Analisis Pengaruh Efektivitas Penerapan Sistem Manajemen Keselamatan Dan Kesehatan Kerja (SMK3) Terhadap Produktivitas Kerja Karyawan (Studi Kasus Plant 11 PT Indocement Tunggal Prakarsa, Tbk Citeureup)

Employee is an important resource to have production process in a big factory. Factory couldn\u27t operate without employee. To protect their employees, the leader makes a policy like occupational health and safety. This policy for protect their employee from risk of bad accident and illness that causes of work. Bad accident can strike employee anywhere and anytime so this cases must to have a special attention. So, the leader, government, and management must pay attention to this risk. Work accident leaning influence to manpower productivity because quality of work life and guarantee of occupational health and safety influence manpower productivity. PT Indocement Tunggal Prakarsa, Tbk is one of the biggest cement factories in Indonesia. This factory has applicated occupational health and safety assessment base on Permenaker No. 05/MEN/1996 and OHSAS 18001. Occupational health and safety effectiveness can describe by six aspect based on Miner Theory. That theory are safety training, safety publication, control to work environment, inspection and discipline, improvement awareness of occupational health and safety, report and statistic of occupational health and safety. Five aspect of Theory Miner, can describe by employee perspective, even report and statistic of occupational health and safety can describe by secondary data from Safety Department and Management Representative of PT ITP

Mean number of <i>Ae</i>. <i>albopictus</i> eggs per trap per week (black line), <i>Ae</i>. <i>albopictus</i> females per trap per day (grey area) in 24 BGs and 24 ovitraps positioned in 8 locations in Montpellier in 2014.

<p>Autochthonous chikungunya transmission period (green line); weekly bounded accumulated Growing Degree Days (red line); weekly rainfall (black bars).</p

Characteristics of microsatellites used for the assessment of the genetic structure of <i>Aedes albopictus</i> in La Réunion Island.

<p>N_A, number of alleles.</p><p>F<i>_is</i>, imbreeding coefficient (Weir & Cockerman).</p><p>P, probability for departure from Hardy-Weinberg proportions.</p

Number of multiple inseminations in 27 female <i>Aedes albopictus</i> from La Reunion Island.

1<p>Number of females with no more alleles detected in pools of progeny than would be consistent with the hypothesis that all shared a single father.</p>2<p>Number of females with alleles detected in pools of progeny consistent with the hypothesis of at least two fathers.</p

Graphical representation of the model.

<p>Cattle population is divided into susceptible (<i>S</i>), incubating (<i>E</i>), viraemic (<i>I</i>) and immune (<i>R</i>) individuals in each village. Two populations per village were considered depending on whether or not animals are exposed to the barter practice. Mosquito population is divided into nulliparous (<i>N</i>), parous and non-infected (<i>S</i>), parous and infected, but non-infectious (<i>E</i>, during the extrinsic incubation period), and parous, infected and infectious (<i>I</i>, after the end of the extrinsic incubation period) in each rice field. Full dark arrows represent transition from on state to the other. Full thin arrows represent demographic processus of birth and death specific to both metapopulation. Dotted lines represent infection dynamics. The full description of the parameters can be found in S1 Text. : force of infection due to direct transmission into village v, : force of infection due to vector based transmission into village v, : average force of infection due to vector based transmission into villages accepting the barter into village v (See S1 Text for development of force infection expressions related to cattle exchange practices), : force of infection for mosquitoes of rice field r.</p

Figure 1

<p>1A. Number of progeny (L3 larvae) from the 3 females inseminated by at least two males during the 1^st field sampling. Differences in color (white/black) represent the distribution in the number of larvae coming from one male or from more than one male. 1B. Number of progeny (L3 larvae) from the 4 females inseminated by at least two males during the 2^nd field sampling. Differences in color (white/black) represent the distribution in the number of larvae coming from one male or from more than one male. A Chi-square test was performed to test the distribution of sperm coming from male 1 or male 2 between the first and the second egg laying. The 4th female laid only one time. N = number of larvae;, Df = Degree of freedom; N.S. = Non Significant.</p

A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France-2

<p><b>Copyright information:</b></p><p>Taken from "A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France"</p><p>http://www.malariajournal.com/content/7/1/147</p><p>Malaria Journal 2008;7():147-147.</p><p>Published online 1 Aug 2008</p><p>PMCID:PMC2527012.</p><p></p

Weighted values of model parameters for model M3 (direct transmission when viraemic cows calve and residual mosquito population in winter) and an introduction of RVFV on 2007-09-01 (weight: 0.73) or on 2007-10-01 (weight: 0.24).

<p>Weighted values of model parameters for model M3 (direct transmission when viraemic cows calve and residual mosquito population in winter) and an introduction of RVFV on 2007-09-01 (weight: 0.73) or on 2007-10-01 (weight: 0.24).</p

A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France-0

<p><b>Copyright information:</b></p><p>Taken from "A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France"</p><p>http://www.malariajournal.com/content/7/1/147</p><p>Malaria Journal 2008;7():147-147.</p><p>Published online 1 Aug 2008</p><p>PMCID:PMC2527012.</p><p></p

Weighted prediction of the number of animals infected by direct transmission, when viraemic cows calve, and by vector-borne transmission, according to the season (dry and cold season, May-September, wet and warm season: October-April).

<p>Weighted prediction of the number of animals infected by direct transmission, when viraemic cows calve, and by vector-borne transmission, according to the season (dry and cold season, May-September, wet and warm season: October-April).</p