Studi Komparasi Model Klasifikasi Berbasis Pembelajaran Mesin untuk Sistem Rekomendasi Program Studi

Pratama, Ahmad R.; Aryanto, Rio Rizki; Iswari, Lizda

doi:10.29207/resti.v5i5.3392

Cited by 2 publications

(3 citation statements)

References 3 publications

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“…Setelah dilakukan pengelompokkan data dan mendapatkan hasil dari tiap setiap algoritma, dilakukan studi komparasi untuk membandingkan dua hingga lebih objek penelitian. Hal ini dilakukan untuk menemukan persamaan dan perbedaan dari objek-objek tersebut [12].…”

Section: A Studi Pustakaunclassified

“…Beberapa metode dalam algoritma Hierarchical yang sering digunakan adalah Single Linkage, Complete Linkage, Average Linkage, Average Group Linkage, dan masih banyak lagi. 𝑋 𝑘𝑗 (12) di mana rata-rata dari cluster i untuk variabel j, 𝑁 𝑖 jumlah data, i dan k menjadi indeks klaster, j merupakan indeks variabel, 𝑋 𝑘𝑗 nilai data k untuk variabel j. 6) Kelima tahapan tersebut dilakukan hingga klaster tidak berubah.…”

Section: Hierarchicalunclassified

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Komparasi Algoritma Hierarchical, K-Means, dan DBSCAN pada Analisis Data Penjualan Melalui Facebook

Wahyuningtyas,

Arafat,

Stiawan

et al. 2023

Explore. jurnal. sistem. inf. dan. telematika

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The use of the internet in Indonesia to access social media has increased from the previous four years, where 36.36% of users still use social media Facebook. The average social media users are teenagers with smartphones. Facebook has features that are favored by its users for buying and selling activities, so that it can increase user engagement and sales data. To analyze the increase in sales data, this study uses data mining with clustering methods. By using secondary data from the UCI Repository, a comparative analysis of three different algorithms was carried out to find out which is the best among the Hierarchical, K-Means, and DBSCAN algorithms. The results showed that the Hierarchical algorithm obtained the highest silhouette score, namely 0.884, a fairly thin difference with the silhouette score obtained by K-Means, which was 0.872. Furthermore, the results of comparisons made using performance indicators show that K-Means is the best algorithm with an average execution time of 0.402 seconds, a considerable difference from the other two algorithms. Based on the two indicators that have been used, it can be seen that the best algorithm for analyzing sales data via Facebook is the K-Means algorithm. Finally, the appearance of the number of clusters 2 from the K-Means algorithm can group sales data via Facebook into two categories, namely "Busy Posts" and "Lone Posts".

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Section: A Studi Pustakaunclassified

Section: Hierarchicalunclassified

Komparasi Algoritma Hierarchical, K-Means, dan DBSCAN pada Analisis Data Penjualan Melalui Facebook

Wahyuningtyas,

Arafat,

Stiawan

et al. 2023

Explore. jurnal. sistem. inf. dan. telematika

View full text Add to dashboard Cite

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“…Pemilihan program studi yang akan diampu menjadi tantangan tersendiri bagi calon mahasiswa. Pemilihan ini dipengaruhi berbagai faktor seperti tingkat ekonomi, geografis, prestasi akademik, kompetitor dan lain sebagainya [1]. Pemilihan program studi ini sangat penting, karena dapat menimbulkan efek negatif jika salah dalam proses pengambilan keputusan terhadap program studi yang dipilih seperti ketidakoptimalan prestasi, penguasaan materi yang kurang, serta ketidakpuasan terhadap hasil studi mahasiswa [2].…”

Section: Pendahuluanunclassified

Komparasi Algoritma Klasifikasi Data Mining Menggunakan Optimize Selection untuk Peminatan Program Studi

Anam¹,

Nurhakim²,

Juliane³

2022

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The selection of a study program is a unique opportunity for a student. STMIK IKMI Cirebon is now a KIP Kuliah provider, offering three study program. The research problem is the unavailability of a model of student interest in the study program, so it is necessary to carry out an interest in the study program by applying an algorithm to the classification model. The algorithm used as a comparison is the Decision Tree algorithm (C4.5), Naive Bayes, k-Nearest Neighbor and Support Vector Machine. The classification model applies the Optimize Selection operator by looking for the dominant attribute in its influence on the specialization of the student study program. Finally, the comparison model will be tested by parametric t-test in order to test the significance of the algorithm. The results of the algorithm accuracy test obtained that the SVM algorithm has the best accuracy with a value of 80.76%. While the algorithm with the lowest accuracy is Naive Bayes with a value of 74.64%. While the other two algorithms have a sequential accuracy rate of 80.47% for Decision Tree and 76.09% for k-NN. The results of this study are used to classify study preference for students in STMIK IKMI Cirebon which is useful for predicting study interest based on the background of students

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Studi Komparasi Model Klasifikasi Berbasis Pembelajaran Mesin untuk Sistem Rekomendasi Program Studi

Cited by 2 publications

References 3 publications

Komparasi Algoritma Hierarchical, K-Means, dan DBSCAN pada Analisis Data Penjualan Melalui Facebook

Komparasi Algoritma Hierarchical, K-Means, dan DBSCAN pada Analisis Data Penjualan Melalui Facebook

Komparasi Algoritma Klasifikasi Data Mining Menggunakan Optimize Selection untuk Peminatan Program Studi

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