Value Of Test Statistic Research Articles

An Evaluation Model of Plant Variety Rights Capitalization Operation Value Based on Big Data Analysis

Plant variety rights are essential for agricultural development and food security. This paper mainly starts with the cost-benefit issue of plant variety rights that enterprises are concerned about, and introduces the cost-benefit analysis method into the research and development, application, and protection of plant variety rights. This research takes the new plant variety rights as the research object, clarifies the development status of the world plant variety rights from the perspective of time series development characteristics and spatial distribution pattern, explores the location of the variety rights in the world, and uses methods such as knowledge measurement and data mining, to carry out in-depth research on the application and authorization of plant variety rights, the scope of protection catalogues, the structure of variety rights, and the applicant unit. Finally, the regression model is tested from five aspects: regression model significance test, model goodness-of-fit test, Hosmer goodness-of-fit test, goodness-of-fit test, and overall accuracy test of model prediction. The regression coefficient of plant variety rights cooperation in the research process was 1.908, and the statistical test value was significant at the 5% level ( P = 0.022 < 0.05 ). Using system dynamics to evaluate its risks, it provides new ideas for the risk analysis and prevention of seed industry enterprises’ variety rights capitalization operation.

What is the value of statistical testing of observational data?

Statistical analysis of medical data aims to reveal patterns that can aid in decision making for future cases and, hopefully, improve patient outcomes. Large and bias-free datasets, such as those produced in formal randomized clinical trials, are necessary to make such analyses as reliable as possible. For a host of reasons, randomized trials are, unfortunately, relatively uncommon in veterinary medicine and surgery, implying that less ideal datasets (mostly observational data) must form the basis for much of our decision making regarding treatment of individual patients under our care. In this review, we first describe the common shortcomings of many observational veterinary datasets when viewed in comparison with their optimal counterparts and highlight how the deficiencies can lead to unreliable conclusions. We illustrate how many of the interpretative problems associated with observational data, predominantly various forms of bias, are not solved, and may even be exacerbated, by statistical analysis. We emphasize the need to examine summary data and its derivation in detail without being lured into relying upon P values to draw conclusions and advocate for completely omitting statistical analysis of many observational datasets. Finally, we present some suggestions for alternative statistical methods, such as propensity scoring and Bayesian methods, which might help reduce the risk of drawing unwarranted, and overconfident, conclusions from imperfect data.

Pengaruh Edukasi Kesehatan Obesitas Melalui Audio Visual Aid (AVA) terhadap Perilaku Pasien Obesitas di Wilayah Puskesmas Melayu Kota Piring Kota Tanjungpinang

Background of Study: Obesity is an excessive accumulation of fat due to an imbalance of energy intake with energy used for a long time and has an impact on health problems and decreased quality of life. Health education using audio visual aid (AVA) can improve behavior change in obese patients towards a better understanding of health. This study aims to determine the effect of health education through audio visual aid (AVA) on behavioral changes in obese patients in Puskesmas Melayu Kota Piring.Methods: This research used Pre-experimental research design with One Group Pretest Post-test design. There were 20 respondents for sampling. The instrument data used questioner to measure knowledge, attitudes and actions about behavior change. Analysis data used Wilcoxon statistical test.Results: For statistical test knowledge indicators p-value = 0.055 (˃0.05), this showed that the alternative hypothesis (Ho) was rejected. As for the attitude indicator, the statistical test value of p-value = 0.025 (˂0.05) and the indicator of statistical test action p-value = 0.004 (˂0.05), this showed that the alternative hypothesis (Ha) was accepted. Conclusion: Health education through audio visual aid (AVA) can influence the behavior of obese patients.Keywords : health education, audio visual aid (AVA), obesity

