Sample Selection Method Research Articles

The Application of Remote Sensing Technology in Returning Farmland to Forest

Since the 1980s, due to China's economic development, large tracts of forest trees have been felled, causing serious soil erosion and environmental pollution problems. But since the beginning of this century, China has started to convert farmland to forests and various vegetation restoration activities. The purpose of returning farmland to forest is to better protect the environment and prevent soil erosion. This paper introduces the use of remote sensing images to detect the implementation of the project of returning farmland to forest. Explain the method of sample selection and the steps of data collection. The plan on remote sensing monitoring of returning farmland to forest was introduced. At the same time, the help and continuous monitoring of remote sensing technology after returning farmland to forest was introduced. This article contains examples and analysis of scientists using GIS technology to assist in returning farmland to forests. Finally, it includes the prospect and expectation of GIS for the project of returning farmland to forest. And the future application of this technology in this project is prospected.

Effectivity of Management Events with Integrated System Organization Rumah Sakit Dr. Oen Kandang Sapi Solo

Background: To provide information on health services and education, hospitals require marketing communication, one of which is event. The hospital holds a variety of events for employees and citizen, which are routine or even incidental. Along with era development, hospitals are required to make fast and precise movements, so that performance is efficient and effective to achieve the success of events. President Director of RUMAH SAKIT Dr. OEN KANDANG SAPI SOLO (Droenska) decided to establish the Hospital Event Committee in 2019 with integrated system organization (ISO DOI) to replace the role of the event committee which is formed in every events. It is expected that the performance of each unit can be more effective, efficient, and the entire hospital community makes the culture of hospitals, internal marketers, as a way of life, because intangible marketing assets are important to embrace customers. After the Decision of the President Director is determined and implemented, of course, monitoring and evaluation are required.Purpose: Evaluating the effectiveness of events management which used Integrated System Organization RUMAH SAKIT Dr. OEN KANDANG SAPI SOLO (ISO DOI).Method: Qualitative descriptive research was used. The research datas were obtained through in-depth interviews with 17 informans who are choosen by purposive sampling selection method at the Hospital Event Committee in 2019–2020. Then it is formulated with the study of proposal recapitulation data as well as liability sheet (LPJ) in 2019–2020.Result: Component and function of Hospital events committee already fulfilled the standard of EO. The concept of events is quite good and clear. Coordination between the committees of events is inadequate due to a lack of communication and initiative. The event went smoothly and also there were no obstacles that led to the failure of the event, although there were still some shortcomings. Some of the event committees have not evaluated and given accountability (LPJ).Conclusion: The completeness of EO component’s and work function’s already exists and running on the Hospital Event Committee (ISO DOI). Events held by hospital with ISO DOI committees become more organized, effective, and efficient, but the function of coordination and evaluation must be improved. ISO DOI is potensial to develop as an event organizer that manage events with partners so that it can be additional revenue for Droenska.

Akuntansi Syariah: Harapan dan Realitas di Lembaga Keuangan Syariah

This study aims to determine the influence of Islamic accounting knowledge, work environment, and religiosity on the interest of accounting students in a career in Islamic financial institutions. The population in this study was all accounting students at Cipasung Tasikmalaya University, which amounted to 418 people. The sample selection method uses non-probability sampling techniques. The research method used is a quantitative descriptive analysis method. for data analysis using the IBM SPSS Statistics 27 system program. The results of this study show that partially (t) the variable of religiosity does not have an influence on the interest of accounting students for a career in Islamic financial institutions, while the variables of Islamic accounting knowledge and work environment have an influence on the interest of accounting students for a career in Islamic financial institutions. Simultaneously, (f) Islamic accounting knowledge, work environment, and religiosity jointly affect the interest of accounting students in a career in Islamic financial institutions. The R square value of 0.461 means that the amount of independent influence on the dependent variable is 46.1%. While the remaining 53.9% was influenced by other variables that were not variables in this study.

