Evaluation on Moisture Content of Eucheuma cottonii Seaweed Variety using Statistical Quality Control Approach Evaluasi Kadar Air Rumput Laut Jenis Eucheuma cottonii dengan Pendekatan Statistical Quality Control

Quality is a crucial factor of an industry. PT XYZ is an exporter and distributor company of seaweed in Makassar city. It exports various varieties of seaweed, one of them is Eucheuma cottonii. Quality must be maintained to preserve and increase company image or reputation and consumer satisfaction. The study aims to improve quality of seaweed through quality control by using Statistical Quality Control (SQC) method. Receiving data of Eucheuma cottonii seaweed obtained from 30 sample groups, each group contains three different samples. Analysis on the process capability then was carried out so that the obtained score of process capability ratio was 0.35<1 and the process capability index score was -0.12<0. It can be concluded that the receiving process of seaweed in this company was incapable and need improvement to increase receiving process capability of seaweed. Several factors caused this incapable process were the unskilled human resources on seaweed handling in material receiving process and during distribution process from the farmer, the limitation of reliable measuring instruments, and the lack of constructive partnership between farmers, suppliers, and industry. Hence, this study suggested to improve skills of the employee, supplier, and farmer regarding seaweed cultivation and handling, to provide more reliable measuring instruments, and to develop constructive partnership development among farmer, supplier, and industry as an improvement of seaweed quality on receiving process.


INTRODUCTION
Seaweed is one of the superior commodities and can sustainably develop due to its relatively easy and cheap cultivation technique yet has high productivity. High basic selling price is a trigger factor people to cultivate it. Commonly, seaweed is developed in the form of; 1) dried seaweed, 2) direct consumption product, and 3) hydrocolloid (alginate, jelly, and carrageenan). Around the world, 65% of seaweed is directly consumed, 15% is a hydrocolloid, and the rest 20% is for paper material, fertilizer, and biofuel (Dahuri, 2011).
One of the keys to success to outperform the upcoming seaweed industrial field in the globalization era is to notice the supply chain's quality entirely. The quality of seaweed is one of the crucial indicators of the agricultural product for the export market. It is influenced by three basic kinds of stuff such as cultivation, harvesting period, and drying process (Anggadiredja et al., 2006). Furthermore, the difference in cultivation place is another influential factor in its quality (Kumayanjati & Dwimayasanti, 2018). Another factor is quality seed selection and supply, which is cheap, easy, massive, and sustainable (Sarira & Pong-Masak, 2018). Those factors are crucial to ensure proper material quality for the production process.
Some elements or portions provided in supply chain management generally are supplier, industry/manufacture, product distribution, retail, and consumer. There is also a minor chain in the material supply process such as farmer, supplier, and distributor. In this matter, several kinds of essential things to be developed more deeply are on the seaweed collector and distributor chain. It is a susceptive area due to the new process, i.e., seaweed storage and drying. It certainly raises potential on the decreasing seaweed quality in the storage process, such as sorting process, storage durability, storage condition, and drying process and method being conducted. The initial result showed decreasing seaweed quality, especially in the receiving process of the industry.
The study regarding seaweed mostly still focused on matters that supported the success of seaweed cultivation to maximize the material quality of seaweed both of its internal and external factor (Anton, 2017;Yudiastuti, Dharma, & Puspitha, 2018;Soenardjo, 2011;Valderrama et al., 2013;Triajie, 2010;Failu, Supriyono, & Suseno, 2016). It is also in the producing process chain of seaweed, as several studies conducted (Sedayu, Basmal, & Utomo, 2008;Setyadewi & Cakravastia, 2013;Fateha at al., 2019;Putri, et al., 2018). The quality in the cultivation area and producing process is relatively untouched and is still very limited. However, several different studies about seaweed contribute to the analysis of material quality towards certain kinds of material such as in food production and pharmacy (Rimantho & Mariani, 2017;. Therefore, the study on the distribution process (among farmer and seaweed production industry) needs to be conducted to strengthen the supply chain of the seaweed production process of an industry.
Other than price, the quality of the product is an essential consideration for consumers. Consequently, quality must be a primary concern for the company to maintain and improve. Quality control is a phase to reduce defective products through process variation emphasis and meet the standard of product quality specification of a company or National Standardization Agency of Indonesia (BSN) and prevent the defective product received by consumers. Also, to reach a high quality on the production process, the company must carry out a step of quality control that aims to find out the occurred fault level so that improvement and perfection measure on the process and system can be developed. The process of quality control begins from the material receiving process to the final product.
The purposes of quality control are (Assauri, 2008) to ensure that the production result meets the quality standard; to achieve efficient inspection cost; to design the cost of the product and process on production quality as efficiently as possible; and to keep production cost as low as possible. The main goal of quality control is to obtain product and service quality assurance, set by economical and efficient cost.
Statistical Process Control (SPC) is a method that can be applied to carry out quality control. SPC is a problem-solving technique used to monitor, control, analyze, manage, and improve processes. It is expected by the company to produce goods and services that meet specifications through the beginning to the end of the process by applying several statistical methods (Ariani, 2004;Heizer & Render, 2013;Stevenson, 2009).
PT XYZ is one of the seaweed distribution and processing companies in Makassar municipality. One of the seaweed varieties distributed by PT XYZ, both for the domestic and nondomestic market, is Eucheuma cottonii. The company has several suppliers in various regions, namely Bantaeng Regency, Takalar, Pangkep, Mamuju, Nunukan, and Tarakan. The quality of seaweed in each region is different. Therefore, the company conducts seaweed product sorting of the supplier according to company standard or BSN by using the percentage of moisture content Evaluation on Moisture Content ... measurement. It is essential to the processing company because dried seaweed has high yield content, and it is relatively safe for a longer duration of storage. Seaweed is categorized as dried seaweed if it looks rigid, and salt grains stick to the seaweed surface with a moisture content of 31-35% for Eucheuma cottoni (Anggadiredja et al., 2006). Dried seaweed can easily be cleaned from the foreign object stick on its stems. If it is still wet (high moisture content), then the outer layer in the form of slime resulted in the dirt to stick. If seaweed is dried, bacteria that have the potential to damage the quality of seaweed cannot survive, so it is not easily damaged even for a longer duration of storage (Surata, Nindhia, & Atmika, 2012). According to the observations, there is a difference with the relatively high gap between the results of each employee's judgment in predicting the moisture content at the time of receipt of seaweed from the supplier and laboratory test results. Hence, an in-depth study is needed for mapping the quality of seaweed at the time of receiving from suppliers.
Based on the description, the study can be developed in four subjects; namely, 1) mapping control chart of Eucheuma cottonii; 2) calculating the process capability of Eucheuma cottonii; 3) identifying the factor of non-compatibility of seaweed quality according to BSN standard using fishbone diagram; 4) providing suggestion on the quality improvement of Eucheuma cottonii.