Analysis of University Teaching Evaluation in the Era of BD

College teaching evaluation is an important part of teaching because it not only summarizes the semester's teaching results but also guides the next semester's teaching. However, with the implementation of China's quality-oriented education reform and the arrival of the era of big data (BD), new requirements for college teaching evaluation are being put forward, which also brings many reform conditions. Teaching evaluation in the traditional sense is typically based solely on the course's student scoring data. This method is based on a single data source and thus cannot evaluate the teaching effect comprehensively, objectively or fairly. To address this issue, a teaching evaluation method in colleges and universities operating within the BD environment is proposed. This paper investigates college and university teaching evaluation in the post-BD era. The observed value of the Bartlett sphericity test statistic is 6619.943, and the corresponding probability p is nearly equal to 0. If the significance level an is 0.05, the null hypothesis should be rejected because the probability p is less than the significance level a, indicating that the correlation coefficient matrix cannot be the unit matrix. This also implies that there must be some correlation between the original variables, making factor analysis possible. BD can combine scattered and single evaluation data to create continuous and systematic data. BD can provide a large amount of data support for teaching evaluation, making it more scientific and fair; at the same time, driven by BD, teaching evaluation can return the results of teaching evaluation more quickly.

Designing a New Lightweight AES Algorithm to Improve the Security of the IoT Environment

Recently, the Internet of Things (IoT) is begin used in many fields such as smart homes, healthcare systems, industrial applications, etc. Therefore, the use of the IoT led to a growth in the number of dangers especially in the areas of privacy and security for applications running on low-resource computers. Consequently, the demand for lightweight encryption methods is growing. To safeguard sensing data, this study introduces a Lightweight Advanced Encryption Standard (LAES) depending on dynamic ShiftRows, initial permutation instead of MixColumns, and a dynamic number of rounds. It was created with the goal of reducing encryption/decryption time. The proposed approach was assessed by using various measurements such as lengths of the key used was 2128 and it is quite enough for security, key sensitivity values were 100%, Also, this study compared the encryption/decryption time, NIST statistical test, and security strength of the proposed architecture to those of XTEA, SIMON, Skinny, SPECK, and PRESENT. The encryption/decryption time of the proposed approach was had the shortest period (0.0169 S) while the SPECK algorithm was had the longest period (4.1249 S) among the comparative algorithms. Whereas, NIST statistical test values of the proposed approach were passed successfully and had higher values than the comparative algorithms. Moreover, the proposed approach utilized 1280, 1024, and 768 GE with 6, 8, or 10 rounds respectively. The average number of GE was approximately 1000 GE. These numbers of GE are considered highly efficient with the IoT environment. Index Terms— IoT, AES, Lightweight systems, Chaotic systems, Cryptography.

Spatial Regression Analysis of 2020 Pulmonary TB Cases in North Sumatra Province

Tuberculosis is a disease caused by a contagious infection of the bacterium Mycobacterium tuberculosis which is transmitted through droplets in the air. Based on information from the Indonesian Ministry of Health, there has been an increase in cases since 2017 by 254 cases per 100,000 population, in 2018 250 cases per 100,000 population and in 2019 to 254 cases per 100,000 population in Indonesia. Based on a report from the Central Statistics Agency of North Sumatra, in 2018 cases of pulmonary TB in North Sumatra Province as a whole reached 23,237 cases, while in 2020 there were around 33,779 cases of the spread of this disease. This indicates an increase in cases of 10,542 cases in the span of two years. This study aims to provide an overview related to the distribution pattern of the number of pulmonary TB patients in the North Sumatra Province area by utilizing technology based on geographic information systems using spatial statistical regression method. The applications used in this processing include ArcGIS in processing data and GeoDa in regression analysis. The results showed that there was a correlation between the population density variable between regions and the level of pulmonary TB sufferers in North Sumatra. Based on the test statistic value in the Spatial Autoregressive Model is 2.5634 with a p-value of 0.473466 indicating the decision to reject H0 which states that there is a spatial dependence between regions with population density variables and the high and low cases of pulmonary TB that occur in districts and cities in North Sumatra Province and supported with the results of the autocorrelation Moran's I index obtained is 0.268999 with a p-value of 0.000001 so that it shows that there is a positive spatial autocorrelation.