CLFR-Det: Cross-level feature refinement detector for tiny-ship detection in SAR images

Ship detection in synthetic aperture radar (SAR) images is an important and active topic, due to the characteristics of SAR images involving all-time and all-weather imaging. However, complex backgrounds caused by speckle noise and inshore land, coupled with information deficiency of tiny ships, pose a great challenge for tiny-ship detection in SAR images. To tackle this problem, we present a cross-level feature refinement detector (CLFR-Det) that utilizes features reflecting different levels and distinct semantics (classification and localization). To enrich the semantic information of tiny ships, our approach incorporates a cross-level modulated deformable convolution to aggregate features from relevant positions across multi-level feature maps. This is supported by a spatially-informed multi-scale feature refinement mechanism that combines the features for classification and those for localization. We implement a uniform IoU-weighted adaptive training sample selection method for equitably distributing the impact of positive samples from targets of various sizes during the training process. A generalized IoU loss between ground-truth and preliminary bounding box is further proposed to supervise the learning process of the CLFR-Det, with uncertainty weights incorporated to dynamically depict the levels of disparate losses, enabling adequate training across different tasks. Also, we construct a novel tiny SAR ship detection dataset to comprehensively evaluate the effectiveness of our system, in conjunction with the use of publicly available SSDD and HRSID datasets. Experimental investigations demonstrate that CLFR-Det generally surpasses state-of-the-art performance for multi-scale ship detection, particularly for the detection of tiny ships.

Analysis of the application of OHS Management System in the Emergency Assistance for Rehabilitation and Reconstruction (EARR) Project at Mutiara Sis Al Jufri Airport, Palu City

This research with the background of the Airport that must continue to operate along with the implementation of construction work, wants to know the factors that influence, as well as the dominant factors and the most dominant factors on the implementation of the Occupational Safety and Health Management System (SMK3) on the Emergency Assistance for Rehabilitation and Reconstruction (EARR) Project at Mutiara Sis Al Jufri Airport, Palu City. Using factor analysis method, eight (8) new influential factors were obtained. This study uses a population of 119 project staff and workers and a sample selection method with a random sample with the slovin method, obtaining a sample size of 55 respondents. Research data was taken using a questionnaire method, so that the output of data processing results with the factor analysis method was obtained, that the most significant factor was factor 1 (Standard Operating Procedure / OSH Standard), with the variable: The company provides Personal Protective Equipment (PPE) to project workers. (X11 with a loading factor of 0.895).

Modern technologies for agriculture: how far Pakistani farmers are from the developed world?

In order to accomplish the objective of the current study household data was collected from one district of Sindh province. Main aim of this study is to find out that which modern technologies are being used at various form level and suggest police measure for technical advancement. For this study a purposive sample selection method was adopted to select Hyderabad, because it was considered that farmers of this location might be more aware about modern technologies due to Sindh Agriculture University and Directorate General of Agriculture extension are situated in this district. Those institutes are organizing awareness seminars/training for farmers of the province. Diversified stakeholders are presenting this region, that is why, we selected the respondents from there. At the second stage, through stratified random sampling method 80 households were selected 50 small, 20 medium and 10 large based on proportion of population size in each category of small medium and large farmers. Stratification was made on the bases of small (farmers own land from 1 to 12 acres), medium (farmers own land from 13 to 25 acres) and large (farmers own land from 26 to 46 acres) farmers. Results revealed that the small farmers predominantly rely on farming for their livelihood. They have limited educational attainment, with the majority completing only primary education. While they exhibit a strong commitment to farming, their relatively small landholding of 3.9 acres and the prevalence of financial challenges, as indicated by total household expenditure exceeding income, suggest potential vulnerabilities. Medium farmers, strikes a balance between farming and education, with a more diverse educational background. With a larger landholding of 16 acres and stable income and expenditure patterns, this household appears to be in a relatively secure financial position. Large farmers exhibit the most favorable economic profile. With a more educated and experienced demographic, extensive land ownership, and strong financial stability, they are positioned for prosperity

Determinants of Original Local Government Revenue In North Sumatera Province

The amount of Original Local Government Revenue has increased and decreased every year, in 2020 where the economy in Indonesia was heavily affected by the Covid-19 Pandemic, Original Local Government Revenue has decreased by 6 percent from 2019. The objective of the research was to determine the effect of GRDP, total population, number of labor forces, regional taxes, results of management of separated regional assets, and other legal Original Local Government Revenue toward Original Local Government Revenue of North Sumatra Province. North Sumatera Province is the population in this research. The sample selection method was to use a saturated sampling technique. Secondary data was to use panel data consisting of 2019 to 2021. Data analysis was to use multiple linear regression analysis. The results of the research stated that partially GRDP had a significant effect on Original Local Government Revenue, partially Population had a significant effect on Original Local Government Revenue, partially the number of workforce had no effect on Original Local Government Revenue, partially Regional Tax had a significant effect on Original Local Government Revenue, partially the results of management of separated regional assets did not affected Original Local Government Revenue, partially other Legal Original Local Government Revenue did not affect Original Local Government Revenue. Simultaneously the variables of GRDP, total population, number of labor force, regional taxes, results of management of separated regional assets, other legal Original Local Government Revenue affected Original Local Government Revenue. It is hoped that the government could explore more other sources of Original Local Government Revenue to support sources of financing from the region itself.

