THE PERFORMANCE OF HIGH RESOLUTION NEUTRON POWDER DIFFRACTOMETE

INTRODUCTION

To handle or minimize the occurrence of an increase in work accidents in Indonesia and ensure that the company is capable of OHSM, which refers to PP no. 50 of 2012, where every company is required to implement OHSM. To carry out government efforts by reducing the occurrence of work accidents in the workplace and ensuring this, the company must do OHSM in the company. In addition, the achievement of companies in establishing a functional, systematic occupational health and safety management (OHSM) system varies (Nordlï¿½f, Wiitavaara, Hï¿½gberg, & Westerling, 2017).

PT Indonesia Comnets Plus (ICON+) is one of the subsidiaries of PT PLN (Persero) whose work is a high risk, where the scope of work is to install Fiber Optic cables in high-voltage and low-voltage areas as well as at high altitudes, such as in PT PLN (Persero) Groups, PT Pertamina (Persero), PT Transport Gasi Indonesia, and other state-owned companies. The job is a job that has a very high job risk. PT Indonesia Comnets Plus has committed and will implement the OHSM system with this work.

ICON+ has started the application of OHSM from 2017 to 2019 and got an achievement score on 166 criteria, 85.7% achieved a Gold Certificate, which the Ministry of Manpower and Transmigration ratified. The implementation has not gone well in the company, where the programs that will run are part of the effort to fulfill the safety and safety management criteria that must be met. In fulfilling the evidence document, PT Indonesia Comnets Plus has only achieved a minimum score of 166 criteria. From the evidence that has been fulfilled, it is still only 70 pieces of evidence. There are still 94 pieces of evidence that have not been met, and to get a certificate of gold value (gold certificate), one must fulfill all the evidence.

Over time the implementation of OHSM in 2017-2019 ICON+ has an increase in work accident cases. In the accident case data obtained as follows: zero (0) cases in 2017 as many as 1 (one) case in 2018, and in 2019 as many as 4 (four) cases of these cases have identified and shown that the cause is the result of Human error.

In connection with the above, in making decisions, supervisors in the field are still not firm in implementing OHSM implementation in field. Moreover, the construction sector is one of the most important contributors to gross domestic product (GDP) in most industrialized countries, and it also has a substantial impact on worker health and safety (Yoon et al., 2013). In carrying out and implementing OHSM accurate and firm decisions are also needed to maximize the application of OHSM in the company because there is still leeway from field supervisors and management in implementing OHSM in the field.

Based on the problems above, it will also affect how disciplined we are in following the applicable procedures, both the correct use of PPE the fulfillment of work documents, there is also much fulfillment of work documents that are not following their work, and this also violates the operational standards that have been set. Determined, this lack of discipline is also due to the lack of firm leadership in decision-making on the application of OHSM, so that many workers in the field will also feel that their supervision is still lacking and make field workers violate discipline, this can be seen from the inspection data in the field, it turns out that there are still many undisciplined workers.

The above problems will impact the attitude of workers in the field because of the lack of disciplined workers, making workers do work with an unsafe attitude, which endangers workers in doing their work. This problem can also be seen from the number of workers who do work using safety belts, even though in the regulations safety belts are no longer allowed to be used and what should be used is a full-body harness double screened, this also reflects that the attitude of workers towards the rules that their supervisors do not confirm feels lenient and does not comply with the work rules and the use of PPE.

From the attitude problem above, it cannot be separated from the problem of workers' knowledge in implementing OHSM in the field, from the socialization data that ICON+ itself has carried out, it turns out that the knowledge of workers in doing work and also the knowledge related to standard operating procedures is still poorly understood, both in terms of implementation and procedures for its application, This problem can be seen from some of the Job Safety Analysts that have been done or fulfilled by workers, it is still not understood how the filling should be done and how to identify hazards that should be done when supervisors or workers find a source of danger. This can also be seen from the job reporting inputted into the application that attaches the type of work or job status Open and Close, not recorded or reported in whole or 100%. This shows that workers still do not understand what the report means.

