QUALITY AND POPULARITY PREDICTION MODELING OF TV
PROGRAMME THROUGH FUZZY QFD
Minarya Sitepu1, Sinar Sinurat2, Anggiat Hatuaon Sihite3
Mahasiswa Teknik Informatika STMIK Budi Darma Medan1 Dosen Tetap STMIK Budi Darma Medan23
Jl. Sisingamangaraja No. 338 Sp. Limun Medan123
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
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 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 the benchmark of viewer’s expectations? These and several other questions often come in producers mind when a well invested project faces a drastic failure.
II. LITERATURE REVIEW
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)
In general if R will be interpreted as a fuzzy relation on U x V and F will be interpreted as a
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 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).
Generally a four phase approach is accomplished by using a series of matrixes that
guides the product or service team’s activities by
Picture 1: The four phases of traditional QFD
Source: M. Ganesh, Introduction to Fuzzy Sets and Fuzzy Logic,PHI New Delhi 2006.
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.
III. ANALYSIS AND DISCUSSION
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
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:
A. Determining the Viewers Demand
The initial and most critical step of the QFD process in our case is, the identification of
‘what’ TV viewer want and expect from a good
TV programme. In this step, viewers’ demands,
expectations, and complaints are determined.
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.
The list of the viewer’s concerns is shown below:
1. Cost of production of the programme 2. Production house brand name 3. Sufficient well advance promotion 4. Contents of programme
5. Ease in understanding
6. Confined to specific group of viewer 7. Able to convey the hidden message 8. Provides entertainment
9. Repeat telecast of the programme (time slot) 10. Avoids vulgarity in programme
11. Related to viewers environment 12. Related to social environment 13. Appealing (presentation) 14. Characterization
15. Duration of program 16. avoids excessive mid breaks
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.
IV. Implementation
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
environment’, and Serviceability in our scenario
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
– 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.
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’
Conformance in our case of TV programme is the 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 –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.
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.
3‘Reliability’ vs. ‘Aesthetics’
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!
Durability measures the length of a product’s 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 0.10 – 0.62 which is also lowest among other attribute but indicates moderate consideration if consider upper bound.
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.
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). Fuzzy Quality Function Deployment approach can describe the activity with that various input are gathered through questionanaires, interview, and focus group Discussion.
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
Show” TV programme that will be known as
“Quality and Popularity” attribute. From the
finding and the collect data, viewer’s demand grouped under the three factor which can indicate
the “the quality and the popularity ”of this
programme consist of : Popularity factor, Entertainment factor, and Regional factor.
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 “the
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.
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
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[7]. Crespo, J., Sicilia, M.A, Garcia, E., Cuadrado J.J,
“OnAggregating Second Level Software Estimation
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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