FACTORS AFFECTING TAX AVOIDANCE IN MANUFACTURING COMPANIES LISTED IN IDX

This study aims to examine the affect of the independent variables of Sales Growth, Inventory Intensity, and Liquidity on the dependent variable, namely Tax Avoidance. The population used in this study is all manufacturing companies / taxpayers listed on the Indonesia Stock Exchange (IDX). In this study, companies/taxpayers that have met the criteria so that the data used as a sample for this study are 240 sample data of manufacturing companies/taxpayers. The researcher used the sample selection method, namely the Purposive Sampling Method, so that the researchers obtained a sample of 80 manufacturing companies / taxpayers during the 2019 – 2021 period which met the researcher's criteria. The data used by researchers is secondary data sourced from the Indonesian Stock Exchange website. The researcher tested each independent variable on the dependent variable, namely tax avoidance, and the researcher used a multiple regression model. So, the results of this study indicate that the Inventory Intensity variable has an affect on Tax Avoidance. While other independent variables, namely Sales Growth and Liquidity, obtained results that had no affect on tax avoidance.

ANALISIS PEMANFAATAN DANA CORPORATE SOCIAL RESPONSIBILITY (CSR) BAGI PENINGKATAN KESEJAHTERAAN MASYARAKAT DI SEKITAR TAMBANG DI KABUPATEN KONAWE SELATAN

South Konawe Regency, which has many companies spread across several sub-districts, in implementing CSR in general, which is related to welfare, has not been felt by the community, especially those around the companies in South Konawe Regency. The aim of this research is to determine the process of allocating funds and the contribution of using Corporate Social Responsibility (CSR) funds to improve the welfare of communities around mines in South Konawe Regency. This type of research is qualitative research which is descriptive exploratory in nature which attempts to describe or describe the various realities found in this research. The sample selection method for this research was purposive. The mines sampled are divided into two categories, namely mines that have production operation status and mines that still have exploration status located in 7 (seven) sub-districts, namely Punggaluku, Laeya, Palangga, South Palangga, Lainea, Lalembu and Laonti. Data collection techniques are the observation method, questionnaire method, and documentary method. The data analysis techniques in this research are divided into three, namely data reduction, data display, and drawing conclusions or verification. The research results show that the company's CSR allocation process is carried out by the CSR sector making an annual budget plan. The budget is made based on the year's work plan and on requests from the surrounding community. However, whether the action plan from the CSR budget plan is carried out according to plan or not depends on the profit obtained by the company. So that the company in terms of distribution of Corporate Social Responsibility (CSR) funds is not carried out evenly in the community. Contributions in the use of Corporate Social Responsibility (CSR) funds are not only intended for the community but also for the company itself. The use of CSR funds for community welfare has not been felt by society in general, especially people who live in areas around the mine. Several companies in South Konawe Regency in the process of allocating CSR funds generally focus more on physical aspects such as building mosque ceilings, making curtains, making football field stands and repairing school buildings and so on.

FACTORS THAT INFLUENCE AUDIT LAG IN NON-CYCLICAL CONSUMER SECTOR COMPANIES

The purpose of this study was to examine the effects of comprehensive income, total assets, and KAP size on audit lag. Audit lag is the time span for completing the audit of annual financial statements, namely from the closing date of the company's books to the date stated in the independent auditor's report, the sample selection method for this study is purposive sampling, which is a sampling method based on certain criteria set by the researcher. The research method used in this research is multiple analysis regression. The samples used in this study were 30 companies engaged in the consumer non-cyclicals sector listed on the Indonesia Stock Exchange for the 2020-2022 period, the data used was secondary data. The results of this study are as follows: total assets, KAP size, and comprehensive income have an effect on audit lag.

