Verification Approach Research Articles

The Influence of Work Motivation, Work Environment and Job Satisfaction on Employee Performance at CV Lanupi Bandung

Employee performance is an assessment of work results, and the quality of thinking, behavior and achievements of individuals or teams in achieving organizational goals. This is important to determine the effectiveness and performance of the organization to determine the quality, efficiency and performance of the work carried out by each employee, as well as providing feedback and direction that can improve their performance. Employee performance can be influenced by several factors including, Work Motivation, Work Environment and Job Satisfaction on Employee Performance, The research method used is a quantitative research method with a descriptive and verification approach. The sample in this study was a total sample with a total of 30 respondents. In this study the entire population was sampled, so it is said to be a saturated sample.The research results show that work motivation, work environment and job satisfaction influence employee performance partially or simultaneously with a coefficient of determination test value of 0.753 or 75% so it can be interpreted that 75% of CV. Lanupi (Y) employee performance can be explained by variables work motivation (X1), work environment (X2), and job satisfaction (X3).The research results show that: (1). Employee performance is in the poor category (2). Work Motivation is in the poor category (3) Work Environment is in the poor category (4). Job satisfaction is in the poor category (5). Partial research results show that work motivation influences employee performance (6).

Influence Of Transformational Leadership And Work Motivation On Employee Performance

This research is motivated by the significant competition between construction service providers in the Civil Water sector. This research was carried out in Bandung to learn about and analyze transformational leadership and communication on employee performance in one of the companies operating in Bandung's architectural, civil, mechanical, electrical, and environmental management consulting services. Employee performance generally focuses on transformational leadership and communication. The research method used is quantitative, with a descriptive and verification approach. The sample used was 100 employees at a company engaged in architectural, civil, mechanical, electrical, and environmental management services in Bandung. The research results show valid results for each statement item with a value of 0.3, and reliable results show a value above 0.7. For transformational leadership, (X1) is 0.784, Communication (X2) is 0.789, and Employee Performance (Y) is 0.780. From the value (R Square), it is known that the influence of transformational leadership (X1) and communication (X2) on employee performance (Y) is 0.810 or 81.0%. Leadership (X1), Communication (X2), and Employee Performance (Y) are in the relatively good category. The direct influence of transformational leadership (X1) is 13.3%. The direct influence of Communication (X2) is 32.1%. Employee performance is influenced by transformational leadership and communication by 81.0%, while the remaining 19.0% is caused by other variables or other factors that were not researched. From the research results above, it can be concluded that transformational leadership and communication significantly influence employee performance in one of the companies operating in the architectural, civil, mechanical, electrical, and environmental management consulting services in Bandung. The practical implications of these findings are that professionals in this field can enhance employee performance by adopting transformational leadership and effective communication strategies.

Semantic Verification in Large Language Model-based Retrieval Augmented Generation

This position paper presents a novel approach of semantic verification in Large Language Model-based Retrieval Augmented Generation (LLM-RAG) systems, focusing on the critical need for factually accurate information dissemination during public debates, especially prior to plebiscites e.g. in direct democracies, particularly in the context of Switzerland. Recognizing the unique challenges posed by the current generation of Large Language Models (LLMs) in maintaining factual integrity, this research proposes an innovative solution that integrates retrieval mechanisms with enhanced semantic verification processes. The paper outlines a comprehensive methodology following a Design Science Research approach, which includes defining user personas, designing conversational interfaces, and iteratively developing a hybrid dialogue system. Central to this system is a robust semantic verification framework that leverages a knowledge graph for fact-checking and validation, ensuring the correctness and consistency of information generated by LLMs. The paper discusses the significance of this research in the context of Swiss direct democracy, where informed decision-making is pivotal. By improving the accuracy and reliability of information provided to the public, the proposed system aims to support the democratic process, enabling citizens to make well-informed decisions on complex issues. The research contributes to advancing the field of natural language processing and information retrieval, demonstrating the potential of AI and LLMs in enhancing civic engagement and democratic participation.

