Pemanfaatan Data Mining Untuk Penempatan Buku Di Perpustakaan Menggunakan Metode Association Rule

Yanto, Robi; Kesuma, Hendra Di

doi:10.35957/jatisi.v4i1.83

Cited by 21 publications

(20 citation statements)

References 1 publication

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“…Seperti pada penelitian yang dilakukan oleh Robi Yanto dkk (2017), tema penelitian adalah memanfaatkan data mining untuk mendapatkan pola penempatan buku di perpustakaan, namun metode yang digunakan adalah Association Rule. Penentuan pola penempatan buku yang dilakukan berdasarkan 3 item set buku [2]. Terdapat juga penelitian yang dilakukan oleh Kennedi Tampubolon dkk (2013), dimana penelitian mengambil topik implementasi data mining pada sistem persediaan alat-alat kesehatan menggunakan metode apriori.…”

Section: Pendahuluanunclassified

Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Meningkatkan Pola Penjualan Obat

Saputra

Sibarani

2020

JATISI

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Dengan adanya kegiatan transaksi penjualan setiap hari, data semakin lama akan semakin bertambah banyak. Data tersebut tidak hanya berfungsi sebagai arsip bagi perusahaan, data tersebut dapat dimanfaatkan dan diolah menjadi informasi untuk meningkatan penjualan obat. Permasalahan yang sering timbul di Apotik Pusaka Arta yaitu sering sekali penjualan obat yang diinginkan konsumen tidak ada atau habis karena apotek tidak memperhatikan stok, apotek tidak memanfaatkan data transaksi penjualan yang ada dan biasanya data transaksi penjualan tersebut hanya menjadi arsip yang tidak dimanfaatkan. Untuk memecahkan masalah tersebut, maka dibuatlah aplikasi Data mining menggunakan Algoritma Apriori. Metode yang dipakai penulis dalam menerapkan penelitian ini adalah Association Rules. Asociation Rule merupakan suatu teknik dalam data mining untuk menentukan hubungan antar item dalam satu data set (sekumpulan data) yang telah ditentukan. Teknik ini mencari kemungkinan kombinasi yang sering muncul (frequenct) dari suatu itemset (sekumpulan item). Dalam penelitian ini Association Rule berfungsi untuk menganalisa beberapa sering suatu obat yang sering dijual secara bersamaan, analisis ini akan ditinjau dari data transaksi yang telah terjadi. Penerapan Algoritma Apriori dalam aplikasi ini berhasil mencari kombinasi item terbanyak berdasarkan data transaksi dan kemudian membentuk pola asosiasi dari kombinasi item tersebut. Hasil aplikasi ini dapat mengetahui apa saja obat yang sering dibeli oleh konsumen secara bersamaan sehingga dapat mengetahui pola penjualan obat.

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Section: Pendahuluanunclassified

Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Meningkatkan Pola Penjualan Obat

Saputra

Sibarani

2020

JATISI

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“…Metode asosiasi merupakan salah satu metode data mining yang dapat digunakan untuk menganalisa data transaksi penjualan. Metode asosiasi akan meng-asosiasikan data dengan menggunakan aturan apriori (pengalaman) yang memenuhi syarat minimum support (nilai penunjang), yaitu kombinasi tiap item dalam database dan syarat minimum confidence (nilai kepastian), yaitu kuatnya hubungan antar item dalam aturan asosiasi [5]. Pada penelitian ini akan dianalisa data transaksi penjualan selama tiga bulan dari dropshipper bidang usaha penjualan produk beauty and fashion menggunakan metode asosiasi dengan algoritma apriori untuk mencari pola data paket produk (product bundling).…”

Section: Pendahuluanunclassified

Market Base Analysis in Dropship Business With Apriori Algorithm in Determining R-Based Product Bundling

Fauziyyah¹

2019

IJUBI

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The association method will associate data using a priori (experience) rules that meet the minimum support requirements, namely the combination of each item in the database and the minimum confidence requirement, namely the strength of the relationship between items in the association rules. In this study, the sales transaction data for three months will be analyzed from the dropshipper in the field of sales of beauty and fashion products using the association method with a priori algorithm to look for product bundling data patterns. The minimum value of support is 10% and 20% confidence, and with % ain function where Ordinary Shampoo items become the main products in product bundling, obtained 15 packages of the strongest products with lift values more than 1.

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“…The data mining preparation process uses SEMMA, this stage is often used in solving data mining problems, the steps that will be taken to produce a knowledge from the data that has been obtained are as follows [9]: [10] The stages that are passed are as follows: 1) Sample Collection of data that will become the main data mining processing material, the completeness of the data in each item that is also considered at this stage.…”

Section: Semma Stagementioning

confidence: 99%

“…The amount of initial data entered at the Sample stage is as much as 1503 data on accident cases. Then in the Explore stage, the data were grouped based on the area of each Polres, the data group was divided into 2 regions [10] of Tasikmalaya with a total of 795 data and the area of Ciamis Regency as many as 565 data [11]. After arriving at the Modify stage, the amount of data becomes 1360 accident data with the variable description of the involved actors, namely gender (male and female), age-grouped into 5 The determination of the data mining calculation process model is the association rule model using the Apriori algorithm to get the relationships between available data to see the involvement of variables involved in the accident in each region, namely Tasikmalaya and Ciamis Regency.…”

Section: ) Assessmentioning

confidence: 99%

Associative Analysis Data Mining Pattern Against Traffic Accidents Using Apriori Algorithm

Ruswati

Gufroni²,

Rianto³

2018

SJI

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Traffic accidents are one of the causes of high mortality in the community. Based on information from the World Health Organization (WHO) the number of accident victims in each year amounts to 1,300,000 fatalities, this is caused by traffic accidents that exist throughout the world. The police recorded data on accidents that occurred in several regions of East Priangan namely Ciamis and Tasikmalaya Regencies for the 2016-2017 period reaching an accident rate of ± 1500. The analysis that can be done to reduce the intensity of the occurrence of these events is to use data mining processing techniques. The right method is used by looking at the condition of the data obtained, namely the Association Rules method with the calculation of the Apriori Algorithm. This method will look for patterns of data relations that are formed from combinations of an itemset, so that knowledge will appear from large datasets. The pattern of the relationship sought is the linkages of itemset variables involved in the accident by involving 4 variables that describe the identity of the perpetrators, namely gender, age, profession and level of education and 22 attributes of the dataset. The minimum limit of support, confidence and lift ratio values used in the Apriori Algorithm calculation rules is 15%, 70% and 1.1. This value is used to get many rules that have a high level of occurrence accuracy. The results of the combination pattern calculation were 3 times iterations on each number of data in each region, the pattern of associations found in the Tasikmalaya region were the relation of the professional variables and the age of the perpetrator with the attribute of the Student profession dataset and the boundary group ages 16 to 30 years, while for the pattern associations found in the area of Ciamis Regency, namely the relation between age and education level with the attribute dataset of the 16 to 30 year age group and high school education level. The accuracy of the value obtained is calculated manually and uses one of the data mining applications as a comparison of value accuracy, namely Tanagra 1.4.

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Pemanfaatan Data Mining Untuk Penempatan Buku Di Perpustakaan Menggunakan Metode Association Rule

Cited by 21 publications

References 1 publication

Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Meningkatkan Pola Penjualan Obat

Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Meningkatkan Pola Penjualan Obat

Market Base Analysis in Dropship Business With Apriori Algorithm in Determining R-Based Product Bundling

Associative Analysis Data Mining Pattern Against Traffic Accidents Using Apriori Algorithm

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