Semantic Components of English Directive Speech Act Verbs (Order, Command, Instruct)

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This research focuses on synonymous English speech act verbs that mean “giving order” (directive). The verbs analyzed in this study are those with very close synonymy, namely order, command, and instruct. The aim of this research is to describe in more detail the semantic behavior of the directive English speech act verbs through their semantic component. This semantics study is qualitative descriptive research. The data in this study were collected by using corpus linguistics and observation methods with note-taking techniques. The data source is the Corpus of Contemporary American English (COCA). There are 300 citations for each verb analyzed, which making in total 900 citations analyzed in the study. The study found that the verbs order, command, and instruct has eight semantic features/components that differentiate those three verbs, namely the components of authority, the way of saying, form of order, the duration of orders, level of urgency, actor and undergoer positions, domain of use, compliance level.

Establishing the program to predict Shirt Sizes with Fuzzy Logic

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This paper presents a program for prediction shirt size with a fuzzy logic technique. The Mamdani model is applied to a MISO fuzzy system with two inputs and one output. Neck girth and sleeve length are chosen as the primary dimensions, serving as input variables for this simulation model. In this study, fuzzy logic is used to select the size of the Min-Max rule. The IF-THEN structure is applied to execute commands effectively within this model. The outcome is an appropriate size. The program’s fuzzy rule matrix consists of 45 rows and 5 columns. Each row is a fuzzy rule. The first column represents the 9 sizes of necklaces. The second column represents the 5 groups of sleeve lengths. The third column represents the 9 predicted sizes in the output. The fourth column is the weight coefficient. The last column represents the logical connection type. The fuzzy logic approaches significantly reduces the time required. This approach provides an alternative method for prediction sizes that more accurately align with individual body measurements, offering a personalized fit.

MSMEs Bookkeeping Capabilities for Accounting Information Transparency

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MSMEs contribute 60% to gross domestic income, MSMEs also absorb labor and collect investment. However, of the total percentage of banking credit, MSMEs only get 20%. Banks experience difficulties in disbursing credit due to a lack of information on debtors who are worthy of financing. Difficulties are caused by the absence of financial reports as a parameter for credit worthiness. Through accounting transparency, it will be easy for MSMEs to know the policies that will be and have been taken. Transparency means the availability of sufficient, accurate and timely information about accounting policies and reporting. It is hoped that this research will be able to provide considerations for MSMEs to improve their accounting capabilities in accordance with SAK EMKM. The research was conducted in Denpasar, involving 100 questionnaire respondents and 10 informants in FGD. The data analysis technique used in this research is interpretive descriptive qualitative analysis technique.

As a result, MSMEs do not yet have the capability to prepare financial reports. MSMES players consider that the important aspects in starting a business are capital, skills and innovation or products, not accounting. Low accounting capability has an impact on neglecting the preparation of financial reports. Transparency can increase funding opportunities from banks or investors as well as opportunities for collaboration. There are still many MSMEs that have not prepared financial reports due to limited human resources and costs. However, MSMES players want to prepare financial reports.

MSMEs in the medium business category have prepared financial reports in accordance with SAK EMKM, only some in the small business group and not in the small business group. SAK EMKM requires a statement of financial position at the end of the period (balance sheet), a profit and loss statement for the period and notes to the financial statement. MSMEs focus more on recording expenses and income for profit and loss projections but ignore the balance sheet and Calc. The compiled profit and loss is still not relevant, there are still many accounts that have not been taken into account. Preparing a complete report in accordance with SAK EMKM will provide much more relevant and credible information.

Comparative Analysis of Machine Learning Algorithms for Used Car Price Prediction

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After 2021, over 90 million passenger automobiles were produced, marking a significant increase in auto production. This growth has led to a flourishing used car market, which has become a highly lucrative sector. One of the most critical and fascinating areas of research within this market is automobile price prediction. Accurate price prediction models can greatly benefit buyers, sellers, and businesses in the used car industry. This paper presents a detailed comparative analysis of two supervised machine learning models: K-Nearest Neighbour and Support Vector Machine regression techniques, to predict used car prices. We utilized a comprehensive dataset of used cars sourced from the Kaggle website for training and testing our models. The K Nearest Neighbour algorithm is known for its simplicity and effectiveness in regression tasks. On the other hand, the Support Vector Machine regression technique uses a different approach, finding the optimal hyperplane that best fits the data. Both methods have their strengths and weaknesses, which we explored in this study. Our results indicated that both KNN and SVM models performed well in predicting used car prices, but with slight variations in accuracy.  Consequently, the suggested models fit as the optimum models and have an accuracy of about 83 percent for KNN and 80 percent for SVM. The results indicate that the KNN model slightly outperforms the SVM model in predicting used car prices.

Exploring the Frontiers: A Comprehensive Review of Augmented Reality and Virtual Reality in Manufacturing and Industry

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Augmented reality (AR) and virtual reality (VR) are revo- lutionizing manufacturing practices by offering immersive and interactive experiences. This review paper synthesizes current research on AR and VR’s applications, benefits, and challenges in manufacturing, covering design, training, maintenance, and quality control. Key findings highlight the applications and positive impact of AR/VR on efficiency, cost management, and quality control in manufacturing processes. Industries are in- creasingly adopting these technologies to enhance productivity and reduce errors. However, challenges such as cost, techno- logical infrastructure, and integration into existing workflows remain significant barriers. In conclusion, integrating AR and VR in manufacturing holds immense potential to transform traditional methods and improve operational efficiency. This paper advocates for broader implementation and research to harness the full benefits of immersive technologies in manufacturing.