This problem is also supported by research that supports the assessment of attitudes towards implementation and decision-making based on commitment, that employee attitudes towards OHSM commitment are very supportive or significant positiveï¿½ (Oktorita, Rosyid, Lestari, & Mada, 2015), in contrast to the results of the following research. Namely, two indicators affect knowledge of OSH, OSH training and OHSM, which have an insignificant negative influence on unsafe work attitudes (Syamtinningrum, 2017).

Based on the phenomena above and the theoretical gap above, it can be seen that the problems contained in ICON+ are seen from the level of discipline that is still lacking so that the implementation of the OHSM program does not go well, and decision making in carrying out supervision is also still not being implemented. The attitude of workers who do not comply in the use of appropriate PPE, as well as in providing reporting on work that is not carried out optimally, from these problems it can also be seen that there are still many levels of knowledge among workers in carrying out the process of fulfilling Standard Operating Procedures such as completeness of Job Safety Analysis and Working permits. Who still do not understand how to fill it out. Thus implementing the work not carried out correctly.

With these problems, I am interested in taking research at ICON+, where I will also provide input to the company to achieve maximum implementation targets in occupational safety and health management, and make the author want to do research entitled "The Influence of Management Knowledge, Work Attitudes and Employee Discipline Through Decision Making on Occupational Health and Safety Management at PT Indonesia Comnets Plus.ï¿½

The objectives to be achieved in this research are:

a. To determine the effect of management knowledge variables on decision-making

b. To determine the effect of employee attitude variables on decision-making

c. To find out the effect of work discipline variables on decision-making

d. To determine the influence of knowledge management variables on occupational safety and health management

e. To determine the effect of work discipline variables on occupational safety and health management

f. To find out the effect of Decision Making Variables on occupational safety and health management

Research hypothesis:

H1:Management Knowledge Affects Occupational ï¿½Health and Safety Management.

H2:Management Knowledge affects Decision Making.

H3:Employees' Attitudes towards Decision Making.

H4:Work Discipline Against Decision Making.

H5:Work Discipline on Occupational Health and Safety Management.

H6:The Influence of Decision Making Variables on Occupational Safety and Health Management

METHOD

The study process data using the Path Analysis Method by describing causes and effects. The data used are quantitative data using questionnaires, supported by secondary and interviews and supporting data from this research.

Total sampling is a technique sampling where the number of samples is the same as the population. Reason take total sampling because the total population is less than 100. So the number of samples in this study were 98 people in one month (Sugiono, 2016).

Data collection technique

Sugiyono (2019) mentioned in terms of and ways of knowing how to collect data, and it can be done in the following ways.

a. Questionnaire

This method uses data retrieval by providing several statements to the data source as the answerer to the question.

b. Interview

It is a technique of collecting data that underlies the information about yourself or self-report obtained directly by asking the respondent directly face to face.

c. Observation

Observation is a method of collecting data by observing the research object at the research location.

Data analysis technique

1. Test Instruments and Validity

Validity is a way to consider an essential benchmark in testing the quality of the instrument as a benchmark (Azwar, 2015). Based on further developments, validity is always seen as a characteristic of test scores.

Azwar (2015) said that the validity test was high if the test was carried out with its size to give accurate results. In assessing this method, each statement item can be seen from the value in each question item for each item. A minimum requirement that is considered to have met the validity criteria is if the score or value of the discriminatory power of items is 0.3. So, between the correlations of each item with an overall score > 0.3, then the item of the instrument cannot be used as a data collection instrument.

This validity or validity test can determine to what extent the benchmark value can assess the thing to be measured. The analysis is carried out using the "product moment" correlation formula or the calculated r value:

Information:

r_xy= Correlation Coefficient Value

n = Number of respondents

X = Item Score X

Y = Total Item Score X

2. Rehabilitation Test

This rehabilitation analysis is commonly used as to whether the instrument can measure consistently. This measure can be reliable if it produces results that do not change or are regular. This rehabilitation was analyzed using Cronbach's alpha. The formula is said to be reliable if Cronbach's alpha > 0.60 (Ghozali, 2005).

