QUALITY AND POPULARITY PREDICTION MODELING OF TV PROGRAMME THROUGH FUZZY QFD

  

QUALITY AND POPULARITY PREDICTION MODELING OF TV

PROGRAMME THROUGH FUZZY QFD

Minarya Sitepu

  1 , Sinar Sinurat

  2 , Anggiat Hatuaon Sihite

  3 Mahasiswa Teknik Informatika STMIK Budi Darma Medan

  1 Dosen Tetap STMIK Budi Darma Medan

  23 Jl. Sisingamangaraja No. 338 Sp. Limun Medan 123

ABSTRACT

  

Firstly the researcher want to look how the society interactive one of another. Nowdays TV Program one of facilitate

can accommodate us to look , how people make interactive like what we call in Indonesia costum as: arisan, gossip,

candaan group etc. a social phenomenon like that can be wrapped in miniature setting mostly in Joke or Comedian

theme. Recently one of fumous like Sule “Ini Talk Show” TV Program. “Ini Talk Show” make one of TV production

part of them contribute on TV Program needed to know as a practice, comedian society and as a prediction value.

Sometimes the people who contributing for this production want to know how to get measuring increase of this

program, may be in reputation, interest and benefit for investment. Base on above description the researcher try to

finding a simple method to get the element which make this program can be increased as a quantitative or qualitative

base on the survey for 40 people in one area and after that making questionnaire for the measuring and the result.

The researcher get 3 domain area which grouped as : popularity factor, entertainment factor and regional factor.

  Key Word :Fuzzy Quality Function Deployment (FQFD), TV Programme

I. Introduction

  In this paper we tried to dwell on to the problem of identifying the most important ‘Quality and Popularity contributing factors’, which plays an important role in deciding the ‘Popularity’ of a TV production.The daily show is a kind of a nightly news parody that takes a reality-based look at news, trend pop culture, current event politics, sports, entertainment and the media. Some free TV want to entertain or inform to their audience is rapidly becoming divided, just like the 1 % percent haves 99% have hots [1].

  First tried to identify correctly the most important ‘Quality and popularity’ contributing factors of a TV programme which makes the TV programme more popular and successful, and then applied the knowledge of a most suitable scientific technique. Fuzzy Logic in our situation, which would successfully incorporate these identified factors by establishing a proper correlation between these factors and the relative engineering requirements which used to effects these factors mostly if not considered at the time of production of the TV programme, and lastly we analyze our findings by simulating a most approximate ‘fuzzy inference rule’ based ‘Quality and Popularity’ prediction model. The extended of the fuzzy logic is a super set of boollean logic and that hasbeen extended to take care of truth value. Survey has taken genuinely believe that America canbe looked greedy, sexist,racism. Every one has a bad day, it hapines. You wake up on the wrongside of the bed, but then you think of a great quote your favorite talkshow host once said, “ you day is bright and light once more. This great discovery of all time is that person can change his future by merely changing his attitude (Oprah Winfrey).

  In TV entertainment industries where millions of money are being invested in producing variety of TV programmes on regular basis and after finishing the production, producers of the programme, start search for sponsorship of their production through various commercial agencies or directly with TV channel owners, to get some good return on their investment, these agencies in return provide them a platform to telecast their programme for the viewers and depending upon the response of the viewers in terms of popularity of the said programme the return on the investment of the producers could be decided, though every producer has invested his money by thinking a good return on the investment but only a few of them encounter a positive response from its viewer and thus could become success in term of monetary returns, but majority of others could not even get back their investment or just equalize it and some more unfortunates get totally loss as they even do not get any commercial sponsorship for their production. Though most of the producers of the TV industry used to concern about the latest way of incorporating the current trend and technicality of the production industries rather, in a blind manner to prove that their production incorporating the latest feature of the industry, even then their programme does not taste the success on real ground. There exist a number of cases of drastic failure of hugely invested projects which incorporates the entire latest technicality and invested millions of Rupiah in the projects, why it is so?

