Household employment of potato farmers with allocation of working time and gender theory

Potato farming is affected by the amount of time which the farmers spend. The more labors spend the time, the more potato agricultural production. Potato farmers both male and female spend their time to potato farming together, but gender inequality often occurs between male and female farmers, so a research is needed on male and female potato farmers. The aims of this study are: 1) to analyze the factors that influence the outpouring of farmer household work, 2) to compare the difference in wages between male and female farmers. The Karangreja Sub-District’s Kutabawa Village and Serang Village served as the research sites. There is a quantitative descriptive used in the research approach. Document analysis, questionnaires, observations, and interviews are the methods used in the research to acquire data. The t test and multiple linear regression analysis were employed in the data analysis. Types of sample selection using purposive sampling. The results of the study show that: 1) the factors that influence male’s work outpouring are land area, farming experience and family responsibilities, while female’s work outpouring is influenced by age. 2) there is a difference in wages between male and female farmers in potato households in Karangreja Sub- District, Purbalingga Regency.


Introduction
The Indonesian population consists of both male and female.The population aged 15 and over is called the workforce [1].A total of 29.90% of the workforce is employed in agriculture, fishing, and forestry.[2].In 2019, the number of male workers was 21,222 people, increases 1.05 percent in 2020 to 22,093 and increases 1.02 percent to 22,571 people in 2021.Female workers in farming is 9,997 in 2019, increases 1.49 percent to 14,944 in 2020 but decreased by 1.11 percent in 2021.The increase in the agricultural workforce every year as a whole is due to an increase in the production of agricultural commodities.The more production of agricultural commodities, the more labor is needed.One of the agricultural commodities that has increased production every year is horticulture.The horticultural production index in 2019 was 112.43 points, 119.26 points in 2020 and 121.39 points in 2021 [4].One type of horticultural product is vegetables.The highest vegetable production in Indonesia in 2021 is shallots of 2,004,590 tons, cabbage of 1,434,670 tons, cayenne pepper of 1,386,447 tons, potatoes of 1,361,064 tons and large chilies of 1,360,571 tons [5].
IOP Publishing doi:10.1088/1755-1315/1302/1/012141 2 Potatoes are the only vegetable commodity needed throughout the year as a substitute for the main food ingredient other than rice [6].
Potatoes grow well in highland areas with an altitude of more than 1000 meters above sea level with low temperatures of 15 0 C -20 0 C [7].One of the highland areas which produces potatoes is in Central Java, namely in Karangreja Sub-District, Purbalingga Regency.Potato farming is affected by the amount of time which the farmers spend.The more labor outpouring, the more potato agricultural production.Potato farmers both male and female spend their time to potato farming together, but male farmers have more access to potato farming resources than female farmers.Female farmers also cannot make decisions related to potato farming.In addition, there are differences in farming activities carried out by male and female which causes differences in the wages of male and female farmers.This raises gender inequality potato farmers.As a result, the purpose of this study is to examine the factors influencing the labor output of farmers, both male and female, as well as the disparities in their pay.It is anticipated that the study's findings will serve as a guide for creating farmer household empowerment initiatives centered on gender equality.

Methods
The research method uses a quantitative descriptive which describes the research variables supported by the data produced.The research was conducted in Kutabawa Village and Serang Village, Karangreja Sub-District, considering that these two villages are potato-producing areas in Purbalingga Regency.The research data collection techniques use interviews, questionnaires, document study, and observation.Types of sample selection using purposive sampling uses the Isaac and Michael formula [8] The population of potato farmers in Karangreja was 500 people with a total sample of 70 people selected consisting of 35 Serang potato farmers and 35 Kutabawa potato farmers.The analysis of the data used are as follows:

Analysis of wages [3]
Wages = money from work + money for food + money for drink + money for cigarette (3)

Result and discussion
Potato farming in Purbalingga Regency is only found in Karangreja Sub-District, particularly in Kutabawa Village and Serang Village.Potato farming in the village has 2 characteristics, namely partners and non-partners.Then farmers will get an SOP (Standard Operating Procedure) to carry out potato farming.Seeds, fertilizers and pesticides are provided by partner companies.All potato farming processes from planting to harvesting are also directly controlled by coordinators from partner companies.The company buys all of the farmer's potato harvest at the price agreed upon at the beginning of the collaboration.The company will then process the potatoes into potato snacks.Nonpartner farming is carried out entirely by farmers from planting to harvesting.All business capital is also be responsible by farmers.Then the farmers will sell the potato harvest to the collectors, the collectors will hand it over to the wholesalers, the wholesalers will sell the potatoes in retail to the retailers and then bought by the consumers.

