Favorite Products Research Articles

UJI OPTIMALISASI DAYA HAMBAT EKSTRAK DAUN TEH HIJAU (Camellia Sinensis) TERHADAP PERTUMBUHAN BAKTERI Escherichia coli DAN Staphylococcus aureus

Research on substances as new antibiotics to inhibit or kill bacteria that are resistant to antibiotics needs to be done. One of the simplicia has an antibacterial effect is the leaves of green tea (Camellia sinensis). Antibacterial content the leaves of green tea (Camellia sinensis), namely alkaloids, saponins, tannins, and catechins (polyphenols). Tea one of the favorite products from Indonesia’ estate. The purpose of this study was to determine optimization of the inhibitory power the leaves of green tea’s (Camellia sinensis) extract against the growth of Escherichia coli and Staphylococcus aureus. This research is an experimental laboratory conducted at Bacteriology”s Laboratory, Department of Medical Laboratory Technology Surabaya in November 2020 - April 2021. This study uses the Kirby Bauer disk diffusion method, namely Mueller Hinton Agar (MHA) media which has been planted with Escherichia coli and Staphylococcus aureus with disks that have been prepared. soaked in the leaves of green tea’s (Camellia sinensis) extract at concentrations of 25%, 50%, 75%, and 100% and then incubated for 24 hours in an incubator. The results can be concluded the leaves of green tea’s (Camellia sinensis) extract can be used as an antibacterial. Optimal of results in this research were Escherichia coli at a concentration of 25% with an average diameter of 10,25 mm and Staphylococcus aureus at a concentration of 100% with an average of 22,5 mm. This is because content the leaves of green tea’s (Camellia sinensis) is catechins and alkaloids as strong antibacterials

Aplikasi Titip Online Produk UMKM Berbasis Android

UMKM have a big role in increasing economic growth in the region by increasing the number of UMKM in an area, it will show that buying and selling transaction activities will increase, not least in Selong District, East Lombok Regency. With the presence of the new UMKM, it is able to be a solution to reduce unemployment in East Lombok Regency, but in addition to being able to reduce the unemployment rate, it is very necessary to do how so that the products of UMKM actors can be accessed more widely, because considering the community at this time very active in using smartphones. The purpose of this research is to create an application that will be able to accommodate all forms of products of UMKM actors in Selong District which of course with this application will be able to benefit both parties, namely the community as customers can search for their favorite UMKM products via smartphones, while for UMKM actors can promote their products more broadly so that they can increase the number of sales than before.

NGHIÊN CỨU QUY TRÌNH TẠO ĐỒ UỐNG TỪ DỊCH CHIẾT CÂY TÍA TÔ (Perilla frutescens L. Britton)

Perilla frutescens (L.) Britton is well known as a herb and medicinal plant in ietnam and some East Asian countries. Perilla drinks is a favorite product in Japan. In Vietnam, researches on processing perilla into beverage and juce are quite limited. In this study, we built a process to prepare a quality perilla drinks to meet the requirements of food safety and hygiene. A suitable ratio of perilla and water for preparing perilla extract was 1 : 3 (kg\L). The perilla juice prepared from this extract by supplementation of 15% sucrose and 0.3% citric acid had good sensory score of 18.5 ± 0.05. The content of some active substances such as total phenolic compounds, flavonoid, reducing sugar of the perilla extract reached 5.817 ± 0.172; 5.443 ± 0.016; 1.994 ± 0.003 (mg\mL) respectively and had almost no significantly difference than that of the perilla drinks prepare from this extract (4.737 ± 0.0135; 4.750 ± 0.0235; 1.963 ± 0.014 (mg\mL). The content of anthocyanin in dry mass of Perilla frustescens (L.) Britton was 0.6011 ± 0.002 (mg\g) but it was not detected in the perilla extract and drinks. Antioxidant activity of perilla extract and drinks determined by IC50 on DPPH were 105,46 and 103,92 mg\mL respectively. Results of counting total aerobic microbes and coliform showed that a sterilized\pasteurilized perilla drinks met the requirements of food safety and hygiene in 25 days stored at 4 - 30 ᴼC.