Shoreline Extraction Methods from Sentinel-2 and PlanetScope Images

Abstract. This work aims to compare and assess the performance of certain methodologies for shoreline mapping based on the use of medium (10 m) and high resolution (3 m) multi-spectral imagery, provided by Sentinel-2 (S2) and PlanetScope (PS), respectively. Being Sentinel-2 part of the Copernicus missions, its data are freely available. PS imagery are also freely available for scientific research, upon approval by the European Space Agency of a related project proposal. Several spectral indices, including Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Automated Water Extraction Index (AWEI), and Water Index (WI), were used for shoreline detection. In particular, two unsupervised classification techniques, the Gaussian Mixture Model (GMM) and K-means clustering were deployed as shoreline extraction methods. The outcomes of such approaches were validated using reference shorelines derived from aerial orthomosaics, generated from images acquired as close as possible to the satellite imagery dates, and the ”baseline and transect” approach for accuracy verification. Three tide-less Mediterranean beaches were used as study cases for comparison: the beach between Castelldefels and Gava in Spain, Feniglia and Marina di Grosseto in Italy. The results demonstrated sub-pixel accuracy in shoreline extraction, with Mean Absolute Distances ranging from 2 m to 5 m for S2 data and 1.5 m to 2 m for PS data. These findings highlight the potential of freely available satellite data for semi-automatic shoreline detection. Results obtained by using the combination of different indices and methodologies show that the best option may change depending on the considered context, hence future investigations should be dedicated to the development of a procedure for automatically determining the context-based (close to) optimal index-classifier combination.

Feasibility Verification and Upper Bound Computation in Global Minimization Using Approximate Active Index Sets

We propose a new upper bounding procedure for global minimization problems with continuous variables and possibly nonconvex inequality and equality constraints. Upper bounds are crucial for standard termination criteria of spatial branch-and-bound (SBB) algorithms to ensure that they can enclose globally minimal values sufficiently well. However, whereas for most lower bounding procedures from the literature, convergence on smaller boxes is established, this does not hold for several methods to compute upper bounds even though they often perform well in practice. In contrast, our emphasis is on the convergence. We present a new approach to verify the existence of feasible points on boxes, on which upper bounds can then be determined. To this end, we resort to existing convergent feasibility verification approaches for purely equality and box constrained problems. By considering carefully designed modifications of subproblems based on the approximation of active index sets, we enhance such methods to problems with additional inequality constraints. We prove that our new upper bounding procedure finds sufficiently good upper bounds so that termination of SBB algorithms is guaranteed after a finite number of iterations. Our theoretical findings are illustrated by computational results on a large number of standard test problems. These results show that compared with interval Newton methods from the literature, our proposed method is more successful in feasibility verification for both, a full SBB implementation (42 instead of 26 test problems) and exhaustive sequences of boxes around known feasible points (120 instead of 29 test problems). History: Accepted by Antonio Frangioni, Area Editor for Design & Analysis of Algorithms–Continuous. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0162 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0162 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Manajemen Pemasaran Online melalui Penerapan Iklan secara Digital

This research discusses online marketing management through the application of digital advertising. With the rapid development of technology and increasing use of the internet, traditional marketing methods are increasingly shifting towards digital marketing. Digital marketing offers various advantages, such as the ability to reach a wider audience, more precise targeting, and more efficient costs. This research aims to identify effective strategies in online marketing and evaluate the impact of digital advertising on consumer behavior. The development of the internet is changing the way of doing business, including in the retail business where the business model utilizes digital services in the transaction process which is known as e-commerce. This research aims to examine how in online marketing to implement online advertising and realize consumer buying interest. This research also uses a descriptive survey method using a verification approach. The population in this research is Lazada consumers in the city of Bandung, with a sample of 96 customers. The findings show that the implementation of online advertising has a direct impact on purchasing interest on the Lazada site. This research concludes that online marketing management through the implementation of digital advertising is a crucial component in modern business strategy. Companies that adopt this approach well can gain a significant competitive advantage in an increasingly digitally connected marketplace.