Mapping 30-m cotton areas based on an automatic sample selection and machine learning method using Landsat and MODIS images

ABSTRACT Cotton is one of the most significant cash crops in the world, and it is also the main source of natural fiber for textiles. It is crucial for cotton management to identify the spatiotemporal distribution of cotton planting areas timely and accurately on a fine scale. However, previous research studies have predominantly concentrated on specific years using remote sensing data. Challenges still exist in the extraction of cotton areas for long time series with high accuracy. To address this issue, a novel cotton sample selection method was proposed and the machine learning method is employed to effectively identify the long time series cotton planting areas at a 30-m resolution scale. Bortala and Shuanghe in Xinjiang, China, were selected as the study cases to demonstrate the approach. Specifically, the cropland in this study was extracted by using an object-oriented classification method with Landsat images and the results were optimized as the vectorized boundary of croplands. Then, the cotton samples were selected using the Normalized Difference Vegetation Index (NDVI) series of Moderate Resolution Imaging Spectroradiometer (MODIS) based on its phenological characteristics. Next, cotton was identified based on the croplands from 2000 to 2020 by using the machine learning model. Finally, the performance was evaluated, and the spatiotemporal distribution characteristics of cotton planting areas were analyzed. The results showed that the proposed approach can achieve high accuracy at a fine spatial resolution. The performance evaluation indicated the applicability and suitability of the method, there is a good correlation between the extracted cotton areas and statistical data, and the cotton area of the study area showed an increasing trend. The cotton spatial distribution pattern developed from dispersion to agglomeration. The proposed approach and the derived 30-m cotton maps can provide a scientific reference for the optimization of agricultural management.

THE EFFECT OF TRANSFORMATIONAL LEADERSHIP, FINANCIAL COMPENSATION AND GENDER ON JOB SATISFACTION OF CARGO TERMINAL BRANCH OF MINANGKABAU INTERNATIONAL AIRPORT

Objective -This research is to find out: (1) The effect of transformational leadership on job satisfaction at Minangkabau Airport Cargo Terminal (2) The effect of financial compensation on job satisfaction at Minangkabau Airport Cargo Terminal (3) The Effect of Gender on job satisfaction at Minangkabau Airport Cargo Terminal
 Methodology –This research is a quantitative research. The population of this study were all employees working at the Minangkabau International Airport Cargo Terminal as many as 41 people. The sampling technique was carried out by using Technic Total Sampling, which is a sample selection method that is applied to the entire population. Collecting data using a questionnaire with a Likert scale. The data analysis technique is a regression analysis technique using the SPSS V. 25 application.
 Results -The results of data processing in this study show that: (1) There is a positive influence between transformational leadership on job satisfaction. (2) Compensation has a significant and positive effect on job satisfaction at Minangkabau Airport Cargo Terminal. (3) there is a positive influence between gender on job satisfaction.

Cost-effective identification of the field maturity of tobacco leaves based on deep semi-supervised active learning and smartphone photograph

As a key technology for tobacco leaf harvesting, automatic identification of the field maturity of tobacco leaves is an important issue in the tobacco industry. For years, researchers have been exploring machine learning methods to perform the identification task, with traditional supervised learning (SL) schemes being studied in depth. However, the actual use of an SL algorithm is always costly and cumbersome, as it requires a large amount of labor and time to collect and label enough tobacco leaf samples. Therefore, a cost-effective algorithm solution is desired by the industry. To this end, we investigate the efficacy and efficiency of semi-supervised learning (SSL) scheme for this task, attempting to significantly reduce the labeling cost and provide a flexible way to control the cost. Considering the advantages of smartphones in terms of availability and economy, we use smartphone photography as an image acquisition tool, thereby building a tobacco leaf maturity dataset containing more than 7000 tobacco leaf images of three field maturity categories (unripe, ripe and overripe) of three stem positions (bottom, middle and top). According to the fact that the maturity of the unripe, ripe and overripe leaves increases sequentially, we propose a maturity structure constraint (MSC) to make the identification model converge to a confident space and be generalizable. Furthermore, we propose a sample selection method based on self-supervised representation learning, which can effectively select high-quality samples for the identification network. Finally, we design an SSL algorithm framework called maturity structure constraint based semi-supervised learning (MSC-SSL) for the identification task. Experimental results show that our SSL framework is capable to significantly reduce the sample usage and improve the identification accuracy. It achieves the accuracies of 91.92% (bottom position/with 33.16% training samples), 87.06% (middle position/with 27.57% training samples) and 87.64% (top position/with 28.02% training samples) when auto stopped, as compared to the SSL benchmarks of 87.37% and 90.40%, 83.53% and 85.10%, 81.65% and 84.64%, respectively. Furthermore, our method can match or exceed the accuracy of the SL scheme using only about 25% of the labeled samples required by the SL scheme.