The Effect of Teacher Communication Through Storytelling Method on the Creativity Level of Kindergarten Students in Bekasi City

Background - Children's creativity can be increased through learning methods. Creativity in kindergarten student learning aims to develop students' curiosity and develop their imagination. It is suspected that teacher communication in telling a story using the storytelling method will help increase student creativity in Kindergarten in the city of Bekasi.
 Purpose – This study aims to: 1) analyze the effect of teacher communication variables on the creativity level of kindergarten students in Bekasi City. 2) analyze the storytelling method variable as a mediator variable between teacher communication and students' creativity level.
 Design/methodology/approach – The research method uses the quantitative-correlation method, namely calculating the relationship between variables using the SPSS application and the Sobel calculator to calculate the mediator variable, whether it can be used as a mediator variable after being calculated by using a Sobel calculator. The population of this study was kindergarten students in Bekasi City who were taken randomly. The research sample was determined in kindergarten schools using the storytelling method as a learning method. Randomly selected, namely private kindergarten "Islam Mentari" and Islamic kindergarten "Gema Nurani". Of the two kindergartens, the respondents were parents of students from the two kindergartens. as many as 60 parents of students, namely 30 parents of Mentari Islam students, and 30 parents of "Gema Nurani" students..
 Findings – The results showed 1) there was an influence of teacher communication variables on the creativity level of kindergarten students in Bekasi City. The value of R = 0.381, and R² = 0.145, so it can be said that teacher communication contributes to the storytelling method by 14.5%. This means that there is an influence of teacher communication of 14.5%, and the remaining 85.5% is influenced by other variables not examined in this study 2) there is an effect of teacher communication on the level of creativity of students, and the storytelling method as a mediator is significant at the level of p = 0.05. Results of the Sobel Calculator calculation, can be explained that the Sobel test value is test statistic value = 2.080, standard error value = 0.090, P-value = 0.038. it can be seen that the value is 2,080 > p-value = 0.038, meaning that the Sobel Test calculation shows a significant level of = 0.05, indicating that the Storytelling method can be a mediator variable. This means that the test results show that the storytelling method can be a mediator variable in research between teacher communication variables and students' creativity levels.
 Limitations– there are limitations of researchers when taking data into the field, then it is done using google form. In addition, the limitations of this study were that it was conducted in kindergarten schools in 2 private kindergartens..
 Originality/value – This research can be trusted as the researcher's original research and case selection in kindergarten schools using the storytelling method

Testing for time-varying factor loadings in high-dimensional factor models

This paper proposes a test for structural changes in factor loadings in high-dimensional factor models under weak serial and cross-sectional dependence. The test is an aggregate statistic in the form of the maximum of the variable-specific statistics whose asymptotic null distribution and local power property are studied. Two approaches including extreme value theory and Bonferroni correction are adopted to compute the critical values of the aggregate test statistic. Monte Carlo simulations reveal the non-trivial power of the proposed test against various types of structural changes, including abrupt changes, nonrandom smooth changes, random-walk variations and stationary variations. Additionally, our test can be more powerful than some alternative tests in the considered scenarios. The usefulness of the test is illustrated by an empirical application to Stock and Watson’s U.S. data set.

Association between Mycobacterium tuberculosis genotype and diabetes mellitus/hypertension: a molecular study