On the Importance of Regime-Specific Evaluations for Numerical Weather Prediction Models as Demonstrated Using the High-Resolution Rapid Refresh (HRRR) Model

Abstract The scientific literature has many studies evaluating numerical weather prediction (NWP) models. However, many of those studies averaged across a myriad of different atmospheric conditions and surface forcings that can obfuscate the atmospheric conditions when NWP models perform well versus when they perform inadequately. To help isolate these different weather conditions, we used observations from the U.S. Climate Reference Network (USCRN) obtained between 1 January and 31 December 2021 to distinguish among different near-surface atmospheric conditions [i.e., different near-surface heating rates (), incoming shortwave radiation (SWd) regimes, and 5-cm soil moisture (SM05)] to evaluate the High-Resolution Rapid Refresh (HRRR) Model, which is a 3-km model used for operational weather forecasting in the United States. On days with small (large) , we found afternoon T biases of about 2°C (−1°C) and afternoon SWd biases of up to 170 W m−2 (100 W m−2), but negligible impacts on SM05 biases. On days with small (large) SWd, we found daytime temperature biases of about 3°C (−2.5°C) and daytime SWd biases of up to 190 W m−2 (80 W m−2). Whereas different SM05 had little impact on T and SWd biases, dry (wet) conditions had positive (negative) SM05 biases. We argue that the proper evaluation of weather forecasting models requires careful consideration of different near-surface atmospheric conditions and is critical to better identify model deficiencies in order to support improvements to the parameterization schemes used therein. A similar, regime-specific verification approach may also be used to help evaluate other geophysical models. Significance Statement Improving weather forecasting models requires careful evaluations against high-quality observations. We used observations from the U.S. Climate Reference Network (USCRN) and found that the performance of the High-Resolution Rapid Refresh (HRRR) Model varies as a function of differences in near-surface heating and solar radiation. This finding indicates that model evaluations need to be conducted under varying near-surface weather conditions rather than averaging across multiple weather types. This new approach will allow for model developers to better identify model deficiencies and is a useful step to helping improve weather forecasts.

THE INFLUENCE OF MOTIVATION, WORK DISCIPLINE AND WORK ENVIRONMENT ON THE WORK PRODUCTIVITY OF PT PERKEBUNAN MINANGA OGAN EMPLOYEES IN THE REGIONAL OFFICE SECTION

Abstract: Employee misconduct at PT Minanga Ogan Plantation is evident in the employees' tardiness and mishandling of break time. Additionally, employees' laziness, boredom, and lack of desire cause delays in their work. Increasing staff productivity requires more focus. This study aims to investigate the effects of work environment, work discipline, and motivation on worker productivity at the regional office of PT Minanga Ogan Plantation. 37 respondents made up the study's population, and questionnaire distribution was the method of data collection. Quantitative research methodologies are employed in this study. Descriptive and verification approaches were employed in data analysis techniques. The analysis in this study shows that, in the PT. Minanga Ogan Plantation Regional Office, work environment (X3) has no effect on productivity, whereas motivation (X1) and discipline (X2) each have an impact. At the PT Minanga Ogan Plantation Regional Office, motivation, work discipline, and work environment all contribute 64.9% to employee productivity, according to the coefficient of determination (R2) of 0.643. There are additional elements like pay, communication, and training that could affect the remaining 35.1%. To increase productivity, a comprehensive strategy that takes into consideration other variables influencing worker performance is required.

Statistical Verification using Surrogate Models and Conformal Inference and a Comparison with Risk-Aware Verification

Uncertainty in safety-critical cyber-physical systems can be modeled using a finite number of parameters or parameterized input signals. Given a system specification in Signal Temporal Logic (STL), we would like to verify that for all (infinite) values of the model parameters/input signals, the system satisfies its specification. Unfortunately, this problem is undecidable in general. Statistical model checking (SMC) offers a solution by providing guarantees on the correctness of CPS models by statistically reasoning on model simulations. We propose a new approach for statistical verification of CPS models for user-provided distribution on the model parameters. Our technique uses model simulations to learn surrogate models , and uses conformal inference to provide probabilistic guarantees on the satisfaction of a given STL property. Additionally, we can provide prediction intervals containing the quantitative satisfaction values of the given STL property for any user-specified confidence level. We compare this prediction interval with the interval we get using risk estimation procedures. We also propose a refinement procedure based on Gaussian Process (GP)-based surrogate models for obtaining fine-grained probabilistic guarantees over sub-regions in the parameter space. This in turn enables the CPS designer to choose assured validity domains in the parameter space for safety-critical applications. Finally, we demonstrate the efficacy of our technique on several CPS models.

