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Penerapan Data Mining Untuk Prediksi Perkiraan Hujan dengan Menggunakan Algoritma K-Nearest Neighbor Nursobah Nursobah; Siti Lailiyah; Bartolomius Harpad; Muhammad Fahmi
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): Desember 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2564

Abstract

Rain is a condition where water droplets fall from clouds to the earth. In life, the presence of rain is highly anticipated, rain can help people who have a profession as farmers. Rain that occurs on a large scale will really provide obstacles for the community, in addition to hampering activities or activities especially those carried out on outdoor rain can also cause disaster for the community in the form of flooding. Estimating rain for the community is very important, knowing whether it will rain or not can make it easier for the community to anticipate the possibilities that may occur due to rain. However, in the process of delivering forecasts, there is often an uneven distribution of information and delays in conveying information to the public regarding whether or not rain will occur. The community should be able to independently predict whether or not rain will occur. Data processing should be done properly and correctly. Data mining is a way that can be done to assist in data processing. In this study, the settlement process will be carried out using the K-Nearest Neighbor (K-NN) algorithm. The results obtained show that the data testing decision is NO. In other words, data mining and the K-Nearest Neighbor algorithm can help the problem solving process
Penerapan Metode Weighted Aggregated Sum Product Assessment (WASPAS) dengan Rank Order Centroid (ROC) Dalam Rekomendasi Barbershop Terbaik Wahyuni Wahyuni; Siti Lailiyah; Reza Andrea
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6769

Abstract

Barbershop is an innovation or development of a service previously known as a barber or barbershop. Barbershop operations are led by a barber or hairstylist, also known as a hairstylist, who has special skills in shaving and creating a variety of men's hairstyles. The barbershop business is experiencing rapid growth in this era. While there may be different variations of the name or brand, this business promises very attractive prospects in the long term. With so many barbershop options available, finding the best one can be a daunting task. In choosing a barbershop, there are several criteria to consider, such as the skill of the hairstylist, price, services offered, facilities provided, and level of cleanliness. To organize data and provide recommendations regarding the best barbershop, it is necessary to use an effective information system. The term "Decision Support System" (DSS) is often used to describe these information systems. The main objective of the DSS system is to improve the decision-making process and make it more effective and efficient by providing information, analysis and data modeling. The data needed to provide the best barbershop recommendations in Samarinda City were collected using the WASPAS (Weighted Aggregated Sum Product Assessment) and ROC (Rank Order Centroid) methods in this study. The replacement for the BS4, Sir Salon Barbershop, has the highest rating of 0.9815, making it a top barbershop recommendation.