Respondent identity
The This shows that the area of potato farmers' land in Karangreja Sub-District is narrower than in Pangalengan Sub-District [10].The experience of potato farming in Karangreja Sub-District also varies from 1 year to 50 years.The average farming experience of potato farmers is 15.72 years which is categorized as quite a lot of farming experience.[11] research on potato farmers in Central Aceh Regency states that the average experience of potato farming in that area is 10 years.This shows that the farming experience of potato farmers in Karangreja Sub-District is more than in Central Aceh Regency.The age range of potato farmers is from 21 to 77 years.The age of the farmers most frequently found is 36 to 49 years old with 32 people or 45.71 percent.The average age of farmers is 39 years.This is the same as research by [12] regarding the age of potato farmers in Pangalengan Sub-District, Bandung Regency, which found that most potato farmers are 27 to 49 years old, 56 percent.The most frequently number of dependents of potato farming families is 4 to 6 people, 43 farmers or 61.43 percent.The average number of dependents of potato farmers is 4 people.A research [13] on potato farmers in Kayu Aro Sub-District, Kerinci Regency, stated that the average number of dependents for potato farming families in that area is 3 people.This shows that the number of dependents of potato farmers in Karangreja Sub-District is more than in Kayu Aro Sub-District, Kerinci Regency.

Work outpouring
In the Karangreja Sub-District of Purbalingga Regency, male and female laborers work together to cultivate potatoes.Stake installation, planting, weeding, spraying, harvesting, and post-harvesting are some of the tasks involved in potato farming.The Firms with farmers to cultivate the land by employing hoes to loosen the soil.Machine tools are not used by Karangreja farmers.They then create beds that are 40 cm by 80 cm by 10 cm in size.The fundamental manure fertilizing is then completed.After a week, the soil is left, and then potato seeds of the Granola variety are sown.These seeds are supplied by partner firms rather than being bought from farm shops.Next, the plants are maintained by watering them and giving them fertilizers (SP-36, Phonska, manure).The company also supplies farmers with pesticides.The partner company keeps an eye on the plants as they undergo treatment.After the plants are ninety days old, harvesting is completed.After that, postharvest.Farmers just harvest, and weighing occurs after harvest.In accordance with the agreement, partner companies buy all farmers' harvests.The seeds used by non-partner farmers are Atlantic.In addition to differences in seeds, non-partner farmers do not receive seed, fertilizer and pesticide facilities, so farmers must provide for the needs of potato farming [14].Male workers are more needed than female workers in potato farming in Karangreja Sub-District.The male workforce used was 57.30% while the female workforce was 42.70%.Labor requires an outpouring of work to do potato farming.Workload is the number of working hours devoted to all family members on farming activities.The amount of working time is defined as the number of real working hours (HOK) to carry out farming activities during one period.The following is the workflow of the respondent farmers in table 1.The results showed that the largest total work outlay was spraying 1,084.57HOK.Spraying has a large outpouring of work due to which potato plants require intensive care.This is in accordance with the statement of [15] that the highest work outlay is in maintenance activities including spraying asmuch as 38 percent because this activity must be carried out continuously and repeatedly.The smallest work outpouring is post-harvesting activity.This occurs because the farmers have cooperated with firms so that all post-harvest processes are carried out by partner companies.The company buys all of the farmer's potatoes and handles postharvest.When it's harvest time, the coordinators of firms who are assigned to the villages of Serang and Kutabawa use outside workers to carry out the post-harvest work.This is in accordance with the statement of [16] that the smallest work outlay is post-harvest because there is no post-harvest activity.Farmers sell their harvest wet so that it will be carried out post-harvest by middlemen.