Does Working Culture Improve Employee Performance? The Mediation Role of Job Satisfaction

Does Working Culture Improve Employee Performance? The Mediation Role of Job Satisfaction

Unifying frameworks for complete test strategies

The field of model-based testing has witnessed the development of several test strategies on finite state machines. Although these strategies are often related, little effort has been made to explicitly identify patterns shared between them, and their concrete implementations as well as completeness proofs regularly exhibit redundancy. In this paper, we propose an approach for the systematic verification and implementation of strategies for the language-equivalence conformance relation. We present frameworks in the form of higher order functions that implement shared behaviour once and encapsulate diverging behaviour in procedural parameters, thus reducing duplication and improving maintainability and extensibility. We show that this simplifies completeness proofs by proving complete all considered strategies using the same argument. All presented frameworks, proofs, and concrete strategy implementations have been mechanised using the proof assistant Isabelle.

Pengaruh Kompetensi dan Lingkungan Kerja terhadap Kinerja Pegawai Biro SDM Polres Karawang

Viranty Herlyna Putri, 2023. The influence of competency and work environment on employee performance Biro SDM Polres Karawang. Thesis. Faculty of Economics. University of Singaperbangsa Karawang. In this study, it is related to the influence of competency and work environment on employee performance Biro SDM Polres Karawang. The quantitative method used in this study along with descriptive and verification approaches. Quantitative methods are relied on in this case along with descriptive and verification approaches. The primary data relied on in this case, namely questionnaires and unstructured interviews, non-probability sampling technique is the technique for collecting data for this research. Employees at the Karawang Police HR Bureau are the population in this study, with a total of 59 employees, in determining the sample by relying on saturated sampling, there were 59 employees consisting of Polri and ASN or PNS Polri. The success of this research using Microsoft Word, Microsoft Excel and SPSS 24. In this study, it provides the fact that there is a significant parcial effect on the competence variable of 0,41% and the work environment variable of 44,1% on employee performance at Biro SDM Polres Karawang. Furthermore, there is a simultaneous effect on competence and work environment variables on the performance of Biro SDM Polres Karawang with simultaneous value contribution reaching 74,4% and the remaining 25,6% is contribution of other variables not examined in this study.

Pengaruh Pendidikan dan Beban Kerja terhadap Kompensasi serta Dampaknya terhadap Kinerja Tenaga Fasilitator Lapangan pada Satuan Kerja Penyediaan Perumahan Provinsi Jambi

The purpose of this study is to describe the TFL performance, workload, compensation, and education in the Jambi Province Housing Provision Working Unit. It also seeks to ascertain and evaluate the impact of workload, compensation, and education on TFL performance in the Jambi Province Housing Provision Working Unit. Both quantitative and descriptive approaches of verification were employed in this study. A saturation or census sampling technique was used to determine the study's sample. The study's sample is the full TFL population in 2022, which is limited to 63 people. The path analysis method is used in this study. Employee education at the Jambi Province Housing Provision Work Unit is described as belonging to the "Appropriate" category, workload is in the "Very High" category, work environment is in the "good" category, employee compensation is in the "High" category, and performance is in the "Very High" category. The Jambi Province Housing Provision Work Unit's TFL is classified as "Good." The path analysis's findings, which show that education has a 21.8% impact on performance through compensation, and that the impact of education on workload and compensation is 9.7%, with a total effect of 31.5%. This chart illustrates how education through compensation increased the TFL Performance of the Housing Provision Work Unit in the Province of Jambi by 31.5%. Workload has a 25.3% impact on performance through compensation; it has a 9% impact on performance through education and compensation; the overall effect is 34.3%. Reducing the Workload via Compensation contributed 34.3% to the TFL Performance of the Housing Provision Work Unit in the Province of Jambi. The combined impact of education and workload through compensation has a direct effect on performance of 47.1%, an indirect effect of 186%, and a total effect of 65.8%. This figure illustrates how these factors affected the performance of Jambi Province Housing Provision Work Unit employees by 65.8%.