Product line of selected agricultural entity in Slovakia and suggestion for its expansion based on analysis of consumers' interest in dairy and meat products

Studies on primary agricultural production in Slovakia aimed mainly at biological, economic, or market point of view and there is a lack of managerial approach providing a specific recommendation for farmers according to their production lines or planning process. As a reaction, we are providing a practically oriented study based on the selected livestock producer, which is aimed at statistical significances as an establishment for further recommendations for management and marketing of this entity. The paper aims to analyze the views and preferences of customers of the monitored company, which sells its meat and dairy products in its stores and verify the expected success of the planned expansion of the product lines. Regarding this, the online questionnaire study was conducted on a sample of 202 respondents. Realized statistical analysis based on the Kruskal-Wallis nonparametric test and subsequent Bonferroni post hoc correction signify that meat products, fresh meat, and slaughter specialties are the most favorite products among customers of the monitored company. Fresh milk, on the other hand, is not as attractive as a meal for them. However, selling it from vending machines placed out of the store would increase the sales. Dairy products of own production should be even more successful, as we assume they would be as interesting for customers as the currently expanding portfolio of meat products. The benefit of this study lies in the consideration of the practical use of the obtained results in the business practice of the monitored company. Regarding this, we are providing a set of recommendations, according to the planning of their product lines and connected marketing tools for their successful placement on the market.

AUDIT ENERGI PROSES PENGOLAHAN TEH HITAM (CTC) DENGAN SISTEM PENGAMBILAN KEPUTUSAN METODE SPACE

The favorite product of black tea is tea leaf that are ground using the crush, tear and curl (CTC) method. This process able to produce the dry tea which has high quality with a strong aroma and taste, and high levels of antioxidants. This study aimed to conduct an energy analysis on the processing of black tea CTC at PTP. Nusantara VIII Rancabali to find out the steps towards efficient use of energy, opportunities and conservation efforts. The research method used is descriptive analysis method. The present paper conducted the energy audit calculations which are based on the energy consumption in each tea processing activity from the time. The calculation of energy audit was conducted from preparation of raw materials until the packaging of tea product. The results of the energy audit on the CTC black tea processing showed that for each ton of tea leaves required the energy is about 3.930,66 MJ.ton-1The greatest energy use is drying process which is at 1.424,67 MJ.ton-1 or 36,24%. The results of the analysis space was at quadrant conservative aggressive. Aggressive conservative steps that can be taken in the black tea processing are to develop activities towards energy saving, such as changing fuel from ordinary wood to wood pellets and adding or modifying machine tools so that the installed capacity of each processs to fulfill the capacity input of leaf tea. Key words: CTC, energy analysis, energy saving, processing of tea

Research on e-Commerce User Behavior Analysis Based on Big Data Collaborative Recommendation Algorithm

With the rapid development of Internet, users tend to purchase their favorite products through Internet transactions and online payment. The general trend of e-commerce development in China is that physical trading places are gradually replaced by online trading platforms on the Internet. In this paper, the restricted Boltzmann machine based on category conditions is used to describe the user's own interest preference by using the objective label of the project itself. In this process, only the project information that the user has scored is used, which strengthens the user's personalized needs. The method fully mines user behavior information, replaces commodity content big data with user behavior information as a recommended data set, and can actively push commodity content that users may be interested in to users. Experimental results show that the accuracy of RBM ( Restricted Boltzmann machine) model with nearest neighbor is higher than that of the original model, and the anti-over-fitting ability of the model is also improved.

The Juxtapose of Placement in Retail Outlet-Impact Over Instore Behavior

Marketing strategies have evolved to affect the buying behavior. The location of a shelf in a supermarket is important. The probability of a consumer to choose the product over similar ones that aren't at the eye level to the product at the eyelevel on the shelves is more. Brands pay slotting fees to limit shelf space for their competitors. It is a tempting technique to put products in the path of customers. The location where a product is found such as the middle shelf or at the end of the aisle (end cap) can prompt purchases. This study was conducted among shoppers in all age groups, students, working professionals, homemakers, etc. 103 questionnaires were collected. The objectives were, to know the shopping preference of customer, whether any unplanned product is bought and reasons the customer chooses a product and the impact of eyelevel placement on purchase. It was observed that customers prefer both online and retail stores. Customers buy products because of brand loyalty, sales promotion, and in store advertisements. It was also observed that Placement of products does impact the selection of products over otherwise placed products. Customers search for their favorite product, and are drawn to promotions such as offers, discounts etc. even though they come with a planned list. Eyelevel marketing makes them buy unplanned products. This study revealed the impact of promotion, branding, and eye level marketing among retail customers, across the selected responses.

