Penerapan Metode K-Nearest Neighbor Untuk Sistem Rekomendasi Pemilihan Mobil

Suwirmayanti, Ni Luh Gede Pivin

doi:10.33633/tc.v16i2.1322

Cited by 13 publications

(13 citation statements)

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“…K-NN adalah rumus yang paling sederhana yang sering digunakan dalam pengimplementasian pencarian jarak. Rumus yang digunakan dalam perhitungan K-NN adalah rumus Euclidean Distance [2].…”

Section: Pendahuluanunclassified

Analisis Komparasi Algoritma Naïve Bayes dan K-Nearest Neighbor Untuk Memprediksi Kelulusan Mahasiswa Tepat Waktu

Gunawan¹,

Zarlis

Roslina

2021

mib

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Students are one of the important pillars in the life cycle of a university. In the process of developing, a university can be influenced by how many bachelor degree (S1) graduates from the university are. The number of graduations of a college sometimes has a low ratio when compared to the number of students admitted in the same school year. This low passing rate of students can be caused by several factors, such as the number of student activities that are participated in, economic factors, and several other unexpected factors. This makes a university must have a scheme or a formula that can predict whether the student can graduate on time. Normally, a bachelor (S1) student takes 8 semesters of education. But the existence of several factors that have been mentioned can make the time to take S1 education to be more, or even fail to graduate. This study will try to compare the results of the analysis of the two methods in the classification algorithm to predict student graduation. The algorithm used is the K-Nearest Neighbor and Naïve Bayes Algorithm. This study also aims to identify the best algorithm among the two classification algorithm choices. This research concluded that the Naïve Bayes algorithm has the same level of accuracy as the KNN algorithm in predicting the graduation of students in the Medical Education study program, which is 90%

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“…K-NN adalah rumus yang paling sederhana yang sering digunakan dalam pengimplementasian pencarian jarak. Rumus yang digunakan dalam perhitungan K-NN adalah rumus Euclidean Distance [2].…”

Section: Pendahuluanunclassified

Analisis Komparasi Algoritma Naïve Bayes dan K-Nearest Neighbor Untuk Memprediksi Kelulusan Mahasiswa Tepat Waktu

Gunawan¹,

Zarlis

Roslina

2021

mib

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“…The formula used in the calculation of kNN is the Euclidean Distance formula. The Euclidean distance is used [11] to find the distance between points in class k.…”

Section: K-nearest Neighbor K-nearestmentioning

confidence: 99%

Song Recommendation Application Using Speech Emotion Recognition

Setiawan

Dzulfiqar²

2021

IJID

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This research was conducted to facilitate the interaction between radio broadcasters and radio listeners during the song request process. This research was triggered by the difficulty of the broadcasters in monitoring song requests from listeners. The system is made to accommodate all song requests by listeners. The application produced in this study uses speech emotion recognition technology based on a person's mood obtained from the spoken words. This technology can change the voice into one of the mood categories: neutral, angry, sad, and afraid. The k-Nearest Neighbor method is used to get recommendations for recommended song titles by looking for the closeness of the value between the listener's mood and the availability of song playlists. kNN is used because this method is suitable for user-based collaborative problems. kNN will recommend three songs which then be offered to listeners by broadcasters. Based on tests conducted to the broadcasters and radio listeners, this study has produced a song request application by recommending song titles according to the listener's mood, the text message, the searching songs, and the song requests and the song details that have been requested. Functional test that has been carried out has received 100 because all test components have succeeded as expected.

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“…d(a,b) merupakan jarak tetangga terdekat atau nilai Euclidean yang diperoleh dari data sample dan data uji. Jumlah data sample dianyatakan dengan n, nilai dari data uji dinyatakan dengan Xa dan nilai data sample dinyatakan dengan Xb [12].…”

Section: Metode K-nearest Neighborunclassified

Referensi Penugasan Tenaga Teknisi Pada Penanganan Varian Kerusakan Menggunakan Decision Support System

Setiawan

Ratnawati

Prihandono

2021

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One type of asset managed by an agency is an asset that has a service life limit, if it is not properly maintained it will affect the quality of use. Maintenance can be in the form of routine and incidental maintenance carried out by technicians. Each technician has different abilities, so the assignment should be based on objectivity. The high quantity of maintenance on all assets in an agency and often lack of attention to the division of tasks on all technicians resulted in some technicians having to accept maintenance assignments on assets that were not in accordance with their fields. The right steps were taken to support the decision to refer technicians to an asset maintenance process using the K-Nearest Neigbor method. The final result shows that the percentage of occurrences of referenced names occupies the highest percentage, namely 66% with a value of k=3, so that k=3 is suitable for the process of reference for technicians.

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Penerapan Metode K-Nearest Neighbor Untuk Sistem Rekomendasi Pemilihan Mobil

Cited by 13 publications

References 0 publications

Analisis Komparasi Algoritma Naïve Bayes dan K-Nearest Neighbor Untuk Memprediksi Kelulusan Mahasiswa Tepat Waktu

Analisis Komparasi Algoritma Naïve Bayes dan K-Nearest Neighbor Untuk Memprediksi Kelulusan Mahasiswa Tepat Waktu

Song Recommendation Application Using Speech Emotion Recognition

Referensi Penugasan Tenaga Teknisi Pada Penanganan Varian Kerusakan Menggunakan Decision Support System

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