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All Journal Komversal: Jurnal Komunikasi Universal Jurnal Manajemen Riset Inovasi
Dzaky Muhammad Baihaqi
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Decision Sciences, Operations Research & Management Environmental Science Social Sciences

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Penggunaan Aplikasi Michat Sebagai Sarana Prostitusi Online Di Kota Bandung Dzaky Muhammad Baihaqi; Qisthy Rabathy
KOMVERSAL Vol 5 No 2 (2023): Komversal : Jurnal Komunikasi Universal
Publisher : Program Studi Hubungan Masyarakat Politeknik LP3I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/komversal.v5i2.1444

Abstract

This study aims to determine the motives, actions and meanings of the use of online prostitution in the city of Bandung. In this research uses qualitative research methods, and using phenomenological theory by Alfred Schutz with data collection techniques used are library research, field observations and in-depth interviews with informants. The results of this study indicate that there are similarities and differences between the informants. Like the motives of MiChat users, which are divided into two, namely sex workers and service users, for sex workers the motive for using MiChat is driven by economic factors and the influence of friends, while for users it is influenced by curiosity, the desire to have sex, and also environmental influences.
Optimalisasi Strategi Pemasaran Melalui Analisis RFM pada Dataset Transaksi Ritel Menggunakan Python Andy Hermawan; Nila Rusiardi Jayanti; Aji Saputra; Cahaya Tambunan; Dzaky Muhammad Baihaqi; Muhammad Alif Syahreza; Zacharia Bachtiar
Jurnal Manajemen Riset Inovasi Vol. 2 No. 4 (2024): Oktober : Jurnal Manajemen Riset Inovasi
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/mri.v2i4.3246

Abstract

This study aims to optimize marketing strategies through RFM (Recency, Frequency, Monetary) analysis on a retail transaction dataset obtained from Kaggle. The dataset contains 64,682 transactions from 5,242 SKUs involving 22,625 customers over one year. Data cleaning and RFM analysis were conducted to segment customers based on recency, frequency, and monetary values. The findings reveal that customers were segmented into groups such as Champions, Loyal Customers, and At Risk. These segments provide valuable insights for developing targeted marketing strategies, such as loyalty programs for high-value customers and retention campaigns for at-risk customers. The study demonstrates that RFM analysis is effective in identifying valuable customer segments and optimizing marketing efforts based on customer behavior. This approach can increase customer retention and improve the return on investment (ROI) in marketing campaigns.
Co-Authors Aji Saputra Andy Hermawan cahaya Tambunan Muhammad Alif Syahreza Nila Rusiardi Jayanti Rabathy, Qisthy Zacharia Bachtiar