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All Journal Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan Journal of Computer Scine and Information Technology
Indah Dwi Putri
IPB
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Social Sciences

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Pengaruh Kompensasi, Lingkungan Kerja, dan E-Rekruitment terhadap Daya Tarik Perusahaan bagi Pelamar Kerja (Studi pada Generasi Z di Tribuana Global Group) Putri, Indah Dwi; Zaman, Kamar
Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan Vol. 18, No. 1 : Al Qalam (Januari 2024)
Publisher : Sekolah Tinggi Ilmu Al-Qur'an (STIQ) Amuntai Kalimantan Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35931/aq.v18i1.2998

Abstract

Tujuan dari penelitian ini adalah untuk menilai dampak kompensasi, lingkungan kerja, dan e-rekrutmen terhadap daya tarik perusahaan bagi pelamar kerja Generasi Z di Tribuana Global Group. Penelitian ini menggunakan pendekatan kuantitatif dengan perspektif deskriptif. Pengambilan sampel biasanya dilakukan secara acak. Pemodelan Persamaan Struktural berdasarkan perangkat lunak Partial Least Square (SEM-PLS) digunakan untuk menganalisis data dalam penelitian ini, dan variabel-variabel yang diselidiki relatif belum banyak diteliti. Temuan dari penelitian ini mengungkapkan bahwa kompensasi dan e-rekrutmen memiliki pengaruh positif dan signifikan terhadap daya tarik perusahaan. Namun, lingkungan kerja tidak memiliki pengaruh positif dan signifikan terhadap daya tarik perusahaan.
Application of the FP-Growth Algorithm in Consumer Purchasing Pattern Analysis Putri, Indah Dwi; Yuhandri; Hardianto, Romi
Journal of Computer Scine and Information Technology Volume 10 Issue 2 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i2.99

Abstract

Technology is currently used in various ways, one of which is businesses engaged in selling daily products. The right marketing strategy makes knowledge of consumer shopping patterns important to study because consumers are the main actors in carrying out transactions. The more diverse the types of goods sold in a company, the more diverse the resulting consumer spending patterns will be. Data mining is an analysis process that is carried out automatically on complex and large amounts of data to obtain patterns or trends that are generally not realized. The FP-Growth algorithm is an alternative algorithm that can be used to determine the data set that appears most frequently (frequent itemset) in a data set. The method used in this research is the FP-Growth method which is implemented in the PHP programming language and MySQL as the database. Designing a data mining program using the FP-Growth method can analyze and manage consumer purchasing patterns based on goods purchased simultaneously. The data processed in this research is transaction data that has been processed into information so as to gain knowledge in calculating stock of goods sourced from the owner of Toko Asra. From testing this method, results were obtained from the 10 transactions in December 2021, by limiting the minimum support value to 0.2 and minimum confidence to 0.75, 33 patterns of consumer shopping habits were obtained, meaning that 33 products were most frequently purchased by consumers. Designing a data mining program using the FP-Growth method can help analyze consumer purchasing patterns based on items purchased simultaneously. The results of frequent itemset calculations can help find a sequence of combinations that can be used as product recommendations in business decision
Co-Authors Edison Jambormias Hardianto, Romi Surjono Hadi Sutjahjo Yuhandri Zaman, Kamar