International Journal of Trend in Scientific Research and Development

In the growing world of modernization, mental health issues like depression, anxiety and stress are very normal among people and social media like Facebook, Instagram and Twitter have boosted the growth of such mental health. Everything has its legitimacy and negative mark. During this pandemic, people are more likely to suffer from mental health issues, they are available 24 7 and are cut off from the real world. Past examinations have shown that individuals who invest more energy via online media are bound to be depressed. In this project, we find out people who are depressed based on their tweets, followers, following and many other factors. For this, I have trained and tested our text classifier, which will distinguish between the user who is depressed or not depressed. 

by Rahul Kumar Sharma | Vijayakumar A "Depression Detection in Tweets using Logistic Regression Model" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd41284.pdf 

Paper URL: https://www.ijtsrd.comcomputer-science/data-miining/41284/depression-detection-in-tweets-using-logistic-regression-model/rahul-kumar-sharma

callforpaperlifesciences, lifesciencesjournal, researchpapers

Video games are a source of entertainment for different age groups. Players who are seeking quality video games spend more money on their systems. In this way they spend a hefty amount on internet, storage, GPU etc. Due to the addictive nature the cost is not negligible and there are not so many researches done on predicting the cost a player has to suffer. In this paper, the gaming cost is being determined by applying different algorithms. Data was collected from different age groups with different characteristics like the choice of storage options, game genres, internet speed and time they spend on games. Different models are being used like Ada boost, logistic regression, Decision tree and Random forest to check the accuracy of prediction analysis. This research will help in development of further models which can measure the gaming cost more accurately. MD. 

by Rhineul Islam | Nakib Aman Turzo | Pritom Sarker Bishal "Prediction Analysis of Gaming Cost By Employing Data Mining Algorithms" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd38566.pdf 

Paper URL: https://www.ijtsrd.com/computer-science/data-miining/38566/prediction-analysis-of-gaming-cost-by-employing-data-mining-algorithms/md-rhineul-islam

callforpaperlanguages, languagesjournal, bestjournal

Companies usually have historical data on sales transactions from month to month, but unfortunately, they are only used as weekly and monthly reports. If it is allowed to continue for longer, there will be data growth which results in data richness but poor information. At the same time, companies often still use manual methods in their product marketing strategies that have no reference and are only based on estimates. One of them is the X Fashion Store that sells various local fashions. X Fashion Store has not used data to develop their marketing strategy. This study conducted an association rules analysis to develop a sales strategy. Sales transaction data used is data for December 2020 with a minimum value of support of 25 and a minimum value of confidence of 80 by processing data using Rapidminer application. FP Growth algorithm can produce association rules as a reference in product promotion and decision support in providing product recommendations to consumers based on predetermined minimum support and confidence values. The association rule result with the highest lift ratio is 10.51.

by Ni Putu Priyastini Dessy Safitri "Association Rules Analysis using FP-Growth Algorithm to Make Product Recommendations for Customer" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd38459.pdf 

Paper Url: https://www.ijtsrd.com/computer-science/data-miining/38459/association-rules-analysis-using-fpgrowth-algorithm-to-make-product-recommendations-for-customer/ni-putu-priyastini-dessy-safitri

callforpaperarts, artsjournal, peerreviewedjournal 

Disasters have a huge impact on a country and a region. Bali is one of the provinces in Indonesia which has some disaster, one of the disasters that occurred in Bali was drought. Forecasting of droughtinn Bali is necessary so that the government can prevent and manage this kind disastersand can make wise decisions based on information regarding the number of drought. This study aims to predict the number of drought in the next five years. The method used is the Multilayer Perceptron because it is able to predict time series events. The data used are drought disaster events from 2011 to 2019. The results of the analysis in this study indicate that the best Learning Rate and Hidden Layer for forecasting the number of disaster events are Learning Rate 0.7 and Hidden Layer 3.2 respectively with MAPE accuracy is 19.91 . Forecasting results in the coming years show that there is an increase and decrease in the number of drought in 2020 to 2024. 

by Ni Putu Ratih Andini Putri "Forecasting the Drought in Bali using the Multilayer Perceptron Method" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd38460.pdf 

Paper Url: https://www.ijtsrd.com/computer-science/data-miining/38460/forecasting-the-drought-in-bali-using-the-multilayer-perceptron-method/ni-putu-ratih-andini-putri

callforpapermedicalscience, medicalsciencejournal

Internet usage is increasing today. As a result, internet use changes their lifestyle. Many activities such as shopping, meeting, social environment take place on the internet. Thus, a large amount of data is generated. As the amount of data increased, studies were carried out to store this data. Storage is generally used to analyze data. Data analysis studies are used to realize the advertisements and investments of organizations in the right area and in the right way. Therefore, big data analysis has a place in many areas. The data analyze people personally, except to give information specific to only one area. As a result, the desired effect is created on the analyzed people. Therefore, one of the most used fields is the political field. The most used platform for those who want to express their opinions in the political field is Twitter. Therefore, my aim is to obtain big data via Twitter, to store this data, and to analyze the political approach of the person on the stored data. 

by Hamza Pekdogan | Dr. Atilla Ergüzen "Twitter Big Data Analysis" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, 

URL: https://www.ijtsrd.com/papers/ijtsrd38266.pdf

Paper Url: https://www.ijtsrd.com/computer-science/data-miining/38266/twitter-big-data-analysis/hamza-pekdogan

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Unemployment has an impact on economic development in Indonesia. Bali is one of the provinces in Indonesia which has had a high unemployment rate in the last 13 years. Forecasting the number of unemployed in Bali Province is needed so that government policies can more optimally handle unemployment. This study aims to forecast the number of unemployed in the next five years. The method used is the Support Vector Machine because it is capable of forecasting a certain time series or time series. The data used are unemployment data from 2007 to 2019. The results of the analysis in this study show that the best SVM kernel type for forecasting the number of unemployed is radial. This type of kernel is used because it shows the smallest error value, namely MSE 0.007022, MAE 0.071292, and MAPE 23.24 . Forecasting results in the coming year an increase in the number of unemployed people from 2020 to 2024.

by Imelda Alvionita Tarigan "Forecasting the Number of Unemployment in Bali Province using the Support Vector Machine Method" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, 

URL: https://www.ijtsrd.com/papers/ijtsrd38242.pdf

Paper URL : https://www.ijtsrd.com/computer-science/data-miining/38242/forecasting-the-number-of-unemployment-in-bali-province-using-the-support-vector-machine-method/imelda-alvionita-tarigan

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Kidney is a significant aspect of a human body. Kidney infection or disappointments are expanded in every year. Presently a day’s chronic kidney infection is the most well known disease for the individuals. Today numerous individuals pass on due to chronic kidney disease. The principle issue of CKD is, it will influence the kidney gradually. A few people dont have side effects at all and are analysed by a lab test. It depicts the steady loss of kidney work. Early recognition and therapy are viewed as basic variables in the management and control of chronic kidney disease. Data mining techniques is utilized to extract data from clinical and laboratory, which can be useful to help doctors to recognize the seriousness stage of patients. Using Probabilistic Neural Networks PNN algorithm will get better prediction for determining the severity stage of chronic kidney disease. 

by Seethal V | Kuldeep Baban Vayadande "Predicting Chronic Kidney Disease using Data Mining Techniques" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, 

URL: https://www.ijtsrd.com/papers/ijtsrd37974.pdf

Paper URL : https://www.ijtsrd.com/computer-science/data-miining/37974/predicting-chronic-kidney-disease-using-data-mining-techniques/seethal-v

callforpaperlifesciences, lifesciencesjournal, researchpapers