Predicting Molecular Weight Distribution, Melt Flow Index, and Bulk Density in a Polypropylene Reactor via a Validated Mathematical Model

One of the main goals of polymer science has been to relate the process variable to their vital macroscopic properties in order to obtain tailor-made products. In particular, this goal is significant when we have to use a catalyst that has a unique and unknown behavior with its own complex kinetics such as a Ziegler–Natta catalyst for polypropylene production. Today, computer simulation with acceptable accuracy has come to the aid of polymer science. The final product properties are highly dependent on the crucial factors comprising the average molecular weight, its dispersity, and bulk density of a polymer, and these factors also depend on process variables with the complexity of a kinetic reaction. A mathematical model can be a worthy replacement to the conventional manner, experiment by trial and error, for designing a favorite product. In this study, a mathematical model is proposed to fulfill this aim. By the model with its offered algorithm, kinetic constants can be easily adjusted with fairly good prediction of the desired product. The modeling approach is a polymer moment balance technique (population balance) in a slurry semibatch reactor and coded in MATLAB/SIMULINK software. The model has been validated via experimental data from a laboratory scale reactor with an acceptable margin of error.

Neural text similarity of user reviews for improving collaborative filtering recommender systems

Abstract According to the advent of technology and the expansion of using the World Wide Web, there has been an enormous increase in the number of Internet retailers and their customers. The amount of data is exploding due to the numerous users and the variety of products. In such a condition, recommender systems play an important role in helping users and providing suggestions based on their taste. Using recommender systems’ suggestions, users can save their time on finding their personalized, useful, and favorite items without being overwhelmed by a large set of items. User-based collaborative filtering recommender systems for each user find similar users based on their ratings and suggest their favorite products to the intended user. In this paper, we present a model to improve recommender systems by finding similar users based on their reviews in addition to their ratings. To this end, we compute users’ reviews similarity utilizing seven different approaches, out of which two techniques are lexical-based, two techniques benefit from the neural representation of words, and three techniques are based on the neural representation of texts. Our experiments on two different datasets from Amazon show that the proposed model for capturing review’s similarity significantly improved the performance of the recommender system. Moreover, the model based on Long Short Term Memory (LSTM) network achieves the best results.

Product Recommendation Based on Analysis of Aesthetic Elements Used to Customer’s Favorite Products

Product Recommendation Based on Analysis of Aesthetic Elements Used to Customer’s Favorite Products

Use of kombucha culture in the production of fermented dairy beverages

Kombucha is a beverage obtained by fermenting tea containing sugar as a result of the symbiotic relationship between yeast and acetic acid bacteria. In this study, milk and various herbal teas (sage, blackberry, and green tea) were mixed in the ratio of 60:40 (v/v) and fermented with kombucha culture. 2.2-Diphenyl-1-picrilhydrazyl (DPPH) radical scavenging activity, total phenolic content, total reducing sugar content, and the microbiological and sensory properties of the fermented dairy beverage were examined. The highest DPPH radical scavenging activity was observed on the 1st day of storage of the blackberry tea-blended fermented beverage (98.48%), and the highest total phenolic content was observed on the 30th day of the green tea-blended fermented beverage (81.51 mg/mL). The maximum amount of glucuronic acid (0.42 g/100 mL) was observed on the 20th day of storage in the sage-blended fermented dairy beverage. The most favorite product was the blackberry blend, whereas the least favorite was the dairy beverage (control sample) fermented with kombucha based on sensory scores. This study demonstrates that milk and herbal teas could be successfully fermented with kombucha culture, thereby improving its functional properties.

APLIKASI E-COMMERCE BERBASIS WEB MENGGUNAKAN METODE WEIGHTED MOVING AVERAGE DAN K-MEDOIDS

Sugi Jaya Mandiri, Ltd. is a company specializing in sales of industrial equipments, such as cables, pipes, construction materials, machine spareparts et cetera. The company processes data manually by using Microsoft Excel. The process complicates data recapitulation, especially concerning large amounts of data. Another issue is the lack of advertising towards customer. This application aims to solve the problems by implementing data processing feature with Weighted Moving Average timeseries method and favourite product feature to better market products to prospective customers using k-Medoids clustering method.Preliminary evaluations using k-Medoids method shows two products fit to advertise by considering attributes such as sold amount, mean sold amount and transaction amount. Data evaluation using Weighted Moving Average method acquires sales forecast with Accuracy rate of 92.456%.

