mengatasi berbagai masalah.
Using Machine Learning to Predict Cost Overruns in Construction Projects
Authors: Theingi Aung; Sui Reng Liana; Arkar Htet; Amiya Bhaumik
Year: 2023

Addressing the persistent issue of cost overruns in construction projects, our study explores the potential of machine learning algorithms for accurately predicting these overruns, utilizing an expansive set of project parameters. We draw a comparison between these innovative techniques and traditional cost estimation methods, unveiling the superior predictive accuracy of machine learning approaches. This research contributes to existing literature by presenting a data-driven, reliable strategy for anticipating and managing construction costs. Our findings have significant implications for project management, offering a path towards more efficient and financially sound practices in the construction industry. The improved prediction capabilities could revolutionize cost management, facilitating better planning, risk mitigation, and stakeholder satisfaction.