Perkembangan Teknologi Informasi saat ini begitu pesat, semua kebutuhan sehari-hari dapat dilakukan hanya dengan perangkat pintar dan koneksi internet saja. Semua hal dapat dilakukan, seperti mencari informasi, bersosial media, belajar secara daring sampai dengan kebutuhan ekonomi yang didalamnya terjadi transaksi elektronik banking seperti berbelanja, berdagang dan transaksi bisnis lainnya. Banyak hal positif yang didapat, akan tetapi banyak juga hal-hal negatif yang harus kita fahami dapat terjadi ketika kita berselancar di internet, seperti pencurian data, peretasan akun, penipuan, pembobolan rekening, bahaya pornografi terutama bagi anak-anak dan banyak lagi kasus-kasus kejahatan yang sudah terjadi. Atas dasar pemikiran diatas maka sangat penting untuk selalu dilakukan edukasi kepada masyarakat bagaimana penggunaan teknologi tersebut secara benar dan rambu-rambu apa yang harus difahami dan diikuti. Kegiatan Pengabdian Masyarakat ini adalah salah satu cara untuk mensosialisasikan dan sekaligus mempraktekkan cara-cara penggunaan transaksi secara daring dengan benar. Desa Sambirejo Timur adalah Desa yang dipilih untuk edukasi, sosialisasi dan praktek penggunaan. Desa ini memiliki penduduk yang sangat padat, terletak disebelah timur dari kota medan berbatasan dengan Desa Tembung. Kegiatan ini diharapkan dapat mengedukasi Masyarakat Desa dan bagi peserta dapat Kembali menyebarkan informasi yang didapatkan

Some large companies have difficulty in providing products even though the products are still available in the warehouse. Based on these problems, a solution is needed in managing cosmetic products and can find the right strategy so that it can increase business in the field of sales and improve sales services by using algorithms in data mining that can overcome these problems, such as clustering techniques that use the K-means clustering algorithm as a way to measure proximity data between cosmetic products based on transactions that have occurred. The specialty of the analysis of the management of cosmetic products in this study is that it produces data on products that are not sold enough so that it can provide prevention so that the accumulation of these products does not occur. The use of K-means clustering also makes it easier to collect cosmetic sales transaction data, can solve problems in classifying cosmetic product sales transaction data and find out which products should be in cosmetics stock so as to increase sales profits.

The term ‘digital literacy’ encompasses many skills, which include the ability to evaluate information received through digital technologies, such as internet platforms, social media and mobile devices. Due to the fast spreading of hoax news through digital platforms in this post-truth era, it is urgently needed for this particular skill to be taught in educational settings, and English as a foreign language (EFL) classes are no exception. This study focused on exploring adult EFL students’ experiences in using two fact-checking applications (web-based apps) to help identify fake news in reading comprehension classes, and examining their efficacies from the students’ points of view. Employing a descriptive statistics approach, the researchers collected the data using an online survey administered to 130 students of a Science and Technology study programme at a university in Medan, Indonesia. The results indicated that in general students had positive attitudes toward the use of two fact-checking web-based apps. Specifically, they reported that the apps were very helpful in raising their awareness of digital literacy and fact-checking prior to reading and sharing digitally spread news. A closer look at the data reveals students’ preferences toward one of the two web-based apps. This study recommends the integration of anti-hoax education not only in EFL classes, but also in any other classes to prevent the threats of fake news, particularly to young generations. Keywords: Digital literacy, fact-checking apps, fake news, hoax, post-truth era

Abstrak—Pusat Penelitian Kelapa Sawit (PPKS) merupakan sebuah lembaga penelitian perkebunan pertama di Sumatera yang berfokus utama penelitian adalah pada kelapa sawit yang menghasilkan bibit unggul, untuk mendapatkan bibit unggul yang baik maka diperlukan  sebuah sistem yang dapat menentukan kualitas bibit kelapa sawit yang baik maka diperlukan beberapa cara, salah satunya adalah dengan menerapkan logika fuzzy, logika fuzzy memiliki matematis serta memiliki  toleransi  terhadap data-data  yang  tidak  tepat,  mampu  memodelkan  fungsi-fungsi nonlinear yang sangat kompleks dan dapat bekerja sama dengan teknik-teknik kendali secara  konvensional, pada logika fuzzy maka di terapkan algoritma fuzzy sugeno.  Fuzzy sugeno memiliki kelebihan yaitu lebih intuitif, diterima oleh banyak  pihak,  lebih  cocok  untuk  masukan  yang  diterima  dari manusia  bukan  mesin.  Sehingga algoritma fuzzy sugeno effektif diterapkan dalam menentukan kualitas bibit sawit untuk membantu pihak perusahaan, dalam fuzzy sugeno terdapat beberapa variabel yang bisa digunakan dalam melakukan perhitungan untuk mendapatkan menentuan kualitas bibit kelapa sawit yaitu pada pertubuhan, perkembangan, dan kesuburan. Pada hasil pengujian oleh sistem yang di bangun berdasarkan basis aturan dan perhitungan dari algoritma fuzzy sugeno maka dapat hasil yang di dapat dengan predikat Baik dengan nilai 90.Kata Kunci: Sistem Pendukung Keputusan, Logika Fuzzy Algoritma Sugeno, Bibit Kelapa Sawit  Abstract— The Palm Oil Research Center (PPKS) is the first plantation research institute in Sumatra whose main focus is on oil palm that produces superior seedlings, to get good seedlings, a system that can determine the quality of good oil palm seedlings is needed. ways, one of which is to apply fuzzy logic, fuzzy logic has mathematical as well as having tolerance to inaccurate data, is able to model nonlinear functions that are very complex and can work together with conventional control techniques, in fuzzy logic then applied the Sugeno fuzzy algorithm. Fuzzy Sugeno has the advantage of being more intuitive, accepted by many parties, more suitable for input received from humans not machines. So that the effective Fuzzy Sugeno algorithm is applied in determining the quality of oil palm seedlings to help the company, in Fuzzy Sugeno there are several variables that can be used in making calculations to get a determination of the quality of oil palm seedlings namely on growth, development, and fertility. On the test results by the system that was built based on the basis of rules and calculations from the Sugeno fuzzy algorithm, the results obtained with the predicate Good with a value of 90.Keywords - Decision Support System, Sugeno Fuzzy Logic Algorithm, Oil Palm Seedlings

<p><em>Sales transaction data is a very valuable asset in business processes. Not only is it used to calculate profits and money, but large amounts of transaction data can also be used for various purposes to generate new knowledge (knowledge) in the transaction database. Ways that can be done for data processing and generate new knowledge from the data is to use data mining techniques. The technique used in this case is the FP-Growth Algorithm. The data structure used is a tree called FP-Tree. By using FP-Tree, FP-growth Algorithm can directly extract Itemset from FP-Tree. Research conducted by collecting data related to research in the case studio at Medan Haji Hospital Pharmacy where the variables taken are daily drug transaction data. The results of this study are part of the new knowledge of this sales data by applying the FP-Growth Algorithm that uses the concept of FP-Tree development in finding Frequent Itemset that is useful for the development of investment plans in the study areas taken.</em></p><p><em> </em></p><p><em>Keywords: Data Mining, Association Rules, Frequent Itemset, FP-Growth.</em></p>