Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : CSRID

User Satisfaction Analysis Of Tourist Ticket Applications Using The Heuristic Evaluation Evaluation Method (Case Study: Pagubugan Melung Tour Manager) Evania Adna; Tahyudin, Imam
Computer Science Research and Its Development Journal Vol. 16 No. 3 (2024): October 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of digital technology has changed the way information is interacted with and managed, including in the tourism sector. Nature tourism, as an important part of Indonesia's tourism industry, has also undergone a significant transformation in terms of technology use. This research investigates the application of information technology through websites in improving the accessibility, efficiency, management, and promotion of Pagubugan Melung Tourism in Banyumas. By adopting a website-based ticketing application, Wisata Pagubugan Melung is able to provide more complete and interactive information for visitors and simplify the process of ticket sales and visitor management. Evaluation of user acceptance of the ticketing application was conducted using the Heuristic Evaluation method and Partial Least Square Equation Model (PLS-SEM) statistical analysis. The variables that become indicators in evaluating user acceptance of ticketing applications using PLS-SEM statistical analysis are Visibility of System Status, Match Between System and the Real World, User Control and Freedom, Consistency and Standards, Error Prevention, Recognition Rather Than Recall, Flexibility and Efficient of Use, Aesthetic and Minimalist Design, Help Users Recognize, Diagnose, and Recover from Errors, Help and Documentation and Usability. The results showed that most features were well received by users. Overall, the Wisata Pagubugan Melung ticketing app is popular, showcasing the blend of technology and tourism. This research provides a better understanding of user acceptance of technological innovations in the context of tourism and provides guidance for further development in improving technology-based tourism services.
User Satisfaction Analysis Of Tourist Ticket Applications Using The Heuristic Evaluation Evaluation Method (Case Study: Pagubugan Melung Tour Manager) Evania Adna; Tahyudin, Imam
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 3 (2024): October 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.16.3.2024.259-272

Abstract

The development of digital technology has changed the way information is interacted with and managed, including in the tourism sector. Nature tourism, as an important part of Indonesia's tourism industry, has also undergone a significant transformation in terms of technology use. This research investigates the application of information technology through websites in improving the accessibility, efficiency, management, and promotion of Pagubugan Melung Tourism in Banyumas. By adopting a website-based ticketing application, Wisata Pagubugan Melung is able to provide more complete and interactive information for visitors and simplify the process of ticket sales and visitor management. Evaluation of user acceptance of the ticketing application was conducted using the Heuristic Evaluation method and Partial Least Square Equation Model (PLS-SEM) statistical analysis. The variables that become indicators in evaluating user acceptance of ticketing applications using PLS-SEM statistical analysis are Visibility of System Status, Match Between System and the Real World, User Control and Freedom, Consistency and Standards, Error Prevention, Recognition Rather Than Recall, Flexibility and Efficient of Use, Aesthetic and Minimalist Design, Help Users Recognize, Diagnose, and Recover from Errors, Help and Documentation and Usability. The results showed that most features were well received by users. Overall, the Wisata Pagubugan Melung ticketing app is popular, showcasing the blend of technology and tourism. This research provides a better understanding of user acceptance of technological innovations in the context of tourism and provides guidance for further development in improving technology-based tourism services.
Penerapan Teknik Heuristik untuk Meningkatkan Rekomendasi Produk dari Data Transaksi di Toko Jaffamart Menggunakan Query SQL Al-Haq, Ahnaf Vanning Al-Haq; Tahyudin, Imam
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.50-70

Abstract

In the midst of increasingly fierce competition in the retail business, companies need to implement effective promotional strategies to boost sales and attract customer interest in the various products they offer. Jaffamart, as a provider of daily necessities, possesses valuable transaction data with great potential to be developed into a product recommendation system. This study aims to build a product recommendation system based on purchase frequency while analyzing the comparative effectiveness of two types of SQL queries, namely Cartesian Product and JOIN, in the process of retrieving recommendation data after being optimized using heuristic techniques. The methods applied include transaction data analysis over a specific period, database design, implementation of SQL queries with two different methods, and the application of heuristic techniques to filter relevant data and improve query execution speed. The research findings indicate that the JOIN query consistently delivers faster and more efficient execution times compared to Cartesian Product, especially when handling large volumes of data. Furthermore, the product recommendation results over a 2-month period identified products with the highest purchase frequencies, such as Energen Sereal Cokelat 29gr, Kapal Api Mix, and Susu Jahe Sidomuncul, which are suitable to be prioritized in promotional programs. The implementation of heuristic techniques has proven effective in enhancing query performance and generating more accurate and relevant product recommendations in accordance with current conditions. These findings contribute to the development of recommendation systems and efficient transaction data management strategies for the retail business sector.
Application Of Market Basket Analysis For Sales Transaction Analysis Using Association FP-Growth Algorithm Wini Audiana; Tahyudin, Imam
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.33-49

Abstract

In an increasingly competitive business world, leveraging transaction data has become crucial for understanding consumer behavior and designing effective marketing strategies. This study aims to apply the FP-Growth algorithm in Market Basket Analysis (MBA) to identify consumer purchase patterns at KS Swalayan. The data analyzed in this research was taken from sales transactions that occurred during