Grid Search Optimized Machine Learning based Modeling of CO2 Emissions Prediction from Cars for Sustainable Environment

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Carbon emissions have increased dramatically because of industrialization, trapping heat in the atmosphere and hastening climate change. This is a serious threat to the wealth, security, and well-being of the world. The effects are extensive, ranging from severe weather, disease outbreaks, and economic disruption to food insecurity and water scarcity. The World Health Organization (WHO) has determined that climate change poses the greatest threat to public health in the twenty-first century. Thus, precise CO2 emissions have emerged as a crucial concern in recent times. Several studies have tried to forecast the amount CO2 from industry and power plant using statistical analysis. Efficiency, robustness and diverse application was the limitation of the study.  In this study, we have proposed an AI based model that is able to predict the amounts of CO2 emissions from cars. We applied a grid search-optimized machine learning approach using the publicly available Canadian dataset. Incorporation of different statistical analyses and preprocessing techniques such as duplicate data management, outlier rejection, scaling contributed to enhance the quality of the dataset. Later, grid search techniques were applied to tune the KNN, RF, and SVR models. The approach has enhanced the performance of CO2 emissions prediction. In the study, we further used the explainability of the random forest model to check the bias and fairness of predictability. MSE, RMSE, and R-squared metrics of the proposed approach were the highest as the state of the art.  

Marketing Strategies and Sales Performance of a Manufacturing Company

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This study was carried out to investigate how marketing strategies, consisting of product, price, place, and promotion strategies, affected the sales performance of a food and beverage manufacturing company. A review of extant literature indicated the need for studies, in this regard, in Nigeria’s food and beverages industry.

The study adopted a survey research design. Two hundred and seventy four employees of a food and beverage manufacturing company in Lagos State were studied. Data were collected on a four-point scale ranging from strongly disagree, 1, to strongly agree, 4.  Mean and standard deviation values of statements relating to marketing strategies were obtained from descriptive statistics while inferential statistics based on multiple regression analysis produced results that determined the effects of marketing strategies on sales performance.

The results indicated statistical significance [F(4,269)df = 4783.108, p < .05)] for the effect of marketing strategies on sales performance. Product (β = .478, t = 5.588, p < .05), place (β = .454, t = 5.360, p < .05), and promotion (β = .075, t = 1.773, p > .05) strategies had positive effects on sales performance while price strategy indicated insignificant negative effect (β = -.023, t = -.626, p > .05) on sales performance. Marketing strategies explained 98.6 percent variation in sales performance.

The conclusion of the study indicated a need for the managers of the company to increase the tempo of premium-pricing promotion strategy and advertisements in the social and electronic media as well as reevaluate the pricing strategy of the company as a means of improving its effectiveness by increasing the chances of achieving the objectives of cost recovery and meeting the needs of customers.

Tax Revenue and Human Development Index in the Seven ASEAN Countries

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This research is motivated by curiosity about tax revenues and human development indices in 7 (seven) ASEAN countries that are influenced by tax revenues. The aim of this study is to show the impact of taxes on the Human Development Index in 7 ASEAN countries. Examples of this study include Indonesia, Malaysia, the Philippines and Thailand, Myanmar, Cambodia, and Vietnam. The second data used in this study covers the period from 2010 to 2023. The regression of the panel data was used in the processing of the study data. At the same time, this study significantly illustrates the influence of independent variables on related variables. Variable inflation had a significant negative impact on tax revenues, while variable market capitalization and tourist visits had a positive and significant correlation with tax revenues. Tax revenues also have a positive impact on the economic growth of ASEAN countries (Indonesia, Malaysia, the Philippines, Thailand, Myanmar, Cambodia and Vietnam).

Empowerment Pattern Based on Food Independence on the Indigenous Peoples of the Baduy Dalam Tribe

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The farming system implemented by the Baduy Dalam community still applies the traditional farming system with the mechanism of the farmland system, which is to rest the land after being used for farming and then wait for the time to be used again for farming.  With the increase in the population, the need for food increases, but this has an impact on the small area of land because it has been converted into residential land.  The purpose of this research is to find alternative solutions from the empowerment model that can be applied to the Baduy Dalam community to support food security in the Baduy Dalam community.  The research method uses a qualitative descriptive method using a phenomenological and ethnographic approach. The location of this research is in Cibeo, Cikartawana, and Cikeusik Villages which are included in the Baduy Dalam area.  The number of informants was 7 people consisting of the Head of Kanekes Village, 3 Deputy Puun, and 3 representative residents from each village.  The results of this study are recommendations for empowerment models that can be carried out by a companion must meet the following elements, namely: 1) Empowerment of soil nutrient improvement with orok-orok plants, 2) Making Organic Fertilizer to increase plant fertility, and 3) Empowerment of MOL production.

Optimal Control Strategy to Analyse the Networked Control System Stability

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It is crucial to preserve the networked control systems (NCS) transient performance and stability because adding uncertain parameters degrades system performance and introduces instability. Thus, the analysis of NCS system performance under uncertain conditions, such as disturbance, is the focus of this paper. The performance of NCS is demonstrated using control action and some appropriate stability conditions.
The simulation diagram in result section displays effectiveness of proposed methodology and shows a comparative analysis of the response signal with and without control action along with disturbance in NCS. Experiments conducted in the MATLAB Simulink environment demonstrate the efficacy of the suggested methodology.