The influence of big data analysis of intelligent manufacturing under machine learning on start-ups enterprise

ABSTRACT In order to solve the problem that enterprises waste resources and make wrong decision caused by lack of comprehensive grasp of production, so as to realise intelligent manufacturing under the background of big data and improve the level of intelligent manufacturing of the newly created enterprises, machine learning method is used to make reasonable predictions on the customer’s favourite products and combinations. The research results show that the diagnosis and introspection are predicted through the manufacturing data collection assessment to realise intelligent manufacturing system, optimisation of intelligent manufacturing decision space, provide visual guidance for intelligent manufacturing.

An event-related potential study of consumers’ responses to food bundles

We conducted two event-related potentials (ERP) experiments to investigate consumers' responses to different types of food bundles. In Experiment 1, the participants were instructed to indicate their wanting of a three-yogurt bundle when their neural activity was recorded. The results of self-report wanting scores revealed that the participants wanted bundles consisting of their favorite yogurt products more than those of disliked products. Such a difference in self-report scores was also indexed by the N2 in frontal brain and the P1 in the left hemisphere. By contrast, bundles consisting of three different yogurt products elicited a smaller amplitude of the N2 than bundles consisting of two favorite products and one disliked product, but these two types of bundles received comparable wanting scores. Moreover, we asked the participants in Experiment 2 to perform a visual discrimination task on these bundles, and did not found these effects on the N2 or the P1. Collectively, these results revealed neural activities underlying consumers' responses to food rewards, and demonstrated the role of individuals’ variety-seeking tendency in wanting process.

A Hybrid Leaf Disease Detection Scheme using Grayco-Occurance Matrix Support Vector Machine Algorithm

An Indian economy depends upon the agriculture up to 70% approximately. Hence, there is a need to Take care of agriculture and its resources. In such aspects, the plant disease and leaf disease is one of the major concerns that affect the overall processing of producing food, feed, fiber and many other favorite products by the cultivation. It is one of the reasons that disease identification and detection in plant adopts a significant job in agro industry area. Due to this reason, appropriate detection methodology consideration is to be taken here. Most of the research focused more on combining image processing and soft computing algorithms to solve this issue. With this motivation, this research utilize Median filter for noise removal in initial stage. Later, Hue-Saturation-Value is used for preprocessing. Further, Fuzzy C-Means Clustering (FCM) considered for clustering image samples at different iteration. Finally, the research considered a hybrid mechanism by combining Gray Co-Occurrence Matrix and Support Vector Machine. Further, the proposed method results better outcome in terms of efficiency as 87.43% K-nearest neighbor (KNN) classifier, Color Transform and Exponential Spider Monkey Optimization.

Skin Aging & Modern Edge Anti-Aging Strategies

Skin Aging & Modern Edge Anti-Aging Strategies

Improve the technology of brynza from sheep's milk by adding a bioprotective culture

Brynza is a compulsory product of the daily diet of the inhabitants of the Carpathians and a favorite product for many other consumers, but contains from 4 to 7% of salt. The consumption of a large amount of salt can cause many diseases. The current task of the present is to find ways to extend the shelf life of products provided that the content of their kitchen salt is reduced. One of the ways to reduce the content of the salt is the partial replacement of potassium chloride. The aim of the research was to investigate the course of microbiological processes in brine cheese, the traditional technology of which was improved by 20 and 30% replacement of the salt with potassium chloride in brine and using the bioprotective culture, as well as determining the storage time of the cheese. Preparates used by Chr. Hansen: were used to ferment RSF-742 fermentation culture containing 2 strains of mesophilic and 2 strains of thermophilic microflora, Fresh-Q bioprotection culture and enzyme preparation ‑ CHY-MAX. The action of the Fresh-Q bioprotection culture is aimed at inhibiting the development of yeast and mold, which includes L. rhamnosus. There were made 6 samples of cheese from sheep's milk: K – control sample using the kitchen salt (sodium chloride); D1 and D2 – brynza, made of 20 and 30% by substitution of sodium chloride with potassium chloride, respectively; KF – cheese made using sodium chloride and Fresh-Q bioprotection culture; DF1 and DF2 – brynza, made of 20 and 30% sodium chloride replaced by potassium chloride, respectively, using Fresh-Q. It has been established that the use of Fresh-Q bioprotection culture has a greater effect on organoleptic properties than the replacement of the kitchen salt. According to the results of the score, the highest score was obtained with samples using a bioprotective culture. It is proved that the replacement of the kitchen salt and the use of Fresh-Q provides a high quality product and its compliance with the requirements of regulatory documentation. The study of the course of microbiological processes confirms the expediency of improving the traditional technology of the production of brynza by partial replacement of the kitchen salt with potassium chloride and the addition of Fresh-Q. The research results confirm that the cheese storage period is lengthened by 10 days in samples made using Fresh-Q bioprotection culture.