Factors influencing respondents work outpouring
The factors that affect the work outpouring for male and female are analyzed by using multiple linear regression which is divided into 2 regression models.Multiple linear regression requirements must meet the normality test, linearity test, heteroscedasticity test and multicollinearity test, linearity test, multicollinearity test and heteroscedasticity test.This study uses the Kolmogorov Smirnov Monte Carlo normality test.According to Quraish [18], the Kolmogorov Smirnov normality test can test a sample whether it comes from a certain distribution or not.[19] states that the data criteria are good and normally distributed with the Kolmogorov-Smirnov test has a significance value of more than  = 0.05.The test results show that the significant value of male work outpouring is 0.064 (rounded up to 0.07).This value is more than 0.05 so it is proven that the data on male employment is normally distributed.The significant value of female's work outpouring is 0.259 (rounded up to 0.26).This value is more than 0.05 so that the female's work outpouring is normally distributed.Linearity test is used to determine the linear relationship of an independent variable with the dependent variable.This linearity test is a requirement for carrying out a linear regression test [20].Research data is declared linear if sig.deviation from linearity is greater than 0.05 [19] The results show that the significant value of male's labor work outpouring in land area, farming experience, age and number of dependents is greater than 0.05, which means that male's work outpouring -linear male with all research variables.The significance value of female's work outpouring on land area, farming experience, age and number of dependents is also greater than 0.05, which means that female's work outpouring is linear with all research variables.The multicollinearity test has good data if the Tolerance value is greater than 0.10 and the VIF is less than 10.0 so that the independent variables tested do not experience multicollinearity [19].Male's work outpouring has a tolerance value of land area, farming experience, age and number of dependents greater than 0.10 and a VIF value of less than 10.0.So there is no multicollinearity between the male's work outpouring and the research variables.Female's work outpouring also has a tolerance value of land area, farming experience, age and number of dependents greater than 0.10 and a VIF value of less than 10.0.So there is no multicollinearity between the female's work outpouring and research variable.The heteroscedasticity test has good data.If the Sig. between the independent variable and the dependent variable is more than 0.05 so there is no heteroscedasticity [19].The test results show that male's labor has a significant value for land area, farming experience, age and number of family dependents of more than 0.05 so that male's work outpouring has no heteroscedasticity.Female's work outpouring also has a significant value for land area, farming experience, age and number of dependents of more than 0.05 so that female's work outpouring does not have heteroscedasticity.All research data do not have variables that cause inaccurate and inefficient data.
The F test is used to test hypotheses with a significance level that compares independent samples [23].The hypothesis for the F test conducted in this study is as follows: H0 : there is no significant influence between variables X (land area, age, farming experience, number of dependents) and Y (work outpouring) together; H1 : there is a significant influence between variables X (land area, age, farming experience, number of dependents) and Y (work outpouring) together.
The results of a good F test have a homogeneous variance by looking at the calculated F value that is greater than the F table [23].The results showed that the calculated F value of male's work outpouring is 10.801, while the F table is 2.51.F count is greater than F table, so H0 is rejected and H1 is accepted.This means that there is a significant influence between variables X (land area, age, farming experience, number of dependents) and Y1 (male's work outpouring) together.F calculates the female's work outpouring at 5.235, while F table is 2.51.F count is greater than F table, so H0 is rejected and H1 is accepted.This means that there is a significant influence between variables X (land area, age, farming experience, number of dependents) and Y2 (female work outpouring) together.

Multiple linear regression analysis
Multiple linear regression in this study is divided into two, namely multiple linear regression of male workflow and female employment.The results of multiple linear regression are as follows: Multiple linear regression is used to find a model of multiple linear relationships between independent variables and the dependent variable [25].The regression model obtained in the male's work outpouring is as follows: Y1 = -7.453+ 127.317X1 -0.917 X2 + 0.379 X3 + 4.115 X4 The t test is used to determine the effect of each independent variable on the dependent variable.If the t count is greater than the t table or the t test value is less than 0.05, the independent variable has a significant effect on the dependent variable [24].The variable tested by the t-test is declared significant if the significance value is less than 0.05 [24].The results of the t-test for male's work outpouring showed that land area, farming experience and number of dependents had a significant value less than 0.05 so that land area, farming experience and number of dependents are significant to male's work outpouring.Age has a significance value of more than 0.05 so that age is not significant for male's employment.The of female's work outpouring shows a significance value of less than 0.05, which means that age is significant to the female's work outpouring.Land area, farming experience and number of dependents are not significant to female's employment because the value is more than 0.05.
Land area has an X1 coefficient of 127,317 meaning that for every 1 percent addition of the X1 value (land area), the value of male's work outpouring increases by 127.317.The larger the area of land worked by farmers, the more work the farmers will do.According to [26], the area of a farmer's land indicates production.Farmers who have large land will produce more crops so that more time is devoted to farmers with large land.Farming experience (X2) has an X2 coefficient of -0.917, which means that for every 1 percent addition to the value of farming experience (X2), the value of male labor decreases by 0.917.the more experience farmers have in farming, the more proficient farmers will be in working on farming so that the work outpouring decreases.This is the same as the statement of [27] which states that farmers have been provided with farming experience from childhood for generations so that farmers are accustomed to doing farming so that they can complete farming work more quickly.This causes the farmer's work outpouring to be less and less with a lot of farming experience.The number of dependents (X4) has an X4 coefficient of 4.115 meaning that for every 1 percent addition of the X4 value (number of dependents), the value of the male's work outpouring increases by 4.115.The more the number of dependents of farmers, the more work outpouring of farmers.According to [26], if family dependents increase, then the outpouring of working hours for farmers.

