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E-Happiness Tool ( Web Application ) , Measuring of Poor Family Happiness

Is your family happy? Many factors can affect family happiness. e-Happiness Tool can assess whether your family is happy or not based on factors that are valid and reliable from previous studies. These factors are life satisfaction, affect, and meaning of life. The e-Happiness Tool also presents a percentage of the level of family happiness. Another feature of e-Happiness Tool is the map of the distribution of happiness levels at the provincial and district/city level in Indonesia (case study). E-Happiness Tool can be accessed online and for free.


INTRODUCTION
Slums in urban areas were chosen as research locations because someone in a household living in an urban area has a greater risk of experiencing a high level of inequality and requires more resources to achieve a minimum level of welfare that is socially acceptable, so [4] also states that the location of residence affects how one's perception of their welfare status. Supposedly, people who live in poverty will experience conditions of low subjective well-being compared to those who are not poor. However, in a study [5] entitled Making the Best of A Bad Situation: Satisfaction in the Slums of Calcuta it was found that poor people living in slums in Calcutta, despite experiencing adverse conditions, but in many cases found a life satisfaction that reflects good subjective well-being which often becomes a substitute term for happiness.
Happiness is perceived subjectively for everyone who feels it, and this also depends on the degree to which they positively assess the quality of their whole lives [9,12]. According to [8] states that there are two affective components and cognitive components to measure happiness. The affective component is related to the extent to which an individual feels positive about himself (hedonic level of affect), while the cognitive component is related to the level of individual satisfaction with what he gets in life (contentment / life satisfaction). The word "happiness" is often a vague term for some experts so they often change the term happiness to "subjective well-being" to define it. The term "subjective" is used because in reality a person experiences happiness is relative only to those who experience it alone [15]. Or in other words, "the best judge of how a person feels happiness is that person". But in the end a number of studies have succeeded in delivering accurate and reliable reports to measure individual happiness [3].
Happiness is an indication of well-being which includes aspects of feeling good and positive emotions, as well as the meaning and satisfaction of life [15]. In other words, happiness as an experience of positive emotions combined with deeper feelings about the meaning and purpose of life.
Badan Pusat Statistik (BPS) [6] sets happiness measurements with 3 (three) dimensions namely: (1) Indonesia's happiness score is 70.69 and the happiness index in DKI Jakarta Province is above Indonesia's happiness index which is 71.33. This means, the happiness of the population in DKI Jakarta Province is in the Medium category [7]. What about the happiness of poor households in DKI Jakarta, especially in the Municipality of North Jakarta? The number of poor people in North Jakarta Municipality is highest compared to the number of poor households in other Municipality in DKI Jakarta Province.
The measurement of happiness that has existed so far, which is measured by BPS and OECD (UNDP) [11] is limited to the measurement of happiness that relies on areas in the index measure. However, when asked which household is happy, or how the level of happiness owned by a householdhas not been answered and cannot be disclosed.
Based on this explanation, the researcher will detect indigently the poor household whether happy or unhappy, then it will detect the type of happiness it has. Detection is carried out using indicators that will be discussed in the research method. These indicators are the basis for developing the e-Happiness Tool (Web Application).

II. METHOD
There are several things used in the method in this study. Among them are Alkire-Foster Method, Composite Index Calculation Method (Happiness Index), and Website Development Method E-happinesstool.com.

A. Alkire-Foster Method
The Alkire-Foster (AF) Method [1] is a way to calculate multidimensional poverty developed by OPHI's Sabina Alkire and James Foster. This method was built based on poverty calculation by Foster-Greer-Thorbecke, which calculates the different types of deprivation that a person experiences at the same time, such as lack of education, unemployment, health and low standard of living. Deprivation criteria are analyzed to identify who is poor and then used to build a multidimensional poverty index. This research uses the method [2] to calculate the multidimensional poverty index because this method is easily applied and can be used to monitor changes in poverty over time. This can be seen from the changes in dimensions and indicators directly and quickly [2]. The following are the stages of the method [2]:

1) Select the unit of analysis
The unit of analysis commonly used is individuals or households but it can also be a community or school, clinic, company, village or other unit.

2) Select dimensions.
Dimension selection can be made based on survey data or research on people's perceived needs, the results of general consensus such as human rights declarations, SDGs, national or regional policies.

3) Select an indicator.
Indicators are selected for each dimension with accuracy rules (using as many indicators as needed so that analysis can form the basis of policy) and parsimony (using indicators as little as possible to ensure ease of analysis for policy and transparency purposes). Statistical properties are often relevant for example, when possible and reasoned is the best choice for choosing indicators that are not highly correlated.

4) Establishing the deprivation cut-off point.
The cut-off point is set for each indicator. This stage forms the intersection point which is the first intersection point in this methodology that can identify someone deprived or not for each indicator.

5) Determine the weight / weight for each dimension and variable.
Weights used can be either the same weight (equal weighted) or different weights (equal weighted). 6) Calculate the deprivation score (ci) experienced by each unit of analysis formulated as follows:

7) Set the second intersection point (k).
Determine the number of deprived indicators (k) to identify someone experiencing multidimensional poverty or not.

B. Composite Index Calculation Method (Happiness Index)
Happiness Everyone assessed in the worksheet is seen from the indicators assessed. The assessment consists of dummy 0 or 1. When someone meets the happiness assessment according to a multidimensional happiness indicator, then given a point 1. The assessment will continue to be done on each indicator. After getting an assessment of twenty indicators, it will be calculated based on the following formula: Ci = W1I1 + W2I2 + … + WpIp Information: Ii = 1, if someone include on the indicator I dan Ii = 0, if not. Wi is the weight of the indicator to the total n= the weight is 1. Then the value of Ci is compared with a weight of 1/3, if it is greater then the household is categorized as "HAPPY". Based on the happiness dimension of the BPS version [7], this study will detect poor households who have happiness and are unhappy. The development of the detection is done by giving a value of 0 (No / None) or 1 (Yes) of the indicators in each dimension, as simplified in the following worksheet.

III. RESULTS AND DISCUSSION
Website development is divided into two parts, namely frontend and back-end. The following is a display of www.ehappinesstool.com that has been developed:          Figure 6. On this page, administrators can set various questions (indicators) that will be displayed on the happiness test page of poor households. In addition, all data contained on the website can be retrieved through this page.

Advances in Social Science, Education and Humanities Research, volume 410
IV. CONCLUSIONS BPS and UNDP have data on how happy they are in certain areas, but they have not been able to specifically answer whether a poor household is happy or not. The development of a website-based e-Happiness Tool with the address www.ehappinesstool.com can answer whether a poor household is happy or not. The website can also see the level of distribution of happiness at the district / city and provincial levels. It is expected that future research can utilize much more practical media such as the Android or iOS application.