Landslide Susceptibility Prediction Using Machine Learning Methods: A Case Study of Landslides in the Yinghu Lake Basin in Shaanxi

Landslide susceptibility prediction (LSP) is the basis for risk management and plays an important role in social sustainability. However, the modeling process of LSP is constrained by various factors. This paper approaches the effect of landslide data integrity, machine-learning (ML) models, and non-landslide sample-selection methods on the accuracy of LSP, taking the Yinghu Lake Basin in Ankang City, Shaanxi Province, as an example. First, previous landslide inventory (totaling 46) and updated landslide inventory (totaling 46 + 176) were established through data collection, remote-sensing interpretation, and field investigation. With the slope unit as the mapping unit, twelve conditioning factors, including elevation, slope, aspect, topographic relief, elevation variation coefficient, slope structure, lithology, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), distance to road, distance to river, and rainfall were selected. Next, the initial landslide susceptibility mapping (LSM) was obtained using the K-means algorithm, and non-landslide samples were determined using two methods: random selection and semi-supervised machine learning (SSML). Finally, the random forest (RF) and artificial neural network (ANN) machine-learning methods were used for modeling. The research results showed the following: (1) The performance of supervised machine learning (SML) (RF, ANN) is generally superior to unsupervised machine learning (USML) (K-means). Specifically, RF in the SML model has the best prediction performance, followed by ANN. (2) The selection method of non-landslide samples has a significant impact on LSP, and the accuracy of the SSML-based non-landslide selection method is controlled by the ratio of the number of landslide samples to the number of mapping units. (3) The quantity of landslides has an impact on how reliably the results of LSM are obtained because fewer landslides result in a smaller sample size for LSM, which deviates from reality. Although the results in this dataset are satisfactory, the zoning results cannot reliably anticipate the recently added landslide data discovered by the interpretation of remote-sensing data and field research. We propose that the landslide inventory can be increased by remote sensing in order to achieve accurate and impartial LSM since the LSM of adequate landslide samples is more reasonable. The research results of this paper will provide a reference basis for uncertain analysis of LSP and regional landslide risk management.

Pengaruh Spesialisasi Auditor, Audit Tenure, Leverage dan Profitabilitas terhadap Manajemen laba pada Perusahaan Manufaktur yang terdaftar di Bursa Efek Indonesia

The purpose of testing this research is to find out whether Auditor Industry Specialization, Audit Tenure, Leverage and Profitability have an influence on the occurrence of Earnings Management in Food and Beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange during 2019 to 2021. Food and beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange which will be the focus of the population for this study and the data needed is obtained from their financial statements. Sampling was carried out using several criteria with the purposive sampling method for sample selection. Sample data obtained from 16 companies with a period of 2019 to 2021. SPSS version 26 is used for data analysis then continued with classical assumption testing then hypothesis testing with partial tests. This study found that auditor industry specialization, audit tenure, and leverage do not affect earnings management and profitability has a positive impact on earnings management.

Active learning sample selection based on multicriteria

In multivariate calibration problems, model performance is affected significantly by the calibration samples used during model building. In recent years, active learning methods have become one of the best methods for sample selection. However, most active learning methods only select instances from prediction uncertainty or sample space distance, and these single-criteria methods tend to select undesired samples. In addition, sample density characterizes the spatial information carried by the sample, but few studies in quantitative analysis utilize sample density alone to select calibration samples. Considering these issues, based on the k-means clustering algorithm, this paper proposes an active learning sample selection method (Diversity Informativeness Density Active Learning, DIDAL), which combines the three criteria of diversity, informativeness and sample density. The most representative sample is iteratively selected for - addition to the calibration set for modeling and estimating the chemical concentration of analytes. Soybean meal and soy sauce samples were analyzed by DIDAL and compared with existing sample selection methods. The prediction results show that the DIDAL algorithm significantly outperforms several existing algorithms and is close to the performance of full-sample modeling. A model with high prediction accuracy can be constructed by selecting only a few samples using the DIDAL method.

