The Formula E racing series has become one of the world's most prestigious competitions. In 2022, Indonesia hosted the famous Formula E race. The event possesses the potential for economic benefits for Indonesia worth 78 million euros through the arrival of 35,000 spectators. Indonesians are enthusiastic about Formula E since it allows their nation to encourage tourists and gain international prominence. However, some people do not support this event. Since they regard that amid the COVID-19 pandemic, it is preferable for the government to focus on people affected by the pandemic rather than support a Formula E event. This study compares the Support Vector Machine and Naive Bayes algorithms in classifying public opinion in the Formula E race. This study gets its information from user comments on social media platforms, especially Twitter. The stages start with text preprocessing and include cleaning, case folding, tokenization, filtering, and stemming. Proceed with weighting using the TF-IDF approach. Data testing uses a confusion matrix to evaluate the classification results by testing accuracy, precision, and recall. Categorizing public opinion using the SVM algorithm has an accuracy of 82 percent, a precision of 97.86 percent, and a recall of 77.90 percent. On the other hand, the accuracy of the Naive Bayes technique is more limited, at 87.54 percent. Society's opinion on Twitter shows positive sentiment towards implementing Formula E.
Pada masa pandemi covid 19 yang berdampak pada semua sektor di Indonesia salah satunya adalah sektor perdagangan, seperti halnya UMKM banyak yang mengalami penurunan produktivitas dan pendapatan. Pelaku UMKM harus menghadapi tantangan bisnis dengan beradaptasi dan berinovasi untuk mempertahankan dengan bertransformasi ke ranah digital. Pelaku usaha harus memiliki ketrampilan dalam memanfaatkan teknologi untuk membantu memperluas pasar dan meningkatkan penjualan. Kami mengusulkan kegiatan pelatihan bagi pelaku usaha UMKM Tajur Halang Makmur agar membantu memperluas pasar dan meningkatkan penjualan dengan digital marketing. Materi yang akan diberikan adalah konsep konten marketing, penggunaan aplikasi e-commerce dan digital marketing melalui sosial media. Kegiatan ini diharapkan akan memperluas pemasaran dengan konten yang menarik sehingga penjualan akan meningkat serta menambah ketrampilan pelaku usaha dalam menggunakan teknologi informasi. Luaran kegiatan ini berupa artikel yang akan dipublikasikan di jurnal nasional dan publikasi media massa dan media sosial.
Not a few Micro, Small and Medium Enterprises (MSMEs) still have difficulties in utilizing social media platforms to optimally promote their businesses. Not only that, they also lack the skills to create attractive marketing content, how to start from scratch, how to create attractive poster designs or content, find and promote the advantages of their products, to compete with competitors. Saw the difficulties faced by MSME partners of the Atsiri Women's Cooperative, the author initiated a training program on the use of social media platforms and designs as promotional media. In this training, the author teaches, including the introduction of social media platforms (Instagram, facebook, tiktok), introduction to the platform for making designs: Canva, how to create attractive marketing content, and how to create simple designs with Canva. The results of this training are expected to improve the ability to use social media and design as well as provide education/learning to raise their product branding to a higher level and be known through social media so that it will increase product sales.Abstrak Tidak sedikit para pelaku Usaha Mikro Kecil dan Menengah (UMKM) yang masih banyak kesulitan dalam memanfaatkan platform sosial media untuk mempromosikan usaha mereka dengan optimal. Tidak hanya itu mereka juga kurang memiliki skill untuk membuat konten marketing yang menarik, bagaimana memulainya dari awal, cara membuat desain atau konten poster yang menarik, menemukan dan mempromosikan keunggulan produk mereka, untuk bersaing dengan kompetitor. Melihat kesulitan yang dihadapi mitra UMKM Koperasi Wanita Atsiri, membuat penulis menginisiasi program pelatihan pemanfaatan platform sosial media dan desain sebagai media promosi. Pada pelatihan ini penulis mengajarkan disampaikan diantaranya pengenalan platform sosial media (Instagram, facebook, tiktok), pengenalan platform untuk membuat desain : canva, cara membuat konten marketing yang menarik, dan cara membuat desain yang simple dengan Canva. Hasil dari pelatihan ini diharapkan dapat meningkatan kemampuan penggunaan sosial media dan desain serta memberi edukasi/pembelajaran untuk menaikkan branding produk mereka menjadi lebih tinggi dan dikenal melalui media social sehingga akan meningkatkan penjualan produk.Keywords: desain, digital marketing, konten marketing, sosial media, umkm
The company produces sales data every day. Over time, the data increases, and the amount becomes very large. The data is only stored without understanding the benefits that exist from these data due to limitations in proper knowledge in analyzing the data, especially transaction data. Sale. To overcome these problems, a study focused on reprocessing sales transaction data in 2018 with a data mining technique approach using the Knowledge Discovery in Database (KDD) concept using the association method and apriori algorithm and a supporting application, namely RapidMiner. This study aims to help companies find customer buying habits or patterns based on 2018 sales transaction data. The results of this study produce 316 association rules where the best rules are generated on record 309 with PRO 889 & PRO 868 PRO 869 rules.