METHODS
The study was conducted at a distribution and processing company by using several phases. 1. Analysis of Moisture Content.
In the process of moisture measurement conducted according to Indonesian National Standard (SNI 2690:2015) concerning dried seaweed threshold value of each criterion (Badan Standardisasi Nasional, 2015), particularly for the parameter regarding moisture content test, it can be seen in Table  1. In addition to the standards in Table 1, companies that generally engaged in seaweed business indicate that the ideal level of moisture content in seaweed is in the range of 30% to 40%. In the process of moisture content test, sampling was firstly conducted at PT XYZ, and then tested in the laboratory. 2. Sensory test.
In the sensory test, there is a form sheet about seaweed specifications assessment regarding appearance and texture filled by PT XYZ employees showed in Figure 1.

Data Processing of Control Chart
Statistical process control (SPC) is one of the applicable methods, a problem solving technique used to monitor, control, analyze, manage and conduct process improvement. The goal of the control process is to suppress and reduce variations during whole process, especially variations caused by specific factor (Ariani, 2004;Stevenson, 2009;Heizer & Render, 2013). a. Control Chart − Control chart average ( ) and range ( ) are two control charts that have mutual support in the process of decision making regarding quality of process. The average control chart ( ) is a control chart to monitor whether the process is still in control or not. It shows the average production that meets control standard used by company. The producing process has met product specification if it is on or around center line and in control limit. But, if the data lied out of statistical control limit due to common variation (cause contained and attached to the process) then it does not need to be omitted and is considered in control limit. The data contained outside of the average control limit are called statistical control caused by particular variation.
Range control chart (r) is a chart to identify the level of accuracy or precision of the process by finding out the range of samples during observation. As well as the average control chart, range control chart is  is also used to identify and eliminate specific causes. Data within the statistical control limits for a range is called in statistical control which have variations due to general causes. Moreover, data that is outside the control limits of statistics is called out of statistical control, which have variations due to particular reasons.
The following equation of (1) up to (4) is a measurement to determine central line of mean and range. = ∑ =1 (1) Symbol n denotes number of sample for each observation/sub group/group, g is the number of observation has been conducted, Ri is range of each sub group, Xi denotes data of sub group or sample that has been taken, and X ̅ is the average of each observation. Equation (5) is used to measure upper center line (UCL) and Equation (6) for measuring lower center line (LCL) on the average control chart. For the range control chart, the upper center line (UCL) can be determined using equation (7) and lower center line (LCL) using equation (8). A2, D3, and D4 are constant factors of chart of quality control limit that depends on subgroup measure of each sample.

