No abstract

Technological developments make social media widely used by the general public, which causes negative impacts, one of which is cyberbullying. Cyberbullying is an act of insulting, humiliating another person on social media. A system that can detect cyberbullying because of the large amount of information circulating on social media is impossible for humans to visit. One suitable method to solve this problem is Extereme Gradient Boosting (XGBoost). XGBoost was chosen because it can run 10 times faster than other Gradient Boosting methods. The process of changing sentences into vectors uses the TF-IDF method. The TF/IDF method is known as a simple but relevant algorithm in doing words on a document. XGBoost accepts input in the form of vectors obtained from the TF-IDF process. In this research, there are 1452 comments which will be broken down into training data and testing data. By using XGBoost and TF-IDF methods, the accuracy is 75.20%, precision is 71%, recall is 87%, and F1-score is 78%.

Sistem pencarian menjadi salah satu fitur yang sangat diperlukan pada sebuah aplikasi atau website. Dengan membandingkan 2 algoritma yang sering digunakan yaitu Binary Search dan algoritma Regular Search Expression dalam suatu sistem pencarian sederhana adalah permasalahan yang akan dibahas dalam jurnal ini. Analisa kedua algoritma dilakukan untuk menyelesaikan permasalahan dalam sistem pencarian, sehingga algoritma pencarian dapat diterapkan lebih tepat dan efektif lagi. Hasil penelitian membuktikan bahwa Binary search memiliki kelebihan dalam melakukan pencarian pada data berjumlah besar dengan keadaan terurut serta memiliki iterasi yang lebih efektif. Sedangkan Regular Expression Search memiliki kelebihan dalam melakukan pencarian yang tidak diketahui secara lengkap mengenai hasil dan kunci, selain itu algoritma ini juga memungkinkan untuk melakukan pencarian berdasarkan pola tertentu pada data.

Technological advances at this time are very influential on people's shopping culture, plus during the current pandemic, it has resulted in an increasing number of people shopping for daily necessities online. There are many conveniences offered in online shopping that make people switch to using these facilities. Besides the advantages of online shopping, there are also some disadvantages of online shopping, including the rise of online sales fraud such as goods not being shipped, damaged goods, items not as ordered, and much more. For this reason, in conducting online transactions, trust is needed between the seller and the buyer, and one of the factors that greatly affect the prospective buyer is to know the history of the seller, namely by looking at the reviews given by the buyer on the seller's homepage which is called Online Customers Reviews (OCR). OCR is considered to be very influential on customer buying interest. One of the indicators that are considered very important in influencing consumer buying interest and trust is OCR. This study aims to analyze OCR clustering in one of the marketplaces in Indonesia using the K-Means Clustering Method. K-Means is a clustering algorithm that is quite effective because it has the ability to group large amounts of data and with high speed, the K-Means algorithm partitions data into clusters so that they have the similarity of being in one cluster.

Keberadaan pemasok sangat menentukan kelancaran proses produksi dan produk yang akan dihasilkan. Masalah yang dihadapi perusahaan adalah proses evaluasi atau pemilihan pemasok terbaik masih bersifat manual, sulitnya menentukan pemasok mana yang memiliki performansi terbaik, keterlambatan datangnya bahan baku mengakibatkan keterlambatan proses produksi yang berujung pada tidak tercapainya jumlah produksi. Pada penelitian ini dibangun Sistem Pendukung Keputusan (SPK) untuk pemilihan pemasok terbaik menggunakan 4 kriteria yang disesuaikan dengan kondisi dan kebutuhan perusahaan yaitu harga, stok, delivery, dan mutu. Masing-masing kriteria tersebut akan dibobotkan menggunakan metode Fuzzy AHP. Pada implementasinya dihasilkan bobot kriteria harga sebesar 0,632, stok 0,352, delivery 0,084, mutu 0,107. Hasil pembobotan ini akan digunakan untuk mendukung penilaian pemasok terbaik dan akan diperoleh nilai masing-masing pemasok sehingga diketahui siapa pemasok terbaik