BackgroundA paucity of studies focused on the genetic association that tuberculosis (TB) patients with non-communicable diseases (NCDs) are more likely to be infected with Mycobacterium tuberculosis (MTB) with more potent virulence on anti-TB drug resistance than those without NCDs. The study aimed to document the predominant genotype, determine the association between MTB genotypes and NCD status and drug resistance.MethodsWe conducted a molecular study in 105 TB patients based on a cross-sectional study focused on the comorbid relationship between chronic conditions and TB among 1773 subjects from September 1, 2019 to August 30, 2020 in Guizhou, China. The participants were investigated through face-to-face interviews, followed by NCDs screening. The DNA of MTB isolates was extracted prior to genotyping using 24 loci MIRU-VNTR. The subsequent evaluations were performed by phylogenetic trees, combined with tests of statistical power, Chi-square or Fisher and multivariate logistic regression analysis.ResultsThe Beijing family of Lineage 2 (East Asia) was the predominant genotype accounting for 43.8% (46/105), followed by Lineage 4 (Euro-America) strains, including Uganda I (34.3%, 36/105), and the NEW-1 (9.5%, 10/105). The proportion of Beijing strain in patients with and without NCDS was 28.6% (8/28) and 49.4% (38/77), respectively, with a statistical power test value of 24.3%. No significant association was detected between MTB genotype and NCD status. A low clustering rate (2.9%) was identified, consisting of two clusters. The rates of global, mono-, poly- and multi-drug resistance were 16.2% (17/105), 14.3% (15/105), 1.0% (1/105) and 4.8% (5/105), respectively. The drug-resistant rates of rifampicin, isoniazid, and streptomycin, were 6.7% (7/105), 11.4% (12/105) and 5.7% (6/105), respectively. Isoniazid resistance was significantly associated with the Beijing genotype of Lineage 2 (19.6% versus 5.1%).ConclusionsThe Lineage 2 East Asia/Beijing genotype is the dominant genotype of the local MTB with endogenous infection preponderating. Not enough evidence is detected to support the association between the MTB genotype and diabetes/hypertension. Isoniazid resistance is associated with the Lineage 2 East Asia/Beijing strain.

How to Cariogenic Food Habits in Children aged 9-10 Years? -Caries Severity Index (CSI)

Caries in children is higher than caries in adults. The factor that causes the high caries rate in children is the dietary factor. Cariogenic foods are foods that contain lots of carbohydrates, are sticky and break easily in the mouth. Objective: This study aims to determine the relationship between food of cariogenic to caries severity index (CSI) child of age 9-10 years. Methods: Type of Research is descriptive with device of cross sectional, date which is concerning free variables and the variable trussed will be collected during which at the same time. Subject of Research as much 65 children, have age 9-10 years old. instrument using Food of cariogenic measured by Dietary is Recall Method and for measurement hard; level of caries after conducted by inspection tooth and mouth measured to use caries severity index (CSI). The Result of statistical analyzes with Chi square to know relationship between food of cariogenic to caries severity index (CSI). Results: The results of obtained by statistical test value of p-value p=0,000 according to statistics very have a meaning at storey; level of belief 95% by 0.05. Because p-value < 0.05 inferential hence there is relation between child consuming food of cariogenic hardly caries that happened at child of age 9-10 year. Result of obtained by statistical Analysis of value OR = 29,714 by 95% confidence of international 6,816- 129.540 of its meaning that child. Conclusion: there is a significant relationship between cariogenic food habits and caries severity index (CSI) children of age 9-10 years

GeV γ-Ray Emission of Compact Steep-spectrum Source 4C +39.23B

Abstract Thirteen yr observation data of 4FGL J0824.9+3915 with the Large Area Telescope on board the Fermi Gamma Ray Space Telescope (Fermi/LAT) are analyzed for revisiting whether 4C +39.23B, a compact steep-spectrum (CSS) source close to a flat-spectrum radio quasar (FSRQ) 4C +39.23A in the γ-ray emitting region of 4FGL J0824.9+3915, is a γ-ray emitter. We find that the time-integrated γ-ray emission of 4FGL J0824.9+3915 is overwhelmingly dominated by 4C +39.23A. It shows significant variability at a 6.7σ confidence level and the average γ-ray flux in the 0.1–300 GeV energy band is (1.60 ± 0.15) × 10−8 ph cm−2 s−1 with a power-law photon spectral index of 2.48 ± 0.05. During MJD 57500–58500, 4FGL J0824.9+3915 is in a low state with a steady γ-ray flux. Through the analysis of the Fermi/LAT observation data in this time interval, it is found that the test statistic values of the γ-ray emission from 4C +39.23A and 4C +39.23B are ∼5 and ∼31, respectively, indicating that the γ-ray emission in this time interval is dominated by CSS 4C +39.23B. The derived average flux in this time interval for 4C +39.23B is (9.40 ± 4.10) × 10−9 ph cm −2 s−1 with Γ γ = 2.45 ± 0.17. Attributing the spectral energy distribution (SED) of 4C +39.23B to the radiations from its core and extended region, we show that the SED can be represented with a two-zone leptonic model. Its γ-ray emission is contributed to by the core region. The derived magnetic field strength and Doppler boosting factor of the core are 0.13 G and 6.5. Comparing 4C +39.23B with other γ-emitting CSSs and compact symmetric objects (CSOs) in the Γ γ − L γ plane, it resembles CSSs.

