Article Per Year (5 Year)
p-Index From 2019 - 2024
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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Journal of Informatics and Computer Science (JINACS)
Ghea Sekar Palupi
Universitas Negeri Surabaya
Computer Science & IT Electrical & Electronics Engineering

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Fear of missing out during a pandemic: the driving factors of telemedicine application acceptance Muhammad Noor Fakhruzzaman; Ghea Sekar Palupi; Thinni Nurul Rochmah
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3848

Abstract

COVID-19 pandemic changed how society behaves. Travel and social restrictions, commonly associated with the term lockdown became popular and ubiquitous. Given the rise of gig economy and mobile app delivery in the past several years, combined with lockdowns during the pandemic, and the application of telemedicine becomes essential. Halodoc is one of the popular telemedicine applications in Indonesia, having several useful features such as text-based doctor consultation and prescription drug order-delivery, and Halodoc is easily preferred by many. This article explored the motivation behind using Halodoc as the preferred method of getting health service during the pandemic, behind the perceived usefulness and perceived ease of use of the application, we found that fear of missing out (FOMO) has an indirect role in the application adoption in society, especially during lockdowns, where social interaction is limited to social media and other internet-based platforms. The reason why FOMO can be an important factor in technology adoption and how advertisers should explore FOMO is further discussed.
Studi Penelusuran Alumni Prodi Sistem Informasi Jurusan Teknik Informatika Universitas Negeri Surabaya Ghea Sekar Palupi; Aries Dwi Indriyanti
Journal of Informatics and Computer Science (JINACS) Vol 3 No 02 (2021)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.108 KB) | DOI: 10.26740/jinacs.v3n02.p165-170

Abstract

Abstrak— Relevansi dan kesesuaian yang baik antara program studi di pendidikan tinggi sebagai penyedia sumber daya manusia dan dunia kerja sebagai penyedia lapangan kerja merupakan salah satu aspek keberhasilan implementasi kurikulum program studi. Namun, pada kenyataannya masih banyak para lulusan perguruan tinggi bekerja tidak sesuai dengan kompetensi yang didapatkan selama kuliah. Untuk meneliti seberapa besar tingkat lulusan program studi terserap dalam dunia kerja dapat dilakukan sebuah upaya penelusuran terhadap para lulusannya yang disebut dengan tracer study. Penelitian ini dilakukan pada alumni Program Studi Sistem Informasi Jurusan Teknik Informatika Universitas Negeri Surabaya dengan tahun lulus 2019-2020 dan pengguna alumni. Tujuan penelitian ini adalah untuk melihat kompatibilitas antara kompetensi yang dimiliki oleh lulusan Program Studi Sistem Informasi Jurusan Teknik Informatika Universitas Negeri Surabaya dengan ekspektasi pengguna lulusan. Harapannya, hasil dari penelitian ini dapat digunakan sebagai rekomendasi untuk meningkatkan mutu pelayanan pendidikan di Program Studi Sistem Informasi Jurusan Teknik Informatika Universitas Negeri Surabaya. Metode penelitian ini adalah survei secara online dengan pendekatan analisis deskriptif kuantitatif. Kata Kunci— tracer study, alumni, relevansi, kurikulum, sistem informasi, program studi
Indonesian pharmacy retailer segmentation using recency frequency monetary-location model and ant K-means algorithm Ghea Sekar Palupi; Muhammad Noor Fakhruzzaman
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6132-6139

Abstract

We proposed an approach of retailer segmentation using a hybrid swarm intelligence algorithm and recency frequency monetary (RFM)-location model to develop a tailored marketing strategy for a pharmacy industry distribution company. We used sales data and plug it into MATLAB to implement ant clustering algorithm and K-means, then the results were analyzed using RFM-location model to calculate each clusters’ customer lifetime value (CLV). The algorithm generated 13 clusters of retailers based on provided data with a total of 1,138 retailers. Then, using RFM-location, some clusters were combined due to identical characteristics, the final clusters amounted to 8 clusters with unique characteristics. The findings can inform the decision-making process of the company, especially in prioritizing retailer segments and developing a tailored marketing strategy. We used a hybrid algorithm by leveraging the advantage of swarm intelligence and the power of K-means to cluster the retailers, then we further added value to the generated clusters by analyzing it using RFM-location model and CLV. However, location as a variable may not be relevant in smaller countries or developed countries, because the shipping cost may not be a problem.  
Co-Authors Aries Dwi Indriyanti Muhammad Noor Fakhruzzaman Thinni Nurul Rochmah