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Bayu Rizki
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Perbandingan Penggunaan Metode Topsis dan Metode AHP dalam Penilaian Kinerja pada Karyawan (PT XYZ) Muh Akbar Tamrin; Bayu Rizki; Andres Nodas; Ali Rahman; Esa Firmansyah
Infoman's : Jurnal Ilmu-ilmu Manajemen dan Informatika Vol. 14 No. 1 (2020): Infoman's
Publisher : STMIK Sumedang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33481/infomans.v14i1.123

Abstract

XYZ merupakan suatu perusahaan yang bergerak di bidang kuliner, Saat ini proses penilaian kinerja karyawaan pada PT. XYZ belum ada sehingga pihak PT. XYZ merasa kesusahan dalam menilai karyawan nya sendiri, Melaksanakan pemilihan karyawan terbaik bukan saja memilih dan menetapkan karyawan yang tepat.Maka dari itu diperlukan sistem pendukung keputusan yang akan memudahkan pemilihan karyawan terbaik dan membuat keputusan yang efektif dan efisien. Metode Topsis dan metode AHP merupakan metode yang akan digunakan dalam memberikan rekomendasi karyawan terbaik sesuai dengan yang diharapkan. Pada penelitian sebelumnya, peneliti telah melakukan penerapan metode topsis dalam menentukan karyawan terbaik pada PT. XYZ berdasarkan kriteria yang telah ditetapkan untuk penilaian sebanyak 4 kriteria yaitu Kerjasama (C1), Kejujuran (C2), Tanggung Jawab (C3) dan Kedisplinan (C4). Hasil Akhir dari penelitian yang dibuat adalah membantu pihak PT. XYZ dalam merekomendasikan karyawan terbaik dengan menggunakan metode Topsis dan metode AHP, Berdasarkan hasil perangkingan metode Topsis dengan nilai tertinggi yaitu 0,8710 adalah Agus Septa Triana dan dengan nilai terendah yaitu 0,0801 adalah Tari Nuraeni. Kemudian berdasarkan hasil perangkingan menggunakan metode AHP dengan nilai tertinggi yaitu 0,23015 adalah Agus Septa Triana dan dengan nilai terendah yaitu 0,02692 adalah Anisa R. Kemudian membandingkan metode Topsis dengan metode AHP pada tingkat akurasi keputusan sistem dengan keputusan perhitungan perusahaan, Untuk hasil tingkat akurasi metode AHP yaitu sebesar 70 persen, kemudian untuk hasil tingkat akurasi metode Topsis yaitu sebesar 20 persen.
Customer Loyality Segmentation on Point of Sale System Using Recency-Frequency-Monetary (RFM) and K-Means Bayu Rizki; Nava Gia Ginasta; Muh Akbar Tamrin; Ali Rahman
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.511

Abstract

It is no doubt that the development of the business world has been progressive. Point of sale is one of the many system used as a means of payment in various existing businesses, especially in heterogeneous markets. The activity of transactions between Point of Sale Systems and Customers occur in the business world. Keep in mind also that one of the main factors of business success, is from customers. There is the need of an attractive strategy and certainly it will be to increase the income and assets of a business. To know that, this research will explore the behavior of customer which is based marketing, through RFM Method (Recency, Frequency and Monetary). The case of this study is in Goldfinger Store. It will do segmentation and also use data mining technique to do clustering by using K-Means with result of loyal and potential customer. The results of segmentation using RFM (Recency, Frequency, Monetary) and K-Means methods have produced multiple clusters by dividing them into groups.
Customer Loyality Segmentation on Point of Sale System Using Recency-Frequency-Monetary (RFM) and K-Means Bayu Rizki; Nava Gia Ginasta; Muh Akbar Tamrin; Ali Rahman
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.511

Abstract

It is no doubt that the development of the business world has been progressive. Point of sale is one of the many system used as a means of payment in various existing businesses, especially in heterogeneous markets. The activity of transactions between Point of Sale Systems and Customers occur in the business world. Keep in mind also that one of the main factors of business success, is from customers. There is the need of an attractive strategy and certainly it will be to increase the income and assets of a business. To know that, this research will explore the behavior of customer which is based marketing, through RFM Method (Recency, Frequency and Monetary). The case of this study is in Goldfinger Store. It will do segmentation and also use data mining technique to do clustering by using K-Means with result of loyal and potential customer. The results of segmentation using RFM (Recency, Frequency, Monetary) and K-Means methods have produced multiple clusters by dividing them into groups.
Co-Authors Ali Rahman Ali Rahman Andres Nodas Esa Firmansyah Muh Akbar Tamrin Nava Gia Ginasta