Politeknik Tri Mitra Karya Mandiri adalah salah satu perguruan tinggi vokasi yang berada di wilayah Cikampek Kabupaten Karawang yang pada tahun akademik 2017/2018 mempunyai jumlah mahasiswa mencapai 987 orang mahasiswa.Namun sayangnya dari total jumlah mahasiswa tidak seluruhnya mempunyai orientasi minat yang sesungguhnya untuk kuliah, banyak factor yang mempengaruhinya. Tinginya tingkat orientasi minat mahasiswa yang tidak memilih kuliah, inilah yang membuat diadakan penelitian tentang sebab-sebab mengapa mahasiswa berkuliah dikampus ini serta mecari solusi guna mengurangi jumlah mahasiswa yang menjadi non aktif ketika diketahui mempunyai orientasi minat yang bukan untuk kuliah. Dengan melakukan komparasi menggunakan 3 algoritma yang termasuk dalam metode klasifikasi data mining yaitu; Decision Tree C4.5, Naïve Bayes dan K-Nearest Neighbor penelitian ini mencari nilai akurasi dan Area Under Curve (AUC) yang terbaik dari ketiga algoritma yang dikomparasi guna ditentukan model yang digunakan pada penentuan orientasi minat mahasiswa. Hasil dari komparasi yang dilakukan dalam penelitian ini adalah; algoritma Decision Tree C4.5 mempunyai nilai akurasi sebesar 91,75% dan AUC sebesar 0,969, Naïve Bayes mempunyai nilai akurasi sebesar 86,77% dan AUC sebesar 0,930 sedangngkan K-Nearest Neighbor mempunyai nilai akurasi sebesar 88,61% dan AUC sebesar 0,500. Melalui uji beda yang dilakukan menggunakan operator T-test pada Rapid Miner ditemukan hasil bahwa algoritma Decision Tree C4.5 merupakan algoritma terbaik dari 3 buah algoritma yang digunakan, maka dalam penelitian ini digunakan rule Decision Tree C4.5 untuk diterapkan pada deployment yang dilakukan.
Customer complaints about the company can be used as a form of self-evaluation and performance that has been carried out by the company, based on customer complaints the company can find out the weaknesses that exist in the company and fix them. The forms of submitting customer complaints are very diverse, currently not only by telephone, but customers also submit suggestions or complaints, customers can submit suggestions or complaints via electronic mail or e-mail or forums in cyberspace that are indeed created by product-producing companies to accommodate various complaints, suggestions, and direct criticism from consumers, especially social media that are free to express opinions on the delivery services used. Instagram is a social media that is more inclined towards images and on the other hand, has captions and comments text, a study is needed for the problem of customer complaints from shipping service users on an Instagram account of a delivery service company. Based on this background, a solution is needed in solving problems for text mining classification using Naïve Bayes with SMOTE techniques and N-Gram feature extraction with the usual process for text mining so that it can produce Naïve Bayes and SMOTE accuracy with an accuracy of 88.54%, before implementation. N-Gram and the accuracy rate increased by 1.44% after the N-Gram Term was applied to 89.98% by using a dataset of 776 Instagram comment text records that had to preprocess text.
ABSTRACT The Gade Coffee & Gold produces a lot of sales transaction data every day that is stored in the database, but this data has not been maximized in conducting analysis to produce new knowledge, based on this problem it is necessary to carry out an analysis using a data mining approach and applying association techniques. Data mining is able to analyze data into information by applying association techniques to find several purchasing patterns that are useful to assist companies in the process of making business decisions such as determining product cross-selling, determining promotional programs, and so on. This study aims to determine the pattern of combinations of food and drinks ordered by customers by applying the Apriori method based on sales transaction data for the month of September 2022. The results show that there are 16 association rules with the highest support value which is 6.8% with a confidence value of 85 .7% and the Lift value is 111%, with the rule formed that if a customer buys an Almond Croisant product, there is a chance that the customer will also buy Van Lenning – Iced products. Keywords: Data Mining, KDD, Association, Apriori ABSTRAK The Gade Coffee & Gold setiap harinya menghasilkan banyak data transaksi penjualan yang tersimpan dalam basis data, namun data tersebut belum dimaksimalkan dalam melakukan analisa untuk dapat menghasilkan suatu pengetahuan baru, berdasarkan masalah tersebut perlu dilakukan sebuah analisa dengan menggunakan pendekatan data mining serta menerapkan teknik asosiasi. Data mining mampu menganalisa data menjadi sebuah informasi dengan menerapkan teknik asosiasi dapat menemukan beberapa pola pembelian yang berguna untuk membantu perusahaan dalam proses pengambilan keputusan bisnis seperti menentukan cross-selling produk, menentukan program promosi, dan sebagainya. Penelitian ini bertujuan untuk menentukan pola kombinasi dari makanan dan minuman yang dipesan oleh pelanggan dengan menerapkan metode Apriori berdasarkan data transaksi penjualan periode bulan September 2022. Hasil penelitian menunjukkan sebanyak 16 aturan asosiasi dengan nilai support tertinggi adalah 6,8% dengan nilai confidence sebesar 85,7% dan nilai Lift 111%, dengan aturan yang terbentuk yaitu apabila pelanggan membeli produk Almond Croisant peluang pelanggan juga membeli produk Van Lenning – Iced. Kata Kunci: Data Mining, KDD, Asosiasi, Apriori
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