This study aims to develop a tool that can be used to detect obstacles for blind people. This tool also uses the HC-SR04 ultrasonic sensor. The method used in the manufacture of blind assistive prototypes in the form of sticks using Arduino and Ultrasonic Sensors for blind people with the method obtained by hardware design techniques used consists of ATMEGA328 as the main controller, Ultrasonic sensor HS-SRF04 as detecting objects and LM2596 Regulator modules used for lowering the DC voltage level, this study has produced a prototype design stick for blind people using sensor technology to help alert and move blind people who are able to detect objects at a minimum distance of 7 centimeters with output in the form of sound and vibration. The resulting stick has a frame consisting of 0.5-inch PVC material consisting of two parts, the stick rod and the sensor unit.

Nowadays, computer networks are widely used to exchange valuable and confidential data information between servers to computers or cellular devices. Access to user control and use of software or hardware as a firewall often experience security problems. Unauthorized access to information through computer networks continues to occur and tends to increase. This study examines the attack detection mechanism by using three data mining algorithms based on particle swarm optimization (PSO), namely PSO-K Nearest Neighbor, PSO-Random Forest, and PSO-Decision Tree in the Canadian Institute for Cybersecurity Dataset (CICIDS2017). The initial experiment showed that the approach using the PSO-RF method was able to produce the highest accuracy of attack detection. Accuracy values generated using the PSO-RF algorithm with a combination of the number of trees and maximal depth = 20 in the CICIDS2017 dataset are intact higher than other proposed algorithms. The highest accuracy of attack detection in the CICIDS2017 dataset is intact, which is 99.76%. In the CICIDS2017 dataset 50% Benign and 50% Attack it turns out that the PSO-RF algorithm with a combination of the number of trees and maximal depth = 20 also gets the highest accuracy value of 99.67%.

Precision marketing is the companys ability to offer products specifically made to customers. This decision can give the company the ability to attract customers to always buy continuously. This study presents a trend model for accurately predicting monthly supply quantities / The method used in the first stage is the RFM (Recency, Frequency, Monetary) method for selecting attributes to group customers into different groups. The output of the first stage is clustered using the K-Means Algorithm. The output of clustering is then classified using the Decision Tree and compared with the K Nearest Neighbor method. The dataset that is processed is sales data from Syifamart As-Syifa Boarding School in Subang with 351,158 rows of data. The clustering process produces 4 optimal clusters. The four clusters are then classified using the Decision Tree algorithm to determine the potential and non-potential characteristics of each customer.

Donasi adalah suatu kegiatan dimana seseorang ataupun sekelompok orangmenyumbangkan sesuatu kepadaindividu atau kelompok dalam bentuk uang atau barang. Di zaman sekarang ini, hampir semuanya dapatdiakses secara daring, salah satunya adalah kegiatan berdonasi. Seiring dengan tingginya kesadaranmasyarakat dalam berdonasi dan besarnya dana yang dikelola, banyak pula permasalahan yang ada dalamsistem donasi, seperti penggelapan dana maupun ketidakterbukaan dalam hal pendistribusian. Untukmengatasi hal tersebut, maka dibutuhkan suatu sistem yang dapat memberikan informasi transaksi secaratransparan. Tujuan dari penelitian ini adalah membuat sebuah aplikasi donasi berbasis teknologi blockchainkarena dengan menggunakan sistem berbasis blockchain, maka proses donasi dapat dilakukan dengan lebihtransparan. Dengan menggunakan smart contract yang berjalan pada jaringan blockchain, transaksi yangdilakukan pada aplikasi donasi ini tersimpan di dalam basis data publik sehingga lebih terbuka dan tidak dapatdiubah oleh siapapun.