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All Journal Jurnal Teknologi Dan Sistem Informasi Bisnis SIGMA: Information Technology Journal VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian
Surojudin, Nurhadi
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Journal : SIGMA: Information Technology Journal

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Metode Data Mining Untuk Data Permintaan Pemeliharaan Spare Part Menggunakan Algoritma Apriori Surojudin, Nurhadi; Halim Anshor, Abdul
Jurnal SIGMA Vol 14 No 4 (2023): Desember 2023
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Spare part merupakan komponen vital dalam sebuah mesin, tanpa adanya spare part mengakibatkan mesin stop atau tidak dapat beroperasi. Agar peristiwa tersebut tidak terjadi kita dituntutmenyiapkan spare part yang biasa digunakan dalam bentuk stocking spare part. Kita harus bisa memprediksi periode minimum stock part, sehingga bisa dengan langsung melakukan request part tersebut. Kita harus bisa menentukan kombinasi spare part yang kemungkinan besar akan direquest secara bersamaan. Terdapat retusan bahkan ribuan data transaksi request spare part, pemberdayaan data sangat penting untuk menggunakan data yang banyak tersebut agar bisa menjadi sebuah informasi yang bermanfaat dalam membantu stocking part. Salah satunya adalah dengan metode data mining terhadap data request tersebut menggunakan algoritma apriori. Karena lgoritma apriori dinilai cocok dalam penentun part yang consumable agar memiliki periode request yang continue dan juga menentukan kombinasi antara masing masing part yang sering direquest. Kata Kunci: Algoritma Apriori, Perawatan, Sparepart
Analisis Dan Implementasi Data Mining Untuk Menentukan Penilaian Kinerja Karyawan Rilvani, Elkin; Surojudin, Nurhadi
Jurnal SIGMA Vol 14 No 4 (2023): Desember 2023
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

A company must be selective in conducting employee assessments in order to retain employees with the best performance. In assessing employee performance, it can be seen from diligence and discipline. But in reality, employees' good performance sometimes gets bad reviews and even a warning from their superiors. This is caused by the employee assessment monitoring system used, namely only personal assessment without using an assessment system and the data collected is not optimal. Seeing the problems above, the author conducted research using the Naive Bayes method to carry out data processing using data mining algorithms to obtain predictions that can be used as additional references in employee performance assessment decisions for contract extensions. Naive Bayes is a data processing algorithm that is classified as a calculation that is easy to understand but whose accuracy results are reliable. The author also uses the Rapidminer supporting application to test the accuracy of the system created. Testing was carried out by preparing 320 data and testing data of 50 randomly selected data. The testing data will be analyzed using the Rapidminer supporting application. The test results produced an accuracy of 83.96%. Keywords: Employees, Assessment, Data Mining, Naïve Bayes Algorithm
Co-Authors ., Edora Abdul Ghofir Andriani Apisca, Dhea Djoko Nugroho Effendi, Muhammad Makmun Elkin Rilvani Halim Anshor, Abdul Muktiali, Saiful Pradini, Purnama Sakhrial Purnama Sakhrial Siswandi, Arif Suryadi, Dikky Turmud Zy, Ahmad Zy, Ahmad Turmudi