Measuring Process Capability (Analysis of Process Capability)
Process capability analysis is a study to estimate the capability of processes in the form of probability distributions that have form, mean and spread. The process defines the ability of the process to meet specifications or to measure process performance. Additionally, it has purpose to predict the variability of existing processes, test theories about the causes of errors during quality improvement programs, and others. The main reason is in quantifying the ability of the process is to be able to stick to product specifications (Ariani, 2004;Heizer & Render, 2013;Stevenson, 2009). In the process in a condition of statistical control, the steps to conduct a process capability analysis described as follow: a. Process capability ratio or Cp value The process is within statistical control limit if the process of the statistical process control chart categorized as "normal" and the average centered on the target, then index or ratio of process capability can be measured using Equation of (9) and (10). Cp = − 6 (9) = 2 (10) Cp stands for process capability ratio. Factor of d2 is a constant factor to estimate sigma value for control limit chart depending on subgroup of each sample. UCL (Upper Control Limit) and LCL (Lower Control Limit) are established by consumer and must be fulfilled by producers, and σ is deviation standard of the process. According to the measurement, the standard value of Cp describe as follows: 1) If the value of Cp > 1, it shows a capable process, 2) Cp < 1 shows incapable process, and 3) Cp = 1 shows appropriate process or it has met consumer specification. If process capability index higher than the product that lied outside, the specification limit becomes lesser. b. Process Capability Index (Cpk) The value of process capability index is a parameter made to observe the real capability of a process. Value of Cpk is formulated using Equation (11).
Standard value of sigma of Cpk are as follow: 1) Cpk < 0, shows process average outside of specification limit, means a low accuracy. 2) 0 < Cpk < 1.5, shows that accuracy and precision are still low if the value of Cpk < 1.5, however, if the value of Cp > 1.5, then it has high precision but low accuracy. 3) Cpk > 1.5, if it is followed by Cp > 1, then, it is categorized as capable process with high accuracy and precision. If Cp < 1, it means high accuracy and low precision.

Analysis of Cause and Effect using Fishbone
Diagram. Kaoru Ishikawa is a figure who developed a fishbone diagram in 1943, so that it is known as the Ishikawa diagram. It is useful to provide the cause of a problem specifically for further development steps or corrective actions. 6. Arrangement of recommended seaweed quality improvement. Recommendation arrangement is according to the result of the prior analysis using fishbone diagram.

Moisture Test
Content of Sample water was tested in Food Chemistry Analysis Laboratory of Animal Husbandry of Hasanuddin University with the result presented in Table 2.

Sensory Test
Sensory test was performed as an additional instrument of the results of the moisture content test. Table 3 presents the results of sensory test conducted by employees of PT The XYZ.
The specifications measured are in terms of appearance and texture of the seaweed samples. A good standard value of seaweed sensory is 7. Based on the sensory test has been conducted by expert employees on seaweed field showed that the average of seaweed sample concerning its appearance lied on the established standard, several sub groups have value of 9 that means a very good result in fact. Moreover, regarding the texture, 3 subgroups that have value of 5 means not good, but it did not significantly affect the result of moisture test.

Data Processing
The research is not possible to conduct an examination of each product regarding quality of the product. Therefore, an assessment with a statistical method is needed so that it eases to find out the overall quality of the product by taking several samples on each truck which is conducted 30 times, on August to September 2018. Statistical methods used to analyze data of the defect of Eucheuma cottonii are the average control chart ( ) and range (R). The result of the first data processing shows that two data are outside of control limit, namely 2 nd data and 3 rd data called as particular cause variant. Then, data processing is repeated by using 28 data. According to the results of this revision I of data processing, there are two data which are out of control limits, namely the 22 nd and 15 th data. Then the data processing is repeated with a total data of 26. The results of the revision II data processing showed there is still one data that comes out of the control limit that is the 22 nd data. Finally, data processing is performed again with the amount of data as much as 25. The results of data processing revision III showed all the data are in statistical control and no outlier data.
Based on the results of data processing (Figure 2), it is known that three data are outside the average control limit ( ) and two data are outside the distance control limit (r). Therefore, variations of specific causes can be identified and a revision of the average control chart ( ) and distance (r) needs to be performed three times. After revising, the value of the center line, upper control limit and lower control limit on the average control chart ( ) are obtained, which are 41.71; 50.04; 33.39 sequentially. The center line (CL), upper control limit, and lower control limit on the distance control chart sequentially are (R) of 8.14; 20.95; so that all data is in statistical control and there are no outlier data.

Analysis of Process Capability
According to BSN, the maximum value of seaweed moisture is 30 %. In addition, several requirements and certain specification limit must be met by the company regarding the product quality. The next phase is measuring value of , process capability ratio (Cp), and process capability index (Cpk). The measurement as follows: 1. process capability ratio (Cp) = 2 (12) The measurement as follows: The result of data processing presented the value of process capability ratio (Cp) of 0,35 < 1 means it is outside of the specification. Moreover, process capability index (Cpk) value of -0,12 < 0 that showed the accuracy of process capability is relatively low. According to the value of Cp and Cpk, it can be concluded that seaweed receiving process is not capable, so that improvement action is needed to increase the process. Sub Group yet comprehensive because it only measured one of the parameters of BSN, i.e. moisture content of Eucheuma cottonii to find out the process capability and quality of seaweed. Consequently, to develop further research, it is suggested to consider another parameters such as sensory, Clean Anhydrous Weed (CAW), metal or physical contamination.