The Effect of Project-Based Learning Method on Creative Problem-Solving in Students of the Entrepreneurship Study Program, Indonesian University of Education

The effectiveness of learning is significant in preparing students' skills paradigms. This research aims to instill the influence of the Project Based Learning (PjBL) method on students' Creative problem-solving abilities in the context of entrepreneurship learning. This research focuses on Indonesian Education University Entrepreneurship Study Program students who have taken the Start-up course. Creative problem-solving skills are considered important in preparing students to face the demands of an increasingly complex world of work. The research method used is quantitative with a descriptive verification approach, and data collection is carried out through questionnaires. The results of the research show that project-based Learning (PjBL) has a significant influence on increasing creative problem-solving abilities in students of the Entrepreneurship Study Program at the Indonesian University of Education. This research shows that Project Based Learning significantly improves the quality of Creative Problem Solving for Entrepreneurship Study Program Students at Universitas Pendidikan Indonesia

Evaluating Reliability and Economics of EV Charging Configurations and Deep Reinforcement Learning in Robotics and Autonomy

Growing EV popularity drives companies to focus on reliable charging station designs despite challenges in maintaining reliability. A proposed 36-ported design combines uniform and non-uniform port arrangements, tested with 50-350 kW systems. Failure rates are estimated using MILHDBK217F and MILHBK-338B standards, assessing port reliability and station success rates through binomial distribution and cost analysis. This design improves voltage stability and reduces maintenance costs through enhanced port reliability. In robotics and autonomous systems, Deep Reinforcement Learning (DRL) excels but faces challenges from unsafe policies leading to hazardous decisions. This study introduces a reliability assessment framework for DRL-controlled systems, using formal neural network analysis. A two-level verification approach evaluates safety locally using reachability tools and globally by aggregating local safety metrics across tasks. Experimental validation confirms the framework's effectiveness in enhancing RAS safety.

Ensuring the Quality of the Analytical Process in a Research Laboratory

This paper discusses approaches for verification of methods of measurements of chemical and physical characteristics of specific samples. The limitations of well-known approaches are discussed. Some examples of alternatives are given to demonstrate specific issues encountered in the research laboratory analyzing new materials or characterizing new properties of materials. Application of sequential procedure using lower quantities of samples and reagents is presented. A standard addition to solid samples is discussed. The approach of control charts for estimation of method uncertainty for determination of plant available phosphorus is presented. The method comparison is applied as an approach to verification of alkaline reactivity by inductively coupled plasma–optical emission spectroscopy (ICP-OES) measurement, as well as density of newly synthesized chalcogenide glass materials. The presented examples demonstrated that alternative approaches are needed in order to verify the methods applied due to the great variety of activities and corresponding tasks in a research laboratory.

Local deadlock analysis of Simulink models based on timed behavioural patterns and theorem proving

Compositional deadlock analysis of process networks is a well-known challenge. We propose a compositional deadlock analysis strategy for timed process networks, more specifically, those obtained from Simulink multi-rate block diagrams. We handle models with both acyclic and cyclic communication graphs. Particularly, the latter naturally happens in Simulink models with feedback, among other kinds of cycles. Since there is no general solution to analyse cyclic models in a compositional way, we explore the use of behavioural patterns that allow the verification to be carried out in a compositional fashion. We represent process networks in tock-CSP, a dialect of CSP that allows modelling time aspects using a special tock event. The verification approach is implemented as a new package in CSP-Prover, a theorem prover for CSP which is itself implemented in Isabelle/HOL. To illustrate the overall approach and, particularly, how it can scale, we consider several variations of an actuation system with increasing complexity. We show that the examples are instances of the client/server and the asynchronous dynamic timed behaviour patterns. These patterns and all verification steps are formalised using CSP-Prover.