  The same production has shown in Indonesia media one this project canbe look in “Ini Talk Show”. Ini Talkshow is a group consist of Sule as a host , Andre as a co-host, Maya as a family assistant, mami Jessie (mother) mang Saswi (as the uncle). Ini Talk Show is one of the favorite Net-TV programe in Indonesia. They have a good rating as the Entertain focused on comedian reality show. Many people like this TV show even they also have a certain argument for this Showing. The reasecher want to know how the people opinion about this programme Talk- Show. We are making a survey fourty people in one complex area. 50 % of this comunity showing a big attention may be for their performance that can be look like the interactice between host and the co – host, so for futher conclucion can get the enjoying situated for the the audience. Among the people 30 % of them also say that in Ini TalkShow get all the people freely tobe laughed so that can be supported this TV program has a good reputation.

  A general trend in a TV programme making is the concern about a good script, a well trained director, shooting technicians, camera persons,good sound recordist and vision mixer engineers. The same condition canbe looked in “Sule Ini Talk Show”. The conversation with the guest that faciliate with a good feature of setting area for the meeting and with a goodor a nice soundtrack listening making the Show production can be accepted to all the audience and for the society also. All of them be mad of the funny interactive of the guidance (Sule) and the co-host (Andre). Every audience, guest, crew, and the personal of the group too can express their self in that time, so that step by step making this group as one population as a media that people can making a new typicaly program TV-Show that can be made as one of A popular Entertaiment.

  Posting production and well establish non linear editing facility with some good editors for audio and video effect generation and mixing for finalpresentation of the programme, is been taken as a sufficient resource to produce a good quality programme, is it enough to contribute well in a success of the production? Does not the heterogeneous background of the viewers play any role in the success of a programme? Does only the above mentioned resources are enough to cross t he benchmark of viewer’s expectations? These and several other questions often come in producers mind when a well invested project faces a drastic failure.

  Use of Fuzzy sets in logical expression is known as Fuzzy Logic. Fuzzy Logic is a superset of a Boolean logic and that has been extended to take care of the partially truth values. It is a mathematical technique for dealing with imprecise data and problems that have many solutions rather than one. Fuzzy logic works with ranges of values, solving problems in a way that more resembles human logic. Fuzzy logic is a logical system which is an extension of multi valued logic. Fuzzy logic starts with and builds on a set of user supplied human language rules.

  The fuzzy system converts these rules to their mathematical equivalents. Fuzzy logic can handle problems with imprecise, vague and incomplete data. In Fuzzy Logic a proposition may be true or false or have an intermediate truth value, such as may be true. Fuzzy systems try to emulate cognitive process of the brain with a rule base. The basic concept is inspired by the human process, where the decisional criteria are not clear cut but blurred and is difficult to find objective to make decision more precise and clear [7].

  A. Fuzzy inference mechanism (FIM)

  To get a better understanding of fuzzy inference mechanism we will start with Generalized Modus Ponens (GMP) which is classical logic.

  R: If p then q (Rule)

  F: p’ (premise)

  C: q (conclusion) In general if R will be interpreted as a fuzzy relation on U x V and F will be interpreted as a fuzzy set on U, sothat C = RoF ( composition of F and R) is a fuzzy set onV where U = domain of x and V = domain of y in otherwords , we haveC(y) = max {min [F(x), R(x, y)]}Where max is taken over all x in U. The given process bywhich the conclusion is derived is called fuzzy inference. The general format of fuzzy inference mechanism(FIM) is as follows:

  1. It consists of several rules (several R’s)each R consisting of one or moreantecedents (one or more F) and only oneconsequent C. The collection of such rulesis called the rule base or fuzzy rule base(FRB).

  2. One or more given facts (matching the totalnumber of antecedents) in the form offuzzy propositions.

  3. The objective is to arrive at the appropriateconclusion(s) via the interpretationsdescribed above and the GeneralizedModus Ponens (GMP).

  B. Quality function deployment (QFD)

  Quality function deployment (QFD), originated in Japan firms to improve the quality. "Deployment" has a much broader meaning than its English translation. In Japan "deployment" refers to an extension of activities. Therefore, "quality function deployment" means that responsibilities for producing a quality item must be assigned to all parts of a corporation (Kogure and Akao, 1983).

II. LITERATURE REVIEW

  Generally a four phase approach is accomplished by using a series of matrixes that guides the product or service team’s activities by providing standard documentation during product and/ or process development

  Picture 1: The four phases of traditional QFD

  The initial and most critical step of the QFD process in our case is, the identification of TV programme. In this step, viewers’ demands, expectations, and complaints are determined.

  As shown in figure 2.1 each phase has a matrix consisting of a vertical column of “What’s” and a horizontal row of “How’s”. “What’s” are CR; “How’s” are the ways of achieving them (CRs). At each stage, the “How’s” are carried to the next phase as “What’s”. As a result, the House of Quality can be built in many shapes and forms.

  Source: M. Ganesh, Introduction to Fuzzy Sets and Fuzzy Logic,PHI New Delhi 2006.

  Identified data contain current viewer’s expectations that are critical to success and potential expectations that would excite viewers. Several methods can be used to establish the viewers' requirements, including: viewer’s panels; focused group discussions; structured or unstructured viewers interviews; selfcompleting questionnaires; in-depth viewers observation; viewers' complaint and compliment database; viewers' service inquiries database; front-line staff feedback. The list of viewer demand was identified with literature search, and focusing on group brainstorming in the concerned audience research unit, which was applied in this study. In the brainstorming process, group considered the complaints that were received from viewers as an input. In addition that small viewer group was chosen for the pilot study. In this study an open question was asked this list was obtained.

  A. Determining the Viewers Demand

III. ANALYSIS AND DISCUSSION

  Picture 2 House of Quality (HoQ) in QFD method which is been derived through the fusion of computer science and management science discipline. Through this approach we try to resolve the issue of identifying the most important incorporable factor among the various almost same looking important factors by suitably deciding the ranking as per their importance in viewers mind and then discarding those factors which are less important or less relevant to accommodate in the proposed production. We start making a suitable HOQ (QFD process) as explained in previous section through the following stages:

  9. Repeat telecast of the programme (time slot)

  17. Appropriate theme for family viewing

  15. Duration of program 16. avoids excessive mid breaks

  14. Characterization

  13. Appealing (presentation)

  12. Related to social environment

  11. Related to viewers environment

  10. Avoids vulgarity in programme

  8. Provides entertainment

  The list of the viewer’s concerns is shown below:

  7. Able to convey the hidden message

  6. Confined to specific group of viewer

  In order to identify most common incorporable factors which will make a programme more popular and successful among its viewer the various important feedbacks of the viewers must be ranked first as per the decreasing or increasing order of importance of a particular factor in viewers mind and then finding what most of the viewers want to see in a particular programme. The task of listing and identifying these factors is so complicated that the audience research unit of the production house becomes unable to sort out the factors correctly and in orderly fashion, to do so we here proposed a novel practical application of fuzzy QFD

  4. Contents of programme

  3. Sufficient well advance promotion

  2. Production house brand name

  1. Cost of production of the programme

  5. Ease in understanding At any one time it is unlikely that TV organization can satisfy all of its viewers' requirements. Therefore it is necessary to prioritize the needs that are to be met within a planning cycle systematically.

• – 0.76 for performance and 0.18 – 0.78 for serviceability which is almost same for both quality attributes thus put them atthe same ranking of quality requirements.

  In this section the researcher will analyze of previous section to conclude the topic and discuss the result; to start with we will prepare a table which is the summary of our findings through the two mentioned approaches i.e. crisp and fuzzy. This will facilitate us in comparison of the two methodology and in deciding the improvement if any

  Table 2 The ratings related with the crisp approach are also normalized using the maximum ratings obtained. As it was mentioned before, normalized individual rating is calculated by dividing individual rating by the maximum rating. Maximum individual rating for the crisp approach is determined as a score of 900.09. This rating value shows that the conformance attribute has a maximum rating and the highest score. For each attribute of the ‘TV programme in question’ normalized value for crisp approaches (as mentioned in above table 4.1) is also calculated as shown in ‘appendix B’, in order for better comparison and analysis.

  Decision on relative ranking of attributes

  Now we will consider each attribute separately or collectively and analyze the scope of improvement (needed or not needed) depending upon its relative ranking of importance (needed to make the TV programme success and popular) through normalized viewers requirement ratings, and make important decision on the attribute ranking

  1 ‘Performance’ vs. ‘Serviceability’

  For a TV programme these characteristics relate to the regional factor such as, ‘related to viewers environment’ or ‘related to social of ‘TV programme’ is the adaptability of the TV show i.e. flexibility in script to accommodate any future changes to make it continuously more interesting as it progresses. Now we observe that ‘Performance’ has a score of 0.51 while considering crisp methodology and ‘Serviceability’ has a score of 0.32 ,which is quite low in terms of importance ranking if compared with ‘Performance’, therefore if we consider crisp approach we would put ‘Serviceability’ in lower ranking in respect to ‘Performance, but the fuzzy methodology consideration imply a rating of 0.31

IV. Implementation

  Since ‘serviceability’, in our case is the capability of the ‘T V programme in question’ for future adaptation to keep it popular, and through fuzzy approach we found its ranking same as the rating of ‘Performance’ i.e. of equal importance, but this important attribute would have not been considered had we considered only crisp rating methodology and would have lost it for equal consideration for improvement. Therefore we conclude about ‘performance’ and ‘serviceability that they are of the same importance and should be considered equally for improvement i.e. the TV programme ‘A’ must have provision to be related to its viewers environment as well as to its social environment and the provision of future adaptability (i.e. flexibility in script, characters and shoot locations etc to kept it popular in long run) at the same level.

  2 ‘Feature’ vs. ‘Conformance’ Feature in our case is, adding prize

  distribution through lottery to the participating viewers and encouraging them to participate through SMS in between the programme or after the programme etc. while

• – 0.62 which is also lowest among other attribute but indicates moderate consideration if consider upper bound.
• – 0.97 and ‘conformity’ obtain a reading of 0.68 – 1.0 which obviously put quality characteristic ‘Conformance’ at the top of ranking but to the quality characteristic ‘Feature’ it also give the same level of importance.

  “the quality and the popularity ” is a Regional Factor that can be considerated as the viewer knowledge about their environment and a bout the Society so that programme will have value attribute and make a good reputation for “Ini Talk show” Net TV- Programme.

  For the popularity factor it can be shown how the programme can be still go on with a nice response from every audience, and the interactively of the viewers and they able to convey each other. The Second step , we can see from the Entertaiment factor always be indicated with the contain of the programe as afunny , joke and a conversation with cover up as a comedian. Beside that The performance are appropriate for the family viewing both of the figure and feature make all the audience feel comfort. For the third step one of the factor that which contributing

  programme consist of : Popularity factor, Entertainment factor, and Regional factor.

  “the quality and the popularity ”of this

  finding and the collect data, viewer’s demand grouped under the three factor which can indicate the

  Show” TV programme that will be known as “Quality and Popularity” attribute. From the

  The three part above the Reseacher finding “ Ini Talk show” TV programme which the element like, conversation, deep interview, a focus group discussion are modified as a joke or a Comedian. Therefore in this research the Fuzzy Logic and Quality Function deployment (QFD) is used to quantify and analyze the information for knowing the best factor contributing “Ini Talk

  Fuzzy Quality Function Deployment approach can describe the activity with that various input are gathered through questionanaires, interview, and focus group Discussion.

  How we can determine the components “Ini Talk Show” to be one of agood TV production by using Fuzzy logic method or Fuzzy Logic and quality Function deployment (QFD).

  1. Conclusion

  The purpose of this research is oriented towards answering these queries on a well structured scientific background and thereby designing a computational prediction model of “TV programme Popularity”. The scientific finding want to identify correctly the most important commo n popularity factors of Sule “ Ini Talk Show” Tvprogrammethrought its audience point view the fans judge them accurately by some appropriate technique.

  0.10

  life which in our scenario of TV programme, it measures how long (time period) the popularity of the show will remain same and keep its viewers stuck to their Television set on regular basis. Now considering the outcome of importance rating through crisp methodology, for ‘Durability’ it is 0.21 which indicates the lowest ranking, while through fuzzy methodology it is

  4 ‘Durability’ Durability measures the le ngth of a product’s

  As we explain previously that Reliability of a product is the likelihood that a product will not fail within a specific time period. This is the key element for users who need the product to work without fail, in our scenario of TV programme it will be like the inclusion of some local regional employment or administrative announcements, or some informative educative content in between the proposed show by which viewers shall feel connected to it on regular basis, Aesthetics is the subjective dimension indicating the kind of response auser has to a product. It represents the individual’s personal preferences. It reflects the ways of individual’s responds to the look, feel, sound, taste, and smell. A person judging the content of the programme would say it is of higher quality but other viewer can judge exactly opposite of this person. Now considering them on crisp rating scale we have 0.81 score for quality requirement ‘Reliability’ while ‘Aesthetics obtain 0.68 which is far below than ‘Reliability’, so through crisp approach we put ‘Reliability’ far head than ‘Aesthetics’, but is it proper to consider ? Let’s have a look on fuzzy methodology! Which suggest the rating of 0.45

  3‘Reliability’ vs. ‘Aesthetics’

  Therefore through the above discussion we conclude to put both of them i.e. ‘Feature and Conformance’ at the same level thus enhancing the feature by introducing viewers participation either through prizes or through SMS participation and well take care of shooting technicality such as proper lighting to shoot correctly, proper camera control, proper audio balancing and vision mixing, proper after shoot editing and audio mixing etc should be taken with equal care and with top priority to make the launching programme a quality success.

  technical aspect of production shoot and post production engineering features like non linear editing, special audio and visual effects etc. Now considering the outcome of importance rating through crisp methodology, it is 0.96 for the quality attribute ‘Feature’ while for ‘Conformance’ it is 1.0 which keep it at the top of ranking while ‘Feature’ comes next to conformance , now so far as fuzzy methodology is concerned quality attribute ‘Feature’ having a rating in the range 0.64

  Conformance i n our case of TV programme is the

• – 0.87 for both of them and thus judge them at equal rank. Therefore we would have been wrong had we considered crisp approach only.

V. SUGGESTION

  The following of suggestions are: 1.

  The next researcher can make an update data collecting for the element of a

  “Quality and Popularity” TV programme

2. The next researcher can build a system or a

  ”fuzzy logic” method in wider scope at TV- channel such as RCTI, SCTV, ANTV, etc.

VI. REFRENCES

  [1]. www. Detik.com [2]. Source [3]. Source:Wikipedia/Television.org [4]. Source:Wikipedia/Quality.org [5]. Source:Wikipedia/Prediction.org [6]. MathWorks, 2005 [7]. Crespo, J., Sicilia, M.A, Garcia, E., Cuadrado J.J, “OnAggregating Second Level Software Estimation

  Cost Drivers: A Usability Cost Estimation Case Study”, Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU 2004, 1255- 1260, Perugia Italia. [8]. Adi Nugroho, 2010 [9]. Jogiyanto,H.M., AnalisadanDesainSistemInformasi,

  PenerbitAndi Offset, Yogyakarta.,2001 [10]. Tan K.C.; Xie M.; Chia E. (1998). “Quality Function Deployment and Its Use in Designing Information

  Technology Systems”.International Journal of Quality &Reliability Management , Vol.15, No.6, pp.634-