Evaluation of Iranian wood and cellulose industries

Iranian Wood and Cellulose Industries (IWCI) are distinguished via a minimum quantity of wood consumptions with high wastages rates along with favourite products generation. IWCI exposed to lots of obstacles in the way of maturation and expansion especially in terms of technologies assigned and overdependence on input materials entered into industries cycle. Present cluster study of IWCI empirically targeted an assessment of technologies, input and output materials streams, existing facilities in industries individually. SPSS Software along with Delphi Fuzzy theory and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods were assigned to evaluate the data of industries as findings of Iranian evaluator team once before construction of industries. T-test analysis had represented significant differences around (pvalue≤ 0.001, 0.002) among main criteria of IWCI such as the number of employees, power, water and fuel exploitations and the land area occupied by each industry. Using Friedman test the ranks values were obtained about 2.59, 4, 1.53, 1.88 and 5 for the number of employees, power, water, fuel consumed and land area applied in the location of industries. Analytical Hierarchy Process (AHP) via Delphi Fuzzy set, Fuzzy TOPSIS and TOPSIS resulted to a hierarchical classification among IWCI.

Evaluation of Quality Parameters and Shelf Life of Thai Pork Scratching “Kaeb Moo”

Fried foods are one of the most favorite products worldwide because of their typical flavor and crispness. In Thailand, one of the most popular traditional foods is “Kaeb Moo,” a fried pork rind product typical of the Northern Region and widely consumed across the whole country. In this research, we monitored the quality change of Kaeb Moo during storage for 1 month and predicted the consumers’ acceptance measuring texture, moisture contents, malondialdehyde (MDA) and hexanal contents, and peroxide values (PV) of frying oil, as this fried product undergoes a rapid hydrolysis and rancidity. The analyses were done on three types of Kaeb Moo: the first type was prepared in the lab using high-quality products, while the other two types were purchased from local markets in Thailand. It was found that rancidity variation during storage strongly depends on the frying process and product quality, as in 31 days the hexanal content only doubled (225%) in Kaeb Moo type 1, while reached 542% and 962%, in Kaeb Moo type 2 and type 3, respectively. The increase of rancidity was observed even if the peroxide values of frying oil were under the national regulation. At the end of shelf life, the properties of Kaeb Moo samples from predicting equations were as follows: 3.67–6.01% moisture contents, 0.396–0.503 µg/g MDA contents, 0.342–0.481 mg/kg hexanal contents, 50.01–60.08 kg·s linear distances (crispness), 36.01–48.83 mm rancid rating, and 43.72–45.38 mm crispness rating.

The Characteristic of Porang Flour (Amorphophallus muelleri Blume) Purification Use Ethanol and The Application as Subtitution Agent on Chicken Sausage

Abstract: Pouring flour contains high glucomannan which can reach 65 %. This research purposed to analyze the physical and chemical of porang flour purification use ethanol and to describe the effect of the proportion of tapioca and porang flour addition to the physical, chemical, and organoleptic of chicken sausage. Randomized Complete Block Design was applied with two-phase. The first stage was the purification process used ethanol with different concentration (60%, 75%, and 90%). The second phase was the addition of orange and tapioca flour (gram) (0:20, 1:19, 2:18, 3:17, 4:16, 5:15, 6:14), all treatment was replicated 3 times. The results of the first process showed that there was a very significant difference effect to the glucomannan, rendemen, viscosity, and color (lightness and yellowish) of pouring flour. The best treatment was the purification by ethanol 90% with 11,2 % water content, 0,78% ash content, 58,20% glucomannan, 78, 11% rendered, and 3,33 dPas viscosity. The second treatment results described that there was a very significant effect of tapioca and pouring flour addition to the water content, ash content, fat, protein, carbohydrate, color intensity (L, a+, and b+), and organoleptic (taste, aroma, appearance, and favorite product) of chicken sausage.