Challenges of Operational Weather Forecast Verification and Evaluation

Abstract Operational agencies face significant challenges related to the verification and evaluation of weather forecasts. These challenges were investigated in a series of online workshops and polls engaging operational personnel from six countries. Five key themes emerged: inadequate verification approaches for both existing and emerging products; incomplete and uncertain observations; difficulties in accurately capturing users’ real-world experiences using simplified metrics; poor communication and understanding of forecasts and complex verification information; and institutional factors such as limited resources, evolving meteorologist roles, and concerns over reputational damage. We identify nearly 50 operationally relevant scientific questions and suggest calls to action. Addressing these needs includes designing forecast systems with verification as a central consideration, enhancing the availability of observations, and developing and adopting community software systems. Additionally, we propose the establishment of an international community comprising environmental and social science researchers, statisticians, verification practitioners, and users to provide sustained support for this collective endeavor.

Analysis of post COVID-19 economic recovery on inflation fluctuation management in Indonesia

This research aims to find out, explain and test the Post-COVID-19 Economic Recovery Analysis of Inflation Fluctuation Management in Indonesia. This research uses quantitative methods with a descriptive and verification approach by collecting presentations through a process of analysis and hypothesis testing. The data used is secondary data, namely from Ceic Data, Trading Economics and Bank Indonesia for 2019-2023. The data analysis method in this research uses a difference test where this model is used to analyze pre-post or before and after research models. The research results show that there are significant differences in inflation and exchange rates during COVID-19 and post-COVID-19. Post-COVID-19 economic recovery policies such as fiscal stimulus and quantitative easing were able to reduce inflation and stabilize the exchange rate. Coordination is needed between the central, regional and monetary authorities to maintain macroeconomic stability after the pandemic. This research concludes that the post-COVID-19 economic recovery policy has succeeded in controlling inflation and the exchange rate in Indonesia, although regular evaluation and refinement of policies is required.

In Silico and Chromatographic Methods for Analysis of Biotransformation of Prospective Neuroprotective Pyrrole-Based Hydrazone in Isolated Rat Hepatocytes.

In the current study, chromatographic and in silico techniques were applied to investigate the biotransformation of ethyl 5-(4-bromophenyl)-1-(2-(2-(2-hydroxybenzylidene) hydrazinyl)-2-oxoethyl)-2-methyl-1H-pyrrole-3-carboxylate (11b) in hepatocytic media. The initial chromatographic procedure was based on the employment of the conventional octadecyl stationary phase method for estimation of the chemical stability. Subsequently, a novel and rapid chromatographic approach based on a phenyl-hexyl column was developed, aiming to separate the possible metabolites. Both methods were performed on a Dionex 3000 ThermoScientific (ACM 2, Sofia, Bulgaria) device equipped with a diode array detector set up at 272 and 279 nm for analytes detection. An acetonitrile: phosphate buffer of pH 3.5: methanol (17:30:53 v/v/v) was eluted isocratically as a mobile phase with a 1 mL/min flow rate. A preliminary purification from the biological media was achieved by protein precipitation with methanol. A validation procedure was carried out, where the method was found to correspond to all ICH (Q2) and M10 set criteria. Additionally, an in silico-based approach with the online server BioTransformer 3.0 was applied in an attempt to predict the possible metabolites of the title compound 11b. It was hypothesized that four CYP450 isoforms (1A2, 2C9, 3A4, and 2C8) were involved in the phase I metabolism, resulting in the formation of 12 metabolites. Moreover, docking studies were conducted to evaluate the formation of stable complexes between 11b and the aforementioned isoforms. The obtained data indicated three metabolites as the most probable products, two of which (M9_11b and M10_11b) were synthesized by a classical approach for verification. Finally, liquid chromatography with a mass detector was implemented for comprehensive and summarized analysis, and the obtained results revealed that the metabolism of the 11b proceeds possibly with the formation of glucuronide and glycine conjugate of M11_11b.