• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of the East Asian Society of Dietary Life
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• v.19 no.5
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• pp.703-712
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• 2009

The principal objective of this study was to supply basic material determine basic information regarding effective health promotion regimens for elderly women via a comparative survey of health status by aging age between elderly women (=70 y) and college women. The subject groups of elderly women (=70 y) and college women were selected and surveyed from March to October, 2008, in the Seoul area. The average age of the elderly women assessed in this study was $78.64{\pm}7.30$, the average height was $147.07{\pm}5.72$ cm, and the average weight was $50.47{\pm}7.44$ kg. As compared with college women, a higher percentage of elderly women ate breakfast regularly, but the elderly women also experienced difficulties in chewing due to dentures, and therefore ate their meals with large quantities of liquids, and usually ate their meals within 10 minutes. The majority of elderly women suffered from at least one disease, and the most common symptom reported was hypertension (25%). 52.2% of elderly women and 47.8% of college women reported that they exercised 1~2 times per week. They reported that their favorite exercise was light exercise, such as jogging and athletics (73.1%). As compared with college women, the smoking rate was lower among elderly women, but some of the elderly women were long-time smokers or alcoholics. The differences in red blood cells counts, Hb, hematocrit, and MCV of the between elderly women and college women were significant. In addition, but the MCH and MCHC were higher in elderly women compared with college women and the total cholesterol of elderly woman ($175.62{\pm}38.89$ mg/dL) was significantly lower compared with college woman ($186.13{\pm}28.19$ mg/dL). TG ($127.89{\pm}51.25$ mg/dL) and LDL-cholesterol ($120.51{\pm}32.88$ mg/dL) of elderly woman were significantly higher than TG ($79.71{\pm}40.9$ 6mg/dL) and LDL-cholesterol($103.78{\pm}22.94$ mg/dL) of college woman (p<0.05). The levels of HDL-cholesterol ($58.78{\pm}12.90$ mg/dL) in the college women was significantly higher than the HDLcholesterol levels ($48.17{\pm}13.79$ mg/dL) of the elderly women (p<0.05). Serum vitamin C levels in elderly women were significantly higher than those of college women (p<0.05), whereas no significant difference was detected between the two groups. Consequently, it can be concluded that the appropriate education programs for dietary habits and health promotion are necessary for a healthier life. Additionally, it is necessary for individuals to precisely determine precisely their own health status, and develop appropriate dietary programs for themselves.

• Korean Journal of Agricultural Science
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• v.16 no.2
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• pp.179-200
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• 1989

Mucor miehei rennet(MR) was added as calf rennet(CR) substitutes in the fixed amounts of mixed rennets in making Camembert cheese. The conditions in the variations of chemical composition: water-soluble nitrogen, non-caseinic nitrogen, non-proteinic nitrogen, amino nitrogen, ammoniacal nitorgen, electrophoresis, molecular fractionation, mineral distribution, texture characterisitics, free amino acids and free fatty acids, were checked up with the sensory test and the chesse yields at each ripening period. The results obtained by investigating the utility of Mucor rennet were summarized as follows: 1. CR chesse, MR cheese and the mixed-rennet chesse failed to show any significant difference in their yields of 15%. 2. The contents of protein, fat and ash in MR cheese gave lower value than CR cheese did and with progress of ripening lactose decreased rapidly after 14 days of ripening. The difference among the rate of addition of mucor rennet was not recognized. 3. The WSN contents of 5 fresh sample chesse were from 14.7% to 17.3% and WSN increased from 39.7% to 41.0% with progress of ripening. After 21 days of ripening MR chesse had more WSN than CR cheese did. In NCN and ammoniacal nitrogen MR cheese showed higher value. 4. As the ripening progressed, MR chesse showed more cystein, phenylalanine and proline than CR chesse did but it failed to show any increase in aspartic acid, threonine and glutamic acid etc. 5. In the content of free fatty acid MR chesse showed higher value than CR cheese did and with the progress of ripening fatty acids increased from 8.36 mEq to 26.36 mEq but did not show any significant difference in the cheese types by the coagulant ratio. 6. Ca contents in the sample chesse were 0.238-0.27%, Mg 0.019-0.022%, Na 0.910-1.047%, and K 0.175-0.200%. The important non-sedimentable Ca in casein remained from 61 % to 77% without regard the ripening periods and added-rennets and Mg remained from 59.1% to 92.5% in non-sedimentable and water-soluble conditions. 7. In the fractionation of protein by ultrafilteration, MW> $5{\times}10^4$ decresed from 95% at the beginning period of ripening to 45% and MW< $10^4$ increased from 0.2% to 38% and definite caseinolysis was shown in all samples. 8. All the cheese showed to different electrophoretic patterns for the added-amounts of mucor rennet in the 14 days of ripenig. In the 28 days or ripening, MR cheese kept some bands on the patterns compared with CR cheese. 9. In vitro digestibility increased from 81.48-94.81 % to 94.47-98.61% but failed to show any significant difference in the cheese types by the coagulant ratio. 10. In hardness, MR cheese showed lower value compared with CR cheese as the ripening progressed. 11. The results of the sensory test failed to show any difference in flora rind, feelings in mouth and hands, deep structure, flavor and bitterness between CR Camembert cheese and MR Camembert chesse.