This test is to find reliability with instruments whose scores have a range of values, for example, in the form of a scale of 1 - 3, 1 - 5 or 1 - 7 and so on. This formula can be written as follows:

r₁₁= Instrument Rehabilitation

kï¿½ = Large number of items

∑ï¿½ =ï¿½ Number of Item Variants

σ²_t = Total Variant

3. Hypothesis Test

In testing a suggested hypothesis and intervening, it can mediate independent of the dependent, using linear regression analysis and path analysis. Path analysis is a way of expanding multiple regression analysis, which means the use of regression analysis is used to determine the relationship between the variables used previously (Baihaqi, 2010).

In connection with this in the test that has been proposed, the researcher can use the determinant coefficient test, or it is formulated as the R2 test, and the individual parameter test is formulated as the t statistic test (Ghozali, 2005). This test is carried out using the significance level =5%. It can be said that the acceptance or rejection of this hypothesis is carried out with criteria if it is significant = 5% < of the hypothesis, it is said to have no significant or positive effect, while if it is significant = 5% of the hypothesis, it is said to have a significant positive effect.

The data that has been obtained will be processed using a desktop application for computers, namely the IBM Statistical Package for Social Sciences (SPSS). So the conclusion on the hypothesis based on the t-test can test how significant the independent is to the dependent.

The regression assessment can be estimated in a path analysis model, which is compared with the correlation matrix observed as a variable. Interpretation of the results of data processing are:

a. Direct effect: this test is carried out using the t-test to know the effect of each part of X on Z.

b. Indirect effect: this effect is used to understand an indirect relationship to the coefficient of the first path with the R2 test. The multiplication can produce a coefficient more significant than the direct relationship coefficient, which means Y is intervening.

From the explanation above, it can be concluded that the hypothesis is

a. Hypothesis: H₀: β_i = 0, meaning that each variable has no significant effect on the related variable.

b. Hypothesis: H₀: β_i ≠ 0, meaning that each variable has significant effect on the related variable.

c. If Probability > α=5% or t-statistic ≤t-table then the independent variable is not significant to the dependent variable (H₀accept, H_a reject)

d. If the probability < α=5% or t statistic > t table, then the independent variable is not significant to the dependent variable (H₀ rejects, H_a accepts).

RESULTS AND DISCUSSION

Validity test

The test is used to understand whether the questionnaire that will be compiled to the respondents is said to be valid or not. The researchers will conduct trials on 30 respondents using validity and reliability testing

S = Significant

Ns = Non Significant

Discussion

1. Influence of management knowledge on decision making

Management knowledge in decision making is based on the results of the standard coefficient with a total of 0.185 and t statistic with a total of 2.261. Because t-statistic > 1.660, the result is H₀ = rejected and H₁ = accepted, where the decision making influences decision making on PT Indonesia Comnets Plus, field workers.

Knowledge management process is a systematic approach to be managed as intellectual assets and other information that the use of knowledge is also essential to make company decisions so that this research follows the theory put forward (Nawawi, 2012).

It is appropriate that there is a positive influence on decision-making knowledge. Factors Affecting Investors In Making Securities Investment Decisions on the IDX (Septyanto Dihin, 2013).

2. The Effect of Management Knowledge on OHSM

The effect of management knowledge on OHSM based on the results of the standard coefficient is 0.139, and the t statistic is 2.061. Because t-statistic > 1.660 then H₀ = rejected, it means that management knowledge influences OHSM on ICON+ employees.

Therefore this is also in PP No. 50 of 2012, which states that when conducting and implementing OHSM, companies must have a knowledge base by participating in OHSM training.

The findings of this study are in line with research (Ahmad, et al., 2012) entitled "Knowledge, Practice Related and Attitude to Occupational Health and Safety among textile mills workers in Dera Ismail Khan that knowledge has a significant positive effect on K3.

However, the research above is not following the research (Syamtinningrum, 2017) that there is a negative effect on OSH knowledge and OHS training on OHS management.

3. Employee Attitude Towards Decision Making

The effect of employee attitudes on decision-making based on the results of the standard coefficient is 0.229, and the t statistic is 2.189. Because t-statistic > 1.660, then H₀ is accepted, meaning that the employee's attitude influences decision making on ICON+ field employees.

