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All Journal Journal of Information Systems and Informatics Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Ifrah Ayyuna
Universitas Islam Negeri Sumatera Utara
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Rancang Bangun Aplikasi Pesan Tiket Online Swim Course Medan Berbasis Android Ifrah Ayyuna; Nur Nadilla; Anggita Dwi Inayah
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3256

Abstract

The development of information and communication technology has brought changes in various aspects of life, including purchasing tickets. Currently, many tourist and entertainment attractions provide online ticket purchasing services to make it easier for visitors. This can also be applied to swimming pools, where visitors can buy swimming tickets online via the application. The online swimming ticket application offers several benefits for visitors and swimming pool managers. Visitors can buy tickets easily and at any time, without having to queue at the ticket purchase counter. Apart from that, this application can also provide information about ticket availability, swimming pool opening hours and ongoing promotions. For swimming pool managers, this application can help increase ticket sales efficiency.
Implementation of the Collaborative Filtering Method for a Clothing Sales Recommendation System in Fashion Store Ifrah Ayyuna; Triase Triase
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1368

Abstract

The rapid growth of e-commerce has made personalized product recommendations a crucial aspect of enhancing customer satisfaction and boosting sales. However, many small-to-medium-sized retail businesses, like Adiva Fashion Store, still rely on manual product selection through customer searches or seller recommendations, which often leads to challenges in meeting customer preferences. This study presents a case study of Adiva Fashion Store, where the Collaborative Filtering method was implemented to develop a personalized clothing product recommendation system. The item-based Collaborative Filtering approach was employed to calculate the similarity between products based on customer ratings and transaction history. These similarity values were then used to predict customer preferences for products that had not yet been purchased. The system was developed using the Waterfall methodology, which involved needs analysis, system design, implementation, testing, and maintenance. The results show that the recommendation system significantly improved the relevance of product suggestions, helping customers make better purchasing decisions and increasing sales effectiveness. This case study illustrates how data-driven recommendation systems can be effectively integrated into small-to-medium-sized retail environments, providing valuable insights for other businesses aiming to adopt similar strategies.
Co-Authors Anggita Dwi Inayah Nur Nadilla Triase Triase