• Tuberculosis and Respiratory Diseases
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• v.44 no.2
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• pp.241-250
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• 1997

Objective : Although the prevalence of pulmonary tuberculosis has decreased progressively after the national control program for tuberculosis began, nowadays the number of MDRTB is increasing seriously. MDRTB tends to be poor responsive to current antituberculosis regimens. It is mainly due to poor compliance, high rate of side reaction of secondary drugs, and limitation in number of available drugs. The purpose of present study is to evaluate the clinical features of pulmonary tuberculosis patients admitted in one national tuberculosis hospital and to expose the problems pertaining to current remedies, to increase the treatment efficacy for pulmonary tuberculosis including MDRTB in the end. Method : Retrospective analysis of 336 pulmonary tuberculosis patients admitted in National Masan Tuberculosis Hospital was done. Contents of analysis were patients profile, the first diagnosed time and medical institutes, family history, residence, previous treatment history, chief complaints at the time of admission, lesion site on chest X -ray film, combined deseases, side reaction to antibuberculosis drugs, used drugs before admission and the results of drug sensitivity test. Results : The ratio between male and female was 4 : 1. Age showed relatively even distribution from 3rd to 6 th decades. 64.6% of the patients was diagnosed at public health center. Weight loss was the most common complaint at admission. Bilateral lesions on chest X-ray films were 59.8%. 130patients had combined desease, of which DM was the most common(37.7%). 95patients had family history, of which parents were the most common(41.7%). According to the time of first diagnosis, 31 patients were diagnosed before 1980, and after then the number of patients was increased by degrees. Residence overwhelmed in pusan and gyung-nam province. 258 patients got previous treatment history, of which 112 patients(43.4%) had more than 3 times and only 133 patients(51.6%)got regular medication. 97 patients used more than other 3 drugs in addition to INH, EMB, RFP and PZA before admission. 154 patients were informed with the results of drug sensitivity test. of which 77 patients had resistance to more than 5 drugs. Gastrointestinal problem was the most common in side reaction to drugs. Conclusion : In the case of weight loss of unknown cause, tuberculosis should be suspected. In first treatment, sufficient and satisfactory explanation for tuberculosis is necessary and treatment period should not be stict to 6 month-short term therapy. In retreatment, new drugs should not be added to used drugs even though drug sensitivity results show sensitivity to some of them. Proper time for surgical intervention should not be delayed.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.145-156
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• 2015