Using Weighted Differences in Hazards as Effect Sizes for Survival Data

Sensitive to the change in sample sizes, traditional measures such as values of test statistics or p values can fail to quantify the difference in survival between populations for time-to-event data. We thereby propose to use effect sizes defined as the weighted differences in hazards to evaluate the survival difference between two groups. On the basis of the logrank test statistic, Gehan–Wilcoxon test statistic and Prentice–Wilcoxon test statistic, we developed three effect sizes that compare the survival experiences over the time period of investigation. Estimates of these three effect sizes were provided and their large sample behaviors were studied. In light of the Mann–Whitney parameter, we presented an effect size that compares the survival experiences over the entire possible/hypothetical time period. Two estimates of this effect size were constructed. We compared the proposed effect sizes and illuminated their use by theoretical studies, simulations and real cancer data. The effect sizes proposed in this article can help understand the survival difference in populations and are expected to have promising applications in the field of survival analysis.

Analysis of 16S rRNA sequencing in advanced colorectal cancer tissue samples.

163 Background: Changes in the colon’s microbiota composition are contributors to the pathogenesis of colorectal cancer (CRC). Features of this microbiome may have prognostic significance. For this study, we analyzed 16S rRNA sequencing data from tumor tissue samples of advanced CRC patients and determined if there were potential correlations between microbiome composition and clinical outcomes. Methods: One hundred and thirty three advanced CRC patients in St. Vincent’s Hospital in Korea were enrolled. DNA was extracted from collected tissue samples, the V3-V4 regions were amplified, and a 16S rRNA gene amplicon library was prepared using an Illumina protocol. DNA was sequenced on an Illumina MiSeq instrument. We used three different bioinformatic packages to process the sequence data and evaluate the microbiome composition of each tumor. Results: The classification performances of three different analytic pipelines (Kraken2, QIIME2, and DADA2) were compared in a microbiome control sample. Among these, DADA2 and QIIME2 were chosen for use in subsequent analysis, due to their lower Chi-square (χ2) test statistic values on the control data. After excluding samples that retained less than 5% of total reads after merging, 120 samples were analyzed. The median age of the cohort was 63 years, 63.3% were male, and all were Korean. The distribution over primary sites was 27.5% from the right-side colon, 30.8% from the left-side colon, and 41.7% from the rectum. All subjects received the first line of systemic treatment. The median progression-free survival time was 8.9 months. Twenty-nine patients (24.2%) survived more than 24 months. When examining the results from the two bioinformatic packages, pairwise comparisons showed positive correlations in the relative abundances of the top 20 genera. Fusobacterium, a microbe known to relate to pathogenesis and prognosis of CRC, was not detected by QIIME2. Stratifying by primary site, rectal cancers showed higher alpha diversity than left- or right-side colon cancers. Separately, a higher serum CEA level (≥8) at diagnosis, and the presence of lung metastasis were both found to be related to higher alpha-diversity, a global indicator of microbiome composition. When excluding minimally abundant (< 1% per patient) genera, beta-diversity was found to be differentiable by T stage, the presence of lung metastasis, and the presence of liver metastasis. Most notably, beta-diversity differed between patients who survived more than two years and patients who died within 2 years. Using the DADA2 results, we confirmed that the presence of Fusobacterium nucleatum in CRC tissue was found to be a strong predictor of poor overall survival (OS), along with old age and liver metastasis. Conclusions: This study suggests potential associations between microbiome composition and clinical parameters of advanced CRC. Microbial biomarkers may be a valuable prognostic tool in this population.

