Market basket analysis may be a technique identify the association between couple’s products purchased jointly and identify cases. Scene an occurrence is when two or more things happening. Market basket analysis makes rules if-then, scenario for instance, if an item purchased a and b will likely. bought items rule is probability in nature or, in other words, they are available from the incident. In observation the frequency is that the proportion of a basket of things which will be employed interesting. Rule, price, product placement and various varieties of cross-selling strategy. In order to create it easier to grasp, think in terms of market research handbasket in a very supermarket. Market basket analysis taking data on the transactions containing an inventory of all items that bought by customers in a very purchase. The technique is ascertaining the relations which product bought on other products. This relationship then wont to construct the containing the if-then items purchased. Market basket analysis also called a rule association or analysis affinity, learning may be a technique data processing can be used in numerous fields, as education, marketing, informatics and science. The aim is to include retailer’s awareness of buyers’ actions in order for the retailers with knowledge about the actions of purchasers, which will allow the tailor to make the right choices. All of the numerous market basket algorithms available to try to do. Algorithms, whose current work is on statics and which did not catch data changes in time, but algorithms not only intended to mine static information, but also provided new ways of calculating modifications on paper-listed association processing rules, and provide new algorithms that could stimulate market engagement and encourage up-selling.
Media penyimpanan menjadi hal yang sangat penting dalam proses mengamankan data, permasalahan yang sering dihadapi adalah kurang terpusatnya penyimpanan data atau server sehingga menyebabkan tingginya resiko kehilangan data. Selain itu media penyimpanan yang tidak terpusat juga bisa memakan waktu yang cukup lama ketika proses backup data dilakukan. Oleh karena itu, pada penelitian ini peneliti mengkaji penggunaan Network Attached Storage (NAS) dengan menggunakan Open Media Vault (OMV) pada perangkat Raspberry Pi terhadap kehandalannya, seperti cukup baik atau handalkah Raspberry Pi untuk dijadikan sebuah NAS server. Penggunaan Open Media Vault (OMV) dengan Raspberry Pi juga selain dapat menjadi solusi permasalahan backup data juga memiliki tingkat efisiensi yang tinggi dari segi biaya dan perawatan. Metode yang digunakan pada penelitian ini adalah metode kuantitatif. Setelah melakukan penelitian di PT. Digital Sarana Transportasi dapat disimpulkan bahwa peneliti berhasil membangun sistem server penyimpanan jaringan Network Attached Storage (NAS) menggunakan Open Media Vault (OMV) pada perangkat Raspberry Pi dengan metode client-server. Penelitian telah diuji menggunakan metode analisis data dengan melakukan serangkaian teknik pengumpulan data seperti melakukan observasi, wawancara dan menyebarkan angket/kuesioner pada 35 responden.
The use of the internet network at Wahidin Vocational High School (SMK) Cirebon City is a very significant need in supporting the progress of learning. The ease of using the internet has made the academic community free to use the internet network facilities provided by the school and carry out the activities they want without any control. Causing the academic community to freely access the web that is not related to ongoing education, and certainly this matter will be very disturbing in the teaching and learning process. This matter is in order to identify accurate analysis also using Information Mining as information processing. After that, using the clustering algorithm procedure is K-Medoid. The K-Medoid procedure is able to carry out information grouping on the use of social media access which is often accessed by the academic community throughout the school. Grouping using the K-medoids algorithm can be known that the use of internet network access is on average used to access social media compared to accessing E-learning. It is suitable from the results of research that was tried if the use of WhatsApp reached an average of 126 users, after that accompanied by Instagram, its usage reached an average of 108 users, then accompanied by E-Learning, the average usage reached 90 users, after that it was accompanied by Facebook and YouTube which an average of 71 users. Thus, from the research that has been tried, it is necessary to implement layer 7 protocol firewall security to block social media access so that internet network access at Wahidin Vocational High School (SMK), Cirebon City. Used as a suitable early idea is to facilitate the academic community to maximize E-learning education.
Critical thinking in mathematics can be defined as the processes and abilities used to understand concepts, apply, synthesize and evaluate the information generated. Critical thinking in mathematics is a skill for higher order thinking. It is understood that logical thought plays a part in spiritual growth, social progress, behavioral growth, cognitive development and science progress. This study aims to classify critical thinking skills. The method used to determine the classification of critical thinking skills is to use the Neural Network algorithm. A method which has the potential to classify structured data is the neural network. In this study, a neural network algorithm model was developed. A technology that has the potential to identify structured data is the neural network. In this study, a neural network algorithm model was created. With this neural network model, it can be seen the classification of critical thinking skills. The amount of data used as data in this analysis was 150 in the form of school data and as many as 40 measures were measured in the form of math scores. On the basis of the research results, it was found that the neural network model based on Particle Swarm Optimization achieved an accuracy value of up to 93.33 percent with a 2 percent variance, tested using the k-cross-validation method.
Divorce in domestic life is usually faced by married couples. During the life of a household, no one expects disputes that can end in divorce. A number of regions in Indonesia based on the Annual Reports of the Religious Courts from 2016, 2017, 2018, 2019 and 2020, it is known that there is a problem, namely an increase in the divorce rate in terms of the number of cases received by the Religious Courts. The problem of divorce cases is even increasing every year. To find out the Grouping of Divorce Cases Using the K-Means Algorithm in Indonesian Cities/Regencies. To perform this grouping using the k-means algorithm. . The dataset used consists of 410 with attributes of the causes that lead to divorce cases. Then preprocessing is carried out on the dataset to eliminate missing data. Then, the clustering technique was carried out using the k-means algorithm to be grouped. To get the best group, DBI calculation is used. The results of the research are expected to obtain grouping performance with the k-means algorithm. The results obtained show several groups with a DBI value of 0.19 with a number of clusters 2.
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