Purpose : The purpose of this study is to evaluate the efficiency of Split VMAT planning(Contouring rectum divided into an upper and a lower for reduce rectum dose) compare to Conventional VMAT planning(Contouring whole rectum) for prostate cancer radiotherapy involving pelvic lymph nodes. Materials and Methods : A total of 9 cases were enrolled. Each case received radiotherapy with Split VMAT planning to the prostate involving pelvic lymph nodes. Treatment was delivered using TrueBeam STX(Varian Medical Systems, USA) and planned on Eclipse(Ver. 10.0.42, Varian, USA), PRO3(Progressive Resolution Optimizer 10.0.28), AAA(Anisotropic Analytic Algorithm Ver. 10.0.28). Lower rectum contour was defined as starting 1cm superior and ending 1cm inferior to the prostate PTV, upper rectum is a part, except lower rectum from the whole rectum. Split VMAT plan parameters consisted of 10MV coplanar $360^{\circ}$ arcs. Each arc had $30^{\circ}$ and $30^{\circ}$ collimator angle, respectively. An SIB(Simultaneous Integrated Boost) treatment prescription was employed delivering 50.4Gy to pelvic lymph nodes and 63~70Gy to the prostate in 28 fractions. $D_{mean}$ of whole rectum on Split VMAT plan was applied for DVC(Dose Volume Constraint) of the whole rectum for Conventional VMAT plan. In addition, all parameters were set to be the same of existing treatment plans. To minimize the dose difference that shows up randomly on optimizing, all plans were optimized and calculated twice respectively using a 0.2cm grid. All plans were normalized to the prostate $PTV_{100%}$ = 90% or 95%. A comparison of $D_{mean}$ of whole rectum, upperr ectum, lower rectum, and bladder, $V_{50%}$ of upper rectum, total MU and H.I.(Homogeneity Index) and C.I.(Conformity Index) of the PTV was used for technique evaluation. All Split VMAT plans were verified by gamma test with portal dosimetry using EPID. Results : Using DVH analysis, a difference between the Conventional and the Split VMAT plans was demonstrated. The Split VMAT plan demonstrated better in the $D_{mean}$ of whole rectum, Up to 134.4 cGy, at least 43.5 cGy, the average difference was 75.6 cGy and in the $D_{mean}$ of upper rectum, Up to 1113.5 cGy, at least 87.2 cGy, the average difference was 550.5 cGy and in the $D_{mean}$ of lower rectum, Up to 100.5 cGy, at least -34.6 cGy, the average difference was 34.3 cGy and in the $D_{mean}$ of bladder, Up to 271 cGy, at least -55.5 cGy, the average difference was 117.8 cGy and in $V_{50%}$ of upper rectum, Up to 63.4%, at least 3.2%, the average difference was 23.2%. There was no significant difference on H.I., and C.I. of the PTV among two plans. The Split VMAT plan is average 77 MU more than another. All IMRT verification gamma test results for the Split VMAT plan passed over 90.0% at 2 mm / 2%. Conclusion : As a result, the Split VMAT plan appeared to be more favorable in most cases than the Conventional VMAT plan for prostate cancer radiotherapy involving pelvic lymph nodes. By using the split VMAT planning technique it was possible to reduce the upper rectum dose, thus reducing whole rectal dose when compared to conventional VMAT planning. Also using the split VMAT planning technique increase the treatment efficiency.

• Journal of Nutrition and Health
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• v.47 no.6
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• pp.463-474
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• 2014

Purpose: The aim of this study was to assess the food environment, particularly focusing on restaurants in three areas (Suwon city, Hwaseong Byeongieom-dong, and Bibong-myun). Methods: A total of 662 persons were surveyed on customers' perceptions of the food environment in restaurants. A structured questionnaire composed of 30 questions on 7 factors, sanitation (4 items), displaying information (5), food quality (12), information on nutritional and healthy food choice (6), restaurant's accessibility (1), availability (1), and affordability (1) was used. In addition, an expert assessment of restaurant sanitation, and information on nutritional healthy food choice was conducted through visiting 126 restaurants. Results: Scores (range of score : 1~7) for each factors assessing the restaurant food environment were 5.06 for sanitation factors, 5.05 for displaying information factors, 5.13 for taste appearance factors, and 4.35 for healthy menu factors. Informations on nutritional healthy food choice showed a low rate: only 16.24% of the subjects answered that there is a message encouraging choice of healthy foods and 27.4% answered that menus contain nutritional information. Significant differences in food environment were observed by region (city, town, rural). The restaurants food environment in the rural area turned out to be poorer than that of the other two areas. In comparison of customer perception and expert assessment, significant differences were observed for 'Employee appearances and uniforms are clean and tidy' (p < .05), and 'There is a message encouraging the choice of healthy foods' (p < .05). Conclusion: This study provided evidence for differences of restaurant food environment by regions. In the rural area, there is a problem in restaurant's accessibility, availability, and affordability because of a lack of variety in menu items and restaurants. This results suggest that there is a need for more healthy food restaurants in the rural area.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.207-221
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• 2012