Detection of Gamma-Rays from the Protostellar Jet in the HH 80–81 System

Considering that the existence of relativistic particles in the protostellar jet has been confirmed by the detection of linearly polarized radio emission from the HH 80–81 jet, we search for gamma-rays from the HH 80–81 system using ten-year Fermi-LAT observations. A significant point-like γ-ray excess is found in the direction of the HH 80–81 system with the Test-Statistic value >100, which is likely produced in the HH 80–81 jet. The γ-ray spectrum extends only to 1 GeV with a photon index of 3.5. No significant variability is found in the gamma-ray emission. It is discussed that the properties of HH 80–81 jet suffice for producing the observed γ-rays.

CLASSICAL GUIDANCE SERVICES USING WINDOW SHOPPING METHOD TO IMPROVE READING COMPREHENSION OF VOCATIONAL SCHOOL COUNSELORS

This study aimed to test the effectiveness of classical guidance services using window shopping methods to improve reading comprehension of vocational school counselors. This research was an experimental study with one group pretest-posttets design. Research subjects were vocational school counselors in East Jakarta. The population in this study were all vocational school teachers, as training participants with a total of 30 people. The sampling technique used was 30 saturated sampling. The research instrument used was a reading comprehension scale with a validity of 0.304 (Pearson Product Moment) and reliability of 0.826 (Alpha Cronbach). Data analysis techniques using paired sample t-test were significant with a statistical test value of -65.619. The results of the study provide an understanding that classical guidance services with the window shopping method was effective in improving reading comprehension of the vocational school counselors.

Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model

This article investigates two test statistics for testing structural changes and thresholds in predictive regression models. The generalized likelihood ratio (GLR) test is proposed for the stationary predictor and the generalized F test is suggested for the persistent predictor. Under the null hypothesis of no structural change and threshold, it is shown that the GLR test statistic converges to a function of a centered Gaussian process, and the generalized F test statistic converges to a function of Brownian motions. A Bootstrap method is proposed to obtain the critical values of test statistics. Simulation studies and a real example are given to assess the performances of the proposed tests.

A hybrid multifactorial evolutionary algorithm and firefly algorithm for the clustered minimum routing cost tree problem

The clustered minimum routing cost tree (CluMRCT) problem is a recent problem with a wide range of real-life applications, especially in designing computer networks with peer-to-peer architecture. Many multifactorial evolutionary algorithms have been proposed to solve multiple CluMRCT problems simultaneously. However, these algorithms only function effectively on complete graphs with small-and-medium sizes. Moreover, the blindness and randomness in the transfer of genetic materials cause a reduction in the exploitation ability and make these algorithms ineffective to solve low-similarity tasks. This paper proposes a hybrid multitasking algorithm named multifactorial firefly algorithm, which integrates the firefly algorithm’s strong exploitation ability to enhance the self-evolution of each task when facing low-similarity tasks while improving inter-task knowledge transfers by delivering higher-quality solutions. Also, the proposed algorithm is equipped with new encoding and decoding to focus more on potential search areas on both complete and sparse graphs. The experiments and Wilcoxon signed-rank tests were conducted on various instances to verify our proposal with several state-of-the-art methods. The results portrayed that the proposed encoding scheme helped multitasking algorithms improve solution quality by 32% on average. Besides, the statistical test values proved the superiority of the proposed hybrid algorithm in terms of solution quality and convergence trend.