Farmer wages
Wages are a person's source of income to fulfill his life.Wages are earned in exchange for work in the form of money [28].Wages are also given for both formal and non-formal workers including farmers.Farmers earn wages by working on their own land.The wages of potato farmers in Karangreja are as follows: Table 3. Wages of male and female potato farmers in Karangreja Sub-District.

Activity
The amount of male wages per planting season (IDR) The amount of female wages per planting season (IDR) The amount of male wages per planting season (IDR) The average of female wages per planting season (IDR) The size of the wages of potato farmers in Karangreja Sub-District indicates the size of the farmer's productivity.The more productivity of farmers, the more wages earned.This is in accordance with [28] on Bangladeshi farmers which states that the higher the wage rate, the more productive the farmer is.The high wages of rice farmers in Bangladesh are due to high productivity for carrying out agricultural activities.After knowing the farmer's wages, a different test was carried out.The different test requirements are fulfilling the homogeneity test.This test is to determine whether there are similarities or not in the two groups (income of male farmers and income of female farmers.If the two groups are homogeneous, then the characteristics of the two groups are the same, so that the difference is in the independent variables [29].The homogeneity test is carried out in order to find out if several variances have similarities or not as a condition for the t different test analysis [30].The homogeneity test hypothesis in this study is as follows: H0 : both samples have the same variance at a significance level of 5% ; H1 : both samples have unequal variances at a significance level of 5%; Homogeneity test was carried out by analyzing the data using the SPSS application. The results of the homogeneity test show a significant value of 0.615 meaning that the data is more than 0.05 so the data is homogeneous.There are similarities between the two groups, namely husband's wages and wife's wages.Then H0 is accepted and H1 is rejected.Both samples have the same variance at the 5% significance level.The different test is a statistical test to find out the difference in the average score between two groups or samples [31].The results showed that Equal variances assumed Sig.(2 tailed) 0.000 less than 0.05.If the Equal variances assumed Sig is less than 0.05, then there is a significant difference between the husband's (male) wage and the wife's (female) wage.The difference in the wages of male and female potato farmers is significant.

Conclusions and suggestions
Based on the description in the discussion, the conclusions obtained are 1) The total work outpouring of male potato farmers in Karangreja District, Purbalingga Regency is 2,225.29 HOK per 20.92 Ha of land per planting season, while the total outpouring of work for women is equal to the total work outlay of female farmers, namely 1,201.29 HOK per 20.92 Ha of land or 57.42 HOK per Ha.Factors that influence men's workflow are land area, farming experience and family responsibilities, while women's workflow is influenced by age.2) There is a difference in wages between male and female farmers in potato households in Karangreja Sub-District, Purbalingga Regency.There are several suggestions from the author.For government and private institutions that will carry out empowerment programs should see this research as a reference so that they can empower farmers with gender equality.For farmers, female farmers should play a greater role in making potato farming decisions, and male farmers also have a more role in domestic household activities.For researchers who will examine the topic of working allocation of potato farmers, it is better to provide more specific questions, for example adding the role of education, training and access to farmer resources in order to achieve optimal research results.
selected respondents in this study are 70 people consisting of 35 farmers from Kutabawa Village and 35 farmers from Serang Village.Potato farmers in Karangreja Sub-District have a land area of at most 1.00 Ha and at least 0.05 Ha with a total land area of 20.92 Ha.The average land area is 0.30 Ha.The majority of potato farmers is 0.05 Ha to 0.29 Ha of land with 40 farmers or 57.14 percent belonging to the small category.Land area of less than 0.50 Ha is classified as small scale.

Table 2 .
Multiple linear regression of farmer's labor.