Implementasi Algoritma K-Nearest Neighbor Dalam  Pengklasifikasian Follower Twitter Yang  Menggunakan Bahasa Indonesia

Rivki, Muhammad; Bachtiar, Adam Mukharil

doi:10.21609/jsi.v13i1.500

Cited by 25 publications

(22 citation statements)

References 3 publications

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“…-Menghitung kuadrat jarak Euclid (queri instance) masing-masing objek terhadap data sampel yang diberikan. (Bramer,2007), yaitu [5] : dengan nilai akurasi Excellent Classification.…”

Section: Pendahuluanunclassified

Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Efektivitas Penjualan Vape (Rokok Elektrik) pada “Lombok Vape On”

Yahya¹,

Hidayanti²

2020

JIT

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Perusahaan yang dibangun dengan tujuan untuk menghasilkan barang atau jasa yang ditujukan untuk memenuhi kebutuhan konsumen juga untuk memperoleh keuntungan bagi perusahaan tersebut. Perusahaan sudah tentu memiliki tujuan yang sama yaitu mencapai target yang sudah direncanakan dan mampu menghasilkan pemasukan yang selalu meningkat disetiap tahunnya. Dan salah satu kegiatan usaha yang harus dilakukan agar perusahaan tetap berjalan dan berkembang adalah penjualan. Keputusan yang diambil pemegang tanggung jawab perusahaan akan mempengaruhi perusahaan dimasa depan. Salah satu keputusan yang harus ditentukan yaitu produk yang akan diproduksi dan dijual untuk periode selanjutnya. Dilihat dari era globalisasi saat ini bahwa usaha yang dapat mengikuti zaman yaitu produk rokok elektrik (Vape). Produk tersebut benar-benar diminati oleh kalangan anak muda hususnya para pria. Salah satu instansi yang mengambil keputusan untuk menggeluti bisnis tersebut yaitu Lombok Vape On. "Lombok Vape On" memiliki konsumen yang cukup banyak sehingga pendapatan yang didapat tentu banyak, akan tetapi pendapatannya tidak menentu dan tidak dapat diprediksi dengan baik setiap bulannya. Tujuan dari penelitian ini untuk mengklasifikasikan hasil penjualan dari Lombok Vape on untuk mengetahui efektifitas penjualan perbulannya agar toko tersebut dapat mengetahui pasang surut pemasukan yang didapat. Apabila instansi tersebut mengetahui tingkat penjualannya maka instansi tersebut dengan mudah mengubah strategi penjualan agar stabil dan meningkat. Untuk itu peneliti menerapkan metode K-Nearest Neighbor untuk mengklasifikasin masalah tersebut,dan diharapkan metode ini mampu mengatasi masalah pada "Lombok Vape On".

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“…-Menghitung kuadrat jarak Euclid (queri instance) masing-masing objek terhadap data sampel yang diberikan. (Bramer,2007), yaitu [5] : dengan nilai akurasi Excellent Classification.…”

Section: Pendahuluanunclassified

Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Efektivitas Penjualan Vape (Rokok Elektrik) pada “Lombok Vape On”

Yahya¹,

Hidayanti²

2020

JIT

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“…The ADC facility contained in Mega 2560 will convert the information in the form of analog voltage signals from the two sensors into 10-bit numbers (0-1024) [6] and adjusted according to the unit of each sensor before processed further using the K-NN algorithm. K-Nearest neighbors K-Nearest Neighbors (K-NN) algorithm is an algorithm used to classify an object, based on k training data which is the closest distance to the object [2]. The condition for k values cannot be greater than the amount of training data, and k values must be odd [3].…”

Section: Hardware Designmentioning

confidence: 99%

Applied K-Nearest Neighbors (KKN) on Dust Suppression Prototype

Adhitya¹,

Nurhasan²,

Widodo³

et al. 2020

IJER

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Steam power plants that use coal as fuel have serious problems during operation. Before heading to the combustion process, coal is stored in an open field area. However, this results in fine particles of coal dust being exposed to wind and polluting the surrounding environment. The purpose of this study is to minimize the impact of pollution from coal dust by using the dust suppression tool. The tools that have been run manually or conventionally can be operated automatically to facilitate the operator in controlling dust suppression without the need to go to the field. This research proposes a prototype dust suppression equipped with dust and temperature sensors, the sensor data is a representation of the condition of the coal storage area which is processed using the K-Nearest Neighbors method to classify whether the condition of the storage area is normal or dusty. When conditions are dusty, the pump activates and directs bursts of water at the coal to minimize dust. In the application of the K-Nearest Neighbors method, center point 1 is obtained for normal conditions, with a dust density of 0.4353 mg / m3 and a temperature of 27.5818 °C. Whereas center point 2 for dusty conditions has a dust density of 2,374 mg / m3 and a temperature of 28.2667 °C. From 40 testing data in real-time, a success rate of 87.5% was obtained.

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“…Received 2018-07-110 Revised 2018-09-14 Accepted 2018- [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] Outbreak Diphtheria is now a special concern for the Indonesian government and is noted as an extraordinary case (KLB) in 2017. Diphtheria is an infectious disease and can cause complications of dangerous and deadly diseases if not addressed immediately, so far the community often underestimates often feels like a sore throat, flu, fever.…”

Section: Article Historymentioning

confidence: 99%

“…The object that has the closest similarity value to the k number is specified, then the new data object is selected. The specified k value uses odd number rules to get different distances in the data classification process [15]. Similarity is a way to calculate the value of the similarity of new data with existing data.…”

Section: K-nearest Neighbor (Knn)mentioning

confidence: 99%

Expert system for diagnosing diphtheria with k-nearest neighbor method

Fatoni¹,

Utami²,

Wibowo³

2018

IJARLIT

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The Diphtheria cases have special concern by the Indonesian government and are recorded as an extraordinary case (KLB) in 2017. Diphtheria is an infectious disease and cause complications of dangerous and deadly diseases if have not any treated immediately. Along this time, the communities often underestimate the common symptoms of diseases, such as throat pain, flu, and fever. The similarity of Diphtheria symptoms with common diseases and complications such as myocarditis, obstruction on breath, Acute Kidney Injury (AKI), making Diphtheria are rather difficult to treat due to the infections spread quickly. Some complications of diphtheria can cause a death if have not treated immediately and there must be any identification early for diphtheria. Then, an expert system is needed to help the community and the government in diagnosing the diphtheria. An expert system is an information system containing knowledge from experts in order provide information to be used for consultation. The knowledge from experts in this particular system is used as a basis by the Expert System to answer the questions (consultation). The study used the K-Nearest Neighbor (KNN) method, which the method calculates the similarity value of Diphtheria disease symptom. As the result, it can provide an initial diagnosis for Diphtheria before complications occur. The output of this study is the diagnosis of diphtheria based on the symptoms with the accuracy results of 93.056%, as well as providing an initial diagnosis in order to have immediately treating the diphtheria.

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Implementasi Algoritma K-Nearest Neighbor Dalam Pengklasifikasian Follower Twitter Yang Menggunakan Bahasa Indonesia

Cited by 25 publications

References 3 publications

Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Efektivitas Penjualan Vape (Rokok Elektrik) pada “Lombok Vape On”

Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Efektivitas Penjualan Vape (Rokok Elektrik) pada “Lombok Vape On”

Applied K-Nearest Neighbors (KKN) on Dust Suppression Prototype

Expert system for diagnosing diphtheria with k-nearest neighbor method

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