The effect of latent and error non-normality on corrections to the test statistic in structural equation modeling

In structural equation modeling, several corrections to the likelihood-ratio model test statistic have been developed to counter the effects of non-normal data. Previous robustness studies investigating the performance of these corrections typically induced non-normality in the indicator variables. However, non-normality in the indicators can originate from non-normal errors or non-normal latent factors. We conducted a Monte Carlo simulation to analyze the effect of non-normality in factors and errors on six different test statistics based on maximum likelihood estimation by evaluating the effect on empirical rejection rates and derived indices (RMSEA and CFI) for different degrees of non-normality and sample sizes. We considered the uncorrected likelihood-ratio model test statistic and the Satorra–Bentler scaled test statistic with Bartlett correction, as well as the mean and variance adjusted test statistic, a scale-shifted approach, a third moment-adjusted test statistic, and an approach drawing inferences from the relevant asymptotic chi-square mixture distribution. The results indicate that the values of the uncorrected test statistic—compared to values under normality—are associated with a severely inflated type I error rate when latent variables are non-normal, but virtually no differences occur when errors are non-normal. Although no general pattern regarding the source of non-normality for all analyzed measures of fit can be derived, the Satorra–Bentler scaled test statistic with Bartlett correction performed satisfactorily across conditions.

THE IMPACT OF GENDER GAP INTO HOURLY WAGES: A STUDY BASED ON PRIVATE SECTOR COMPANIES IN SRI LANKA

Most of the researchers are examining the wage gap between males and females. Most number of researchers is saying that many firms have this kind of issues regarding the gender gap impact into hourly wages. As a third world country, it is very important to examine the impact of gender gap into hourly wages in Sri Lanka. In this study the researcher has used a sample of three thousand employees of private sector companies in Sri Lanka to evaluate the salary difference of males and females. The data has been collected by using a questioner through online method. Working hours, income and other demographic information were collected for the analysis. Different statistical methods were used to evaluate the data. According to this study, the test p-value is higher than the 0.05 significance value. Mean hourly wage of the men and female around 524 and 550 accordingly. According to the test statistic values, the hourly wage of men and female are different, and according to the mean values of the two groups, women earn morethan men.

Analisis Kandungan Karbon pada Vegetasi Mangrove di Desa Lembar Kabupaten Lombok Barat

The mangrove ecosystem is one of the vegetation that has a role as carbon mitigation in coastal areas, especially in port activity areas that can produce large amounts of carbon, such as in Lembar Harbor, Lembar Village, West Lombok Regency. The purpose of this study was to analyze the carbon content in the root and leaf tissue contained in each type of mangrove in the Lembar Harbor Area, Lembar Village, West Lombok Regency. This type of research is descriptive quantitative, with purposive random sampling method, which starts with taking root and leaf samples on each different mangrove species, and testing is carried out based on the Walkley & Black method to obtain tissue carbon content. Based on the results of the study, found 8 (eight) families consisting of 11 species, including: Avicennia lanata, Avicennia marina, Lumnitzera racemosa, Bruguiera gymnorrhiza, Rhizophora stylosa, Ceriops decandra, Scyphiphora hydrophyllaceae, Excoecaria agallocha, Thespesia populnea, Xylocensis, and Ipome pescaprae. The condition of the environmental parameters of the mangrove ecosystem in Lembar Village is still in good condition, in accordance with the quality standards of water health quality, Decree of the State Minister of the Environment Number 51 of 2004 concerning sea water quality standards for biota. The average organic carbon content of root tissue was 43.47 ± 3.10 %C and leaves was 43.87 ± 3.66 %C. The highest organic carbon content in root tissue was found in Xylocarpus moluccensis (47.46 %C), and the lowest was in Ipomea pescaprae (41.49 %C), while the highest organic carbon content in leaf tissue was in Bruguiera gymnorrhiza (50.60 %C), and the lowest was Avicennia lanata (38.99 %C). Based on Tukey's further test that the value of organic content stored in the root and leaf tissue of mangroves was not significantly different (> 0.05) with a statistical test value of 0.76.