Article Per Year (5 Year)
p-Index From 2019 - 2024
2.765
P-Index
This Author published in this journals
All Journal JUITA : Jurnal Informatika CESS (Journal of Computer Engineering, System and Science) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Pilar Nusa Mandiri ILKOM Jurnal Ilmiah MULTINETICS Simpatik: Jurnal sistem Informasi dan Informatika J-Intech (Journal of Information and Technology) J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Ladang Artikel Ilmu Komputer
Satia Suhada, Satia
Program Studi Sistem Informasi, Universitas Bina Sarana Informatika, Sukabumi, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 23 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 23 Documents
Search

 1   2   3 
Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Profile Matching Pada Alia Citra Dekorasi (ACD) Selvia Septi Palupi; Satia Suhada
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 1 No 2 (2021): Desember 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (316.277 KB) | DOI: 10.31294/larik.v1i2.705

Abstract

Employees are one of the main things in a company both in the progress, smoothness, and success of a company, the role of employees is very important. The company realizes how important the role of employees is in the success of a company, therefore the company tries to continue to provide motivation, one of which is by selecting the best employees. The selection of the best employees at Alia Citra Decor (ACD) is still done manually, namely selecting employees who are considered to have good performance by company leaders without an accurate assessment. To overcome these problems a decision support system (SPK) with the Profile Matching method is very helpful in solving the problem of selecting the best employees at Alia Citra Decor. By using the Profile Matching method, ACD can make decisions through employee performance appraisals based on existing aspects according to abilities. With the Profile Matching method, it is possible to determine the percentage of objects or aspects that are assessed and totaled, then a ranking process is carried out which will determine the optimal alternative, namely the best employees.
Kombinasi Tomek-Link Dan Smote Untuk Mengatasi Ketidakseimbangan Kelas Pada Credit Card Fraud Wahyu Nugraha; Deni Risdiansyah; Deasy Purwaningtias; Taufik Hidayatulloh; Satia Suhada
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 2 (2022): Desember 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.131 KB) | DOI: 10.31294/larik.v2i2.1789

Abstract

Increasing online trading activities or e-commerce has become a trend today. As a result the most common crime is credit card fraud or carding. There are approximately 1,000 cases of fraud in one million transactions so that data is collected in the form of datasets of credit card fraud risk. In some cases, minority classes are more important to identify than the majority class as in the case of credit card transactions. In this study to deal with the problem of class imbalances on credit card fraud risk datasets, the proposed resampling method is the Tomek-Link and SMOT data level with the C5.0 classification model. This research was conducted to improve the accuracy of AUC in the C5.0 classification algorithm model. The results showed that the proposed method was able to increase the AUC value of 0.134 compared to without the resampling method.
Sistem Rekomendasi Produk Menggunakan Metode User-Based Collaborative Filtering Pada Digital Marketing Satia Suhada; Saeful Bahri; Setyo Bagus Nugraha; Taufik Hidayatulloh; Dede Wintana
J-INTECH (Journal of Information and Technology) Vol 11 No 1 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i1.866

Abstract

The recommendation system has been implemented in digital marketing used in marketing products and services. The recommendation system is used to provide offers of goods and services in accordance with customer habits and interests in the proposed products and services, but in practice the right product offering for customers leads to the idea of developing a product recommendation system. Purchase data obtained from customers can be used to analyze customer needs and product preferences. In the recommendation system, Collaborative Filtering is one of the most commonly used algorithms. The purpose of this study is to find out how accurate the recommendation system is based on the purchase of similar goods between consumers using User-based Collaborative Filtering. Based on the results of the study, User-based Collaborative Filtering using Cosine Similarity calculations can be applied and produce 10 product recommendations with an RMSE value of 0.9.
Co-Authors A.Gunawan Abidin Abidin Acep Suherman Ami Rahmawati Andi Riyanto Ardi Winardi Arif Purnama Daniel Ratag Dasya Arif Firmansyah Dede Wintana Dede Wintana Desi Susilawati Dicky Prayudi Dwiza Riana Eva Marsusanti Eva Marsusanti Eva Nursyifa Gunawan Gunawan Gunawan Gunawan Gunawan Hamdun Sulaiman Jamal Maulana Hudin, Jamal Maulana Jasisca Marleftan Lestari Yusuf Muhamad Reza Vahlefi Purwaningtias, Deasy Rahmawati, Ami Ramdhan Saepul Rohman Rina Riniawati Risdiansyah, Deni Rusda Wajhillah Rusli Nugraha Rusli Nugraha Saeful Bahri Saeful Bahri Selvia Septi Palupi Setyo Bagus Nugraha Siskawati Siskawati Siti Fatimah Susilawati Susilawati Taufik Hidayatulloh Taufik Hidayatulloh Wahyu Nugraha Wintana, Dede Yahya Iskandar Yulhan Wahyudin