AL QURAN JPG PDF INDONESIA SKIN
Skin cancer recognition by applying modified SECoS algorithm is proven more acceptable. The skin cancer classification has learning rate 1 of 0.3, learning rate 2 of 0.3, sensitivity threshold of 0.5, error threshold of 0.1 and MAPE is 0.5184845 with developing hidden node of 23. This paper recognizes skin cancer by classifying benign malignant skin moles images using SECoS based on parameter combinations. SECoS distance has been modified with the normalized Euclidean distance formula to reduce error in training. SECoS uses a feedforward neural network but its hidden layer evolves so that each input layer does not perform epoch. Data recognition is achieved by aligning testing data to trained data pattern.
Span id="docs-internal-guid-eea5616b-7fff-5d26-eeb4-1d8c084ec93d"> Simple evolving connectionist system (SECoS) is one of data mining classification techniques that recognizing data based on the tested and the training data binding. Meanwhile, BI model is designed to obtain a formula from the cooperative principle, namely the residual income from operations where the transaction process is successfully implemented through the application to allocate a portion of the profits to the members based on the specified percent. Actually, cooperatives have been long abandoned since the existence of conventional and Islamic banking concept but it has kinship principle to divide the profits based on the size of the contribution given.
In this paper, a model is designed to combine three type of principles, namely the business forum, BI and the cooperative principle. Along with the development of information technology towards business intelligence(BI), the business processes carried out in the business forum are modeled specifically in order to create an effort and attempt to follow the indicator and criteria from the industrial revolution 4.0. The results obtained were processed with a MAPE calculation process of 50% for inactive users and 0.1980198% for active users.īusiness forums are activities between individuals and organizations that carry out the transactions on online media or within applications, which spread across countries. The division of word forecasting was classified into two groups i.e.
AL QURAN JPG PDF INDONESIA SERIES
After getting the word weight value of the tweets, a time series forecast was performed with the test data of 1734 tweets that the results referred to 1203 categories of Slack words and 531 verb tweets as training data resulting in good accuracy. In this study had conducted the word forecasting on twitter with 1734 tweets which were interpreted as weighted documents using the TF-IDF algorithm with a frequency that often comes out in tweets so the TF-IDF value is getting smaller and vice versa. Time series is a method that is generally used to forecast based on time and can forecast words in social media.
In this case, the things that were supervised were the label or target data playing a role as a 'supervisor' who supervise the training process in achieving a certain level of accuracy or precision. Thus, many algorithms for solving forecasting problems are categorized as supervised learning with the aim of conducting training. Forecasting is one of the main topics in data mining or machine learning in which forecasting, a group of data used, has a label class or target.
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