DO COMPANY PRODUCTIVITY, PRICE-EARNINGS RATIO, AND EFFECTIVE TAX RATE AFFECT FIRM VALUE?

Investors look for companies with growing firm value and are eager to know the factors that affect it. Other research that has been conducted previously relating to factors that influence company value shows different results. This is the motivation for researchers to conduct research which is a development of previous research. The purpose of this study is to obtain empirical evidence about the effect of firm size, company productivity, firm age, price earning ratio, profitability, leverage, effective tax rates, and audit quality on firm value. The sample used in this research is manufacturing companies listed on the Indonesia Stock Exchange consistently from 2016 until 2018. The sample selection method used was purposive sampling, there were 75 companies met the criteria, resulting in 225 data being taken as samples. Research data were analyzed by doing hypothesis tests using multiple regression methods to determine the model of research. The results of this study show that firm size, profitability, and leverage affect firm value. company productivity, firm age, price earning ratio, effective tax rates, and audit quality do not affect the value of the firm.

Profitabilitas, Leverage Dan Manajemen Pajak Perusahaan Manufaktur Sektor Pertambangan

<p class="JOURNALABSTRACT-KEY">Tax is a source of state revenue that supports the implementation of development and improves people's welfare. The company is one of the taxpayers who has the obligation to pay taxes in accordance with statutory provisions. However, tax for companies is a burden that will reduce net income so that many companies take tax management actions to reduce their tax obligations. Tax management carried out by the company can minimize the tax burden that must be paid by the company. This study aims to determine the effect of profitability and leverage on tax management in mining sector manufacturing companies listed on the Indonesia Stock Exchange in 2019-2021. This study uses secondary data obtained through the company's annual financial reports. The sample selection method in this study used a purposive sampling method and the sample for this study was 69 samples with observations for 3 years. Data analysis using panel data regression method. The results of this study indicate that profitability has a negative effect on tax management. The higher the profitability, the lower the tax management. While leverage has no effect on tax management.</p><p class="JOURNALABSTRACT-KEY"> </p><p class="JOURNALABSTRACT-KEY"><strong>Keywords</strong><strong>:</strong> Profitability; Leverage ;Tax Management.</p>

Comparative Analysis of Financial Performance before And during Covid-19 Pandemic

This study assesses the financial performance of technology sector firms listed on the IDX by utilizing various financial ratios, including Return on Assets, Total Assets Turnover, Current Ratio, Debt to Equity Ratio, and Sales Growth. The study employs a quantitative approach with multiple regression analysis, and the research relies on secondary data gathered from financial reports spanning from the third quarter of 2018 to the second quarter of 2021. The sample selection method employed purposive sampling, resulting in a sample size of nine companies. The normality of the data was assessed using the Kolmogorov-Smirnov method, revealing a non-normal distribution. As a result, the non-parametric Wilcoxon Signed Rank test was applied. The findings indicate significant disparities in the financial performance of technology sector companies listed on the IDX before and during the Covid-19 pandemic, particularly in metrics such as Total Assets Turnover, Current Ratio, Debt to Equity Ratio, and Sales Growth. However, the Return on Assets variable did not significantly differ before and during the Covid-19 pandemic. These insights can be valuable for stakeholders such as investors, creditors, and regulators in comprehending the associated risks and potential impacts when considering investment or extending credit to these entities

The Relationship Between Work Duration and Carpal Tunnel Syndrome in Cigarette Rolling Workers

Aims: This study aimed to identify the correlation between the length and the period of Work correlated with the incidence of carpal tunnel syndrome among cigarette rolling workers at the Breadfruit Factory. Methods: This is an analytic observational study with a cross-sectional method. It utilizes the sample selection method of purposive sampling. The information collection tool consists of questions covering personal information, length of service, and physical examination sheets. Statistical test implemented with Chi-square. Results: The number of cigarette rolling workers used as the sample for this study was 103 people. The statistical test results applying chi-square work duration obtained p-value = 0.005 (p ≤0.05), a p-value of 0.000 (p ≤0.05) was obtained for years of service, indicating a correlation between length of Work and working time with the possible occurrence of Carpal Tunnel Syndrome (CTS) in workers. Conclusion: There is a significant correlation between length of Work and duration of Work on the emergence of CTS symptoms. As a form of prevention, occupational health and safety nurses can provide adequate education to cigarette companies to pay attention to employee conditions and the possibility of health problems occurring for their employees.