The research above is in line with research Mehboob (2012) that decision making is strongly influenced by several factors, namely behavior, guidance, career, aspirations, academics, education costs, location, reputation, promotion, and facilities.

Other sesearch is also in line with research Oktorita et al. (2015) that there is a positive influence between attitudes and decision making. This is stated in research through making OHSM policy commitments in organizations.

4. The Influence of Work Discipline on Decision Making

Directly work discipline on decision making based on the results of the standard coefficient is 0.398 and t statistic is 3.810. Because t-statistic > 1.660, H₀ is rejected, which means that work discipline influences decision-making for ICON+ field workers.

This research also aligns with the theory Afandi (2016) that work discipline influences decision-making.

This variable is also in line with research Ferzadiana, Ruliana and Ekonomi (2016) that there is a positive influence on work discipline on decision making that improves employee performance."ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½

5. Effect of work discipline on OHSM

The direct effect of work discipline on employee OHSM based on the results of the standard coefficient is 0.303, and the t - statistic is 3.006. Because t-statistic > 1.660, then H0 = rejected and H1 = accepted, where work discipline can directly affect OHSM on ICON+ field workers.

This research is also in line with PP No. 50. of 2012, "that there is a positive influence on the application of work discipline to OHSM, which explains that OHSM implementation must be in accordance with the formulation of policies that have been determined".

The findings of this study are also in line with research Samahati et al. (2020) with the title "The Effect of K3 and Work Discipline on Productivity of Daya Expert Employees at PT. PLN (Persero) UP3 Manadoï¿½ is a significant favorable influence on K3 with work discipline that can increase productivity.

6. Effect of decision making on occupational safety and health management

The direct effect of decision-making on OHSM based on the results of the standard coefficient is 0.638, and the t-statistic is 8.127. Because t-statistic > 1.660, then H0 = rejected and H1 = accepted, meaning that decision-making directly influences OHSM on ICON+ field workers.

The research is also following what is contained in the PP. No. 50 of 2012 that in making decisions on OHSM it also has a positive effect by paying attention to the decision-making method (Plan, Do, Check, Action).

Other research is also in line with research Riana Aprilia and Apriatni (2016) that positively influences organizational leadership in making decisions on occupational safety and health management.

7. Based on the education level

Based on the category of Education in this study obtained as follows; seen from various educational backgrounds in this study, there were two respondents in S1, 23 respondents in D3, and at the SMA/SMK (high school) education level there were 73 people, from this it can be concluded that at the S1 education level the company can better implement how to carry out supervision in the field. The company can develop job training for SMA ï¿½ S1 education levels to be more disciplined. This will also affect other levels of education with the highest number of educational backgrounds in this research. Most of the workers in the field are of high school/vocational and D3 education backgrounds, in this case, many workers are not compliant and understand how OHSM must be appropriately implemented, not only in the application of the SOP but also in the use of appropriate PPE and also the implementation of the work. Therefore, following their competence, the company can carry out consistent supervision so that field workers can do their jobs well. Thus, that the attitude of workers remains consistent in its implementation.

CONCLUSION

The results obtained in this research can be briefly described in the following conclusions.

Management Knowledge (X₁) influences Decision Making (Z) on PT Indonesia Comnets Plus field workers. This can be proven through path analysis.

Employees' attitudes (X₂) influence decision-making (Z) on PT Indonesia Comnets Plus field workers. The path analysis evidences this.

Work Discipline (X₃) influences the decision-making (Z) of PT Indonesia Comnets Plus field workers.

Management knowledge (X₁) influences the occupational health and safety management (Y) of PT Indonesia Comnets Plus field workers.

Work Discipline (X₃) influences the management of occupational safety and health (Y) of PT Indonesia Comnets Plus field workers.

Decision-making (Z) influences OHSM (Y) ICON+ field workers.

From the conclusions above, most of the influence is directed at the level of worker discipline, which has the most substantial influence among other variables, the implementation at ICON+ illustrates this, and a lack of worker discipline can indeed hinder the process of implementing the OHSM program itself because there are still many workers in the field who are still indifferent or lack good supervision so that there is a gap in the implementation of OHSM in the company. It is hope for further researchers can improve the shortcomings of this research by increasing the sample population level in the study and adding variables that have not been included in this study.

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Question Number	r-statistic	r-table	Information
1	0,646	0,361	Valid
2	0,595	0,361	Valid
3	0,361	0,361	Valid
4	0,526	0,361	Valid
5	0,745	0,361	Valid
6	0,848	0,361	Valid
7	0,566	0,361	Valid
8	0,649	0,361	Valid
9	0,726	0,361	Valid
10	0,804	0,361	Valid

Question Number	r-statistic	r-table	Information
11	0,721	0,361	Valid
12	0,662	0,361	Valid
13	0,850	0,361	Valid
14	0,809	0,361	Valid
15	0,411	0,361	Valid
16	0,725	0,361	Valid
17	0,830	0,361	Valid
18	0,428	0,361	Valid

Question Number	r-statistic	r-table	Information
19	0,598	0,361	Valid
20	0,371	0,361	Valid
21	0,812	0,361	Valid
22	0,720	0,361	Valid
23	0,744	0,361	Valid
24	0,678	0,361	Valid
25	0,598	0,361	Valid
26	0,746	0,361	Valid
27	0,580	0,361	Valid
29	0,645	0,361	Valid
30	0,431	0,361	Valid

Question Number	r-statistic	r-table	Information
31	0,758	0,361	Valid
32	0,748	0,361	Valid
33	0,810	0,361	Valid
34	0,756	0,361	Valid
35	0,617	0,361	Valid
36	0,746	0,361	Valid
37	0,556	0,361	Valid
38	0,495	0,361	Valid

Question Number	r-statistic	r-table	Information
39	0,863	0,361	Valid
40	0,964	0,361	Valid
41	0,863	0,361	Valid
42	0,964	0,361	Valid
43	0,790	0,361	Valid
44	0,964	0,361	Valid
45	0,389	0,361	Valid
46	0,964	0,361	Valid
47	0,900	0,361	Valid
48	0,900	0,361	Valid

Variable	*alpha cronbachï¿½s*	Description
Occupational Health and Safety Management	0,825	Reliable
Decision Making	0,823	Reliable
Work Discipline	0,849	Reliable
Employee Attitude	0,831	Reliable
Management Knowledge	0,954	Reliable

Coefficient^a
Model 1	Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model 1	B	Std. Error	Beta
(Constant)	14.0	2.728	-	5.159	.000
Work Discipline	.240	.063	.398	3.810	.000
Employee Attitudes	.212	.097	.229	.2.189	.031
Management Knowledge	.254	.112	.185	2.261	.026

Model Summary
Model 1	R	R Square	Adjusted R Square	Std. Error of the Estimate
Model 1	.615	.378	.359	2.753

Coefficient^a
Model 2	Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model 2	B	Std. Error	Beta	t	Sig.
(Constant)	18.582	2.915		6.374	.000
Work Discipline	.462	.054	.649	8.565	.000
Management Knowledge	.310	.160	.147	1.945	.050

Model Summary
Model 1	R	R Square	Adjusted R Square	Std. Error of the Estimate
Model 1	.676^a	.457	.446	3.023

Coefficients^a
Model 3	Unstadardized Coefficients		Standardized Coefficients	t	Sig.
Model 3	B	Std. Error	Beta
(Constant)	18.162	3.216		5.646	.000
Decision Making	.754	.093	.638	8.127	.000

*Path*	Direct	Indirect	Total effect	t_statistic	t_table	Desc
Management knowledge ï¿½-> OHSM	0,139	-	-	2,061	1,660	S
Management knowledge-> Decision Making	0,185	-	-	2,261	1,660	S
Employee attitude -> Decision making	0,229	-	-	2,189	1,660	S
Work Discipline -> Decision making	0,398	-	-	3,810	1,660	S
Work Discipline -> OHSM	0,303	-	-	8,565	1,660	S
Decision making -> OHSM	0,401	-	-	8,127	1,660	S