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All Journal JISI UMJ (Jurnal Integrasi Sistem Industri UMJ) Jurnal Logistik Indonesia Majalah Ilmiah Bijak International Journal of Research in Vocational Studies (IJRVOCAS)
Zulvia, Ferani Eva
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Aerospace Engineering Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Customer Segmentation Using the K-means Clustering Algorithm and Recency Frequency Monetary Model at Pharmaceutical Product Wholesaler Iqbal, Nur Muhammad; Iskandar, Yelita Anggiane; Zulvia, Ferani Eva
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.293

Abstract

PT Kimia Farma Trading and Distribution (KFTD) is a company engaged in the distribution and trading services of Indonesian health products, on a national scale. In 2022, the company aims to increase sales to be awarded as one of the top 3 national pharmaceutical product distributors by 2024. Their current strategy is to provide customers with delayed payment permission and integrated complaint services. However, the offers and services are the same for all customers which does not consider customer track record hence it is not cost-effective. One way to increase sales is by enhancing customer satisfaction and loyalty by implementing Customer Relationship Management (CRM) strategies. Several strategies can be carried out, namely analysis of associations related to pharmaceutical products, and analysis of customer segmentation and clustering of products. The method used in this study was the K-means clustering algorithm combined with the Recency Frequency Monetary (RFM) model. Experiments showed that the optimal clustering results are 4 therefore they are categorized into 4 customer segments, namely Superstar, Golden, Typical, and Occasional Customers.
Intentions to Sustainably Use Air Transportation During the Pandemic: A Structural Equation Model Analysis Kamilia, Rifka Alifa; Iskandar, Yelita Anggiane; Zulvia, Ferani Eva
Majalah Ilmiah Bijak Vol 20, No 2: September 2023
Publisher : Institut Ilmu Sosial dan Manajemen STIAMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31334/bijak.v20i2.3407

Abstract

This research was motivated by the pandemic due to the Corona-19 virus which resulted in the crippling of the aviation industry.  Angkasa Pura II, specifically Soekarno-Hatta Airport, a company specializing in airport services and airport-related services, has experienced a significant decline in its revenue. Specifically, the company has lost an alarming 50% of its total revenue. This substantial decrease in earnings has undoubtedly had a profound impact on the organization's financial stability and future prospects. Soekarno Hatta Airport experienced a decrease in the number of passengers from 27,163,886 people per year in 2019 to a very significant decline in 2020 to 10,139,718. The pandemic has changed people's behavior in traveling using air transportation. One of their considerations is getting infected while traveling. This study aims to examine the effect of passenger satisfaction variables, subjective norms, attitudes, perceptions of behavioral control, and perceptions of travel risk on travel intentions using air transportation during the pandemic. This research was conducted by surveying 145 respondents who had used the services of Angkasa Pura II. The analytical method used in this study is the SEM-PLS with SmartPLS 3.0. Results showed that air travel intentions during the pandemic are significantly affected by passengers' satisfaction, subjective norms, and perceptions of behavioral control. Meanwhile, the variables of attitude and perception of travel risk did not significantly affect the intention to travel using air transportation during the pandemic.
IMPLEMENTASI DATA MINING DENGAN ALGORITMA APRIORI UNTUK PENINGKATAN PENJUALAN MELALUI STRATEGI MIXED BUNDLING DI PT X Iskandar, Yelita Anggiane; Zulvia, Ferani Eva; Nissya, Agtandella Islamy
JISI: Jurnal Integrasi Sistem Industri Vol 11, No 2 (2024): JISI UMJ
Publisher : Fakultas teknik Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jisi.11.2.249-260

Abstract

Pada tahun 2021, PT X mengalami penurunan penjualan pada saluran penjualan melalui e-commerce. Untuk meningkatkannya kembali, diperlukan penerapan strategi bisnis selain yang sudah diterapkan sebelumnya, dengan mengetahui pola asosiasi antar item produk yang dibeli konsumen yang dapat menjadi dasar pembuatan rekomendasi berdasarkan salah satu prinsip customer relationship management yaitu strategi mixed bundling. Data yang digunakan adalah data transaksi penjualan produk melalui e-commerce PT X dari April hingga Oktober 2021, dengan jumlah sebanyak 5.673 transaksi. Metode yang digunakan adalah data mining association rule spesifiknya algoritma apriori. Dengan menggunakan minimum support sebesar 0,15 dan minimum confidence sebesar 0.5, maka didapatkan hasil yang telah divalidasi, yaitu terdapat 5 rules untuk family product dan 5 rules untuk item produk. Dari eksperimen diketahui bahwa produk Pasta sering dibeli bersamaan dengan produk Flour, produk Cookies dan Pasta sering dibeli bersamaan dengan produk Flour, produk Noodle sering dibeli bersamaan dengan produk Flour, produk Cookies dan Noodle sering dibeli bersamaan dengan produk Flour, serta produk Noodle dan Pasta sering dibeli bersamaan dengan produk Flour. Selanjutnya dilakukan penyusunan rekomendasi strategi penjualan, terdapat 4 produk mixed bundling yang dapat menjadi alternatif dalam strategi pemasaran PT X untuk meningkatkan penjualan, yaitu produk CBT01 dan CBM01, MBL01 dan MBT01, CPB01 dan CBM01, serta CPB01 dan CBT01.
Association Rules Mining for Designing Product Bundling Strategy (Study Case at a Cafe in Jakarta) Jannah, Milqi Miftahul; Iskandar, Yelita Anggiane; Zulvia, Ferani Eva
Jurnal Logistik Indonesia Vol. 7 No. 2: Oktober 2023
Publisher : Institut Ilmu Sosial dan Manajemen Stiami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31334/logistik.v7i2.3466

Abstract

Cafe X is a modern and prominent coffee shop in town that sells specialty beverage products with a total of 73 variations. Sales transactions that occurred in March 2021 at that Cafe reached an average of 300 times per day. All this time, the transaction data is only used to calculate inventory replenishment and to observe sales profits whereas it can actually be utilized to reveal information related to customer behavior in buying products by finding the association or pattern between product sales. The purpose of this study is to obtain association models between items that can be used as a base to arrange recommendations for selling beverage products at Cafe X using a data mining method, namely the association rules with the Apriori algorithm. The transaction data specified for data processing are payment transactions of a total of 3,100 data records. From the analysis results, it is known that there are 8 product association rules that meet the minimum support of 0.01 and the minimum confidence of 0.5, which means that these rules can be used as an alternative basis for determining business strategy at Cafe X. Based on the association information between products, the customer relationship management (CRM) strategy that can be applied at Cafe X is the promotion strategy of product bundling. From a number of recommended bundled products, it is found that there are opportunities to increase sales for four products, they are MD001, TH002, LB001, and TU001.
Co-Authors Iqbal, Nur Muhammad Iskandar, Yelita Anggiane Jannah, Milqi Miftahul Kamilia, Rifka Alifa Nissya, Agtandella Islamy