Peningkatan Akurasi K-Nearest Neighbor Pada Data Index Standar Pencemaran Udara Kota Pekanbaru

Yuliska, Yuliska; Syaliman, Khairul Umam

doi:10.25299/itjrd.2020.vol5(1).4680

Cited by 11 publications

(10 citation statements)

References 26 publications

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“…Application of Euclidean distance algorithm [9] for selecting internet packages by region, [10] for ranking bus transport, [11] for ranking Indonesian-speaking participants' degrees, [12] for obtaining information regarding the image of TNI Berets, [13] for Air Pollution Standards Index Data, [14] for Classification of Instagram Bullying Comments and [15] While research uses the Euclidean distance method, among others, [16] to map a web-based pension. In addition, [17] which uses the Euclidean distance method for facial recognition, and [18] which applies the Euclidean distance method for clothing size recommendations in the application of a virtual locker room.…”

Section: Methodsmentioning

confidence: 99%

Schedule Implementing the Modified Euclidean Distance Method in the Course Planning of the USN Kolaka Information Systems Curriculum

Iyes

Mangkona

2022

ITJRD

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Scheduling is needed to anticipate the clash of lecture hours for lecturers in teaching. Some things that need to be considered when arranging a lecture schedule are lecturers, rooms, courses, hours, and days. In this study, the scheduling system uses the Euclidean Distance method by modifying the algorithm. The aim of this study is to prove the Euclidean distance method in the course planning system in universities. In general, to obtain data that will be used in the scheduling system, observations, interviews and bibliographic studies are carried out. From the research results, the lecture scheduling system using the Euclidean Distance method can be used in the scheduling system, especially lecture scheduling. This is proven, that the lecture scheduling system using the Euclidean Distance method does not have a schedule for lecturers who teach more than one course at the same time (collide).

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Section: Methodsmentioning

confidence: 99%

Schedule Implementing the Modified Euclidean Distance Method in the Course Planning of the USN Kolaka Information Systems Curriculum

Iyes

Mangkona

2022

ITJRD

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“…The FP-Tree development stage uses the FP-Growth algorithm to look for frequent and significant itemsets using a set of transaction data. The FP-Growth algorithm is divided into three main steps, namely [14]- [16]:…”

Section: Fp-treementioning

confidence: 99%

Analysis of Information Technology (IT) Goods Sales Patterns Using the FP-Growth Algorithm

Wandri

Hanafiah

2022

ITJRD

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Determination of sales patterns is very important in marketing. Sales pattern serves to conduct an effective analysis in improving marketing. Sales analysis aims to explore new knowledge that can help design effective strategies by utilizing sales transaction data. This study processes sales data for 12 transaction days containing 47 items using the Fp-Growth algorithm. The results of this study are items with a minimum value of support > 0.10 and confidence 0.60 and will be compared with testing data using RapidMiner to test whether the results are valid so that the test results can help in designing sales strategies.

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“…Penelitian lain, mengenai klasifikasi jenis kupu-kupu dengan algoritma KNN, yang menghasilkan tingkat akurasi tertinggi yaitu 91,1% [14]. Akan Tetapi dari penelitian sebelumnya menunjukkan bahwa KNN mengalami kesulitan untuk melakukan klasifikasi objek yang sejenis [15]. Sehingga perlu dilakukan perbaikan dan penambahan metode berdasarkan fitur yang terbentuk dari objek dan dapat mereduksi serta mempertahankan informasi yang sesuai dari karakteristik aslinya agar menghasilkan kinerja yang optimal.…”

Section: Pendahuluanunclassified

Klasifikasi Citra Jenis Kapasitor Menggunakan Kombinasi Algoritma K-Nearest Neighbor dan Principal Component Analysis

Nuraini

2022

JoSYC

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To learn about electronic devices, one must know about the types of electronic components. Capacitors are one of several important electronic components. Capacitors are part of passive components that are able to store energy or electric charge at a temporary time. Capacitors or commonly called capacitors have many types. However, some people do not know about these types of capacitors. Especially for someone or a student who will learn about electronic components. The purpose of this study is to develop a digital image processing system for the classification of transistor types by applying the K-Nearest Neighbor (KNN) and Principal Component Analysis (PCA) methods. PCA serves to reduce and retain most of the relevant information from the original features according to the optimal criteria. Based on the results of feature extraction and data reduction performed by PCA, it is easier for the KNN algorithm to classify. KNN performs a classification based on the data closest to the object being processed. Based on the test results, the developed model is able to produce an average accuracy value of 82.50%. This means that PCA and KNN algorithms can be used in the process of classifying capacitor type images properly

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Peningkatan Akurasi K-Nearest Neighbor Pada Data Index Standar Pencemaran Udara Kota Pekanbaru

Cited by 11 publications

References 26 publications

Schedule Implementing the Modified Euclidean Distance Method in the Course Planning of the USN Kolaka Information Systems Curriculum

Schedule Implementing the Modified Euclidean Distance Method in the Course Planning of the USN Kolaka Information Systems Curriculum

Analysis of Information Technology (IT) Goods Sales Patterns Using the FP-Growth Algorithm

Klasifikasi Citra Jenis Kapasitor Menggunakan Kombinasi Algoritma K-Nearest Neighbor dan Principal Component Analysis

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