Air temperature in Korea has increased by $1.5^{\circ}C$ over the last 100 years, which is nearly twice the global average rate during the same period. Moreover, it is projected that such change in temperature will continue in the 21st century. The objective of this study was to evaluate the potential impacts of future climate change on the rice production and adaptation methods in Korea. Climate data for the baseline (1971~2000) and the three future climate (2011~2040, 2041~2070, and 2071~2100) at fifty six sites in South Korea under IPCC SRES A1B scenario were used as the input to the rice crop model ORYZA2000. Six experimental schemes were carried out to evaluate the combined effects of climatic warming, $CO_2$ fertilization, and cropping season on rice production. We found that the average production in 2071~2100 would decrease by 23%, 27%, and 29% for early, middle, and middle-late rice maturing type, respectively, when cropping seasons were fixed. In contrast, predicted yield reduction was ~0%, 6%, and 7%, for early, middle, and middle-late rice maturing type, respectively, when cropping seasons were changed. Analysis of variation suggested that climatic warming, $CO_2$ fertilization, cropping season, and rice maturing type contributed 60, 10, 12, and 2% of rice yield, respectively. In addition, regression analysis suggested 14~46 and 53~86% of variations in rice yield were explained by grain number and filled grain ratio, respectively, when cropping season was fixed. On the other hand, 46~78 and 22~53% of variations were explained respectively with changing cropping season. It was projected that sterility caused by high temperature would have no effect on rice yield. As a result, rice yield reduction in the future climate in Korea would resulted from low filled grain ratio due to high growing temperature during grain-filling period because the $CO_2$ fertilization was insufficient to negate the negative effect of climatic warming. However, adjusting cropping seasons to future climate change may alleviate the rice production reduction by minimizing negative effect of climatic warming without altering positive effect of $CO_2$ fertilization, which improves weather condition during the grain-filling period.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Culinary science and hospitality research
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• v.22 no.7
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• pp.112-130
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• 2016

In this study the moisture content and chromaticity of fresh made lotus leaf powder added Cheongpomuk to utilize various efficacy of lotus leaf for processed food, as well as chromaticity, moisture content change, texture, total phenolic compound content, DPPH radical scavenging ability and preference of lotus leaf powder added Cheongpomuk with different storage period have been measured and analyzed. From the texture of lotus leaf powder added mung bean as per the storage period, the hardness of fresh Cheongpomuk were $0.38g/cm^2$ from control group, $0.40g/cm^2$ from CCD 1% group, $0.42g/cm^2$ from CCD 3% group, $0.37g/cm^2$ from CCD 5% group, $0.42g/cm^2$ from GGD 1% group, $0.39g/cm^2$ from GGD 3% group, $0.35g/cm^2$ from GGD 5% group, $0.39g/cm^2$ from JLD 1% group, $0.33g/cm^2$ from JLD 3% group, and $0.32g/cm^2$ from JLD 5% group. It has shown that JLD 5% group was the lowest, while CCD 3% group and GGD 1% group were the highest, and there were significant differences among sample groups. For DPPH radical scavenging ability, that of GLD 5% group was 22 times higher than that of control group. In addition, the tendency was increasing by increasing the adding rate of lotus leaf powder though there was some tolerance among sample groups. For total phenolic compound content, that of control group was 6.65 mg CE/100 g, and others were 7.48 mg CE/100 g from CCD 1% group, 15.82 mg CE/100 g from CCD 3% group, 20.15 mg CE/100 g from CCD 5% group, 15.55mg CE/100 g from GGD 1% group, 23.02 mg CE/100 g from GGD 3%, 26.95 mg CE/100 g from GGD 5% group, 3.92 mg CE/100 g from JLD 1% group, 16.72 mg CE/100 g from JLD 3%, and 26.58 mg CE/100 from JLD 5% group. From the analyzing result of responses for color and scent, taste, elasticity, and total preference of lotus leaf powder added Cheongpomuk between two panel groups, there was significant difference for the color, higher from professional cooking instructor group, but there were no significant difference between two groups for all other factors among professional cooking instructors and cooking department students. According to the results, it is expected that various functional foods can be developed by utilizing lotus leaf powder, depending on the growth condition and cultural environment of each region by adding 3% of lotus leaf powder, would be the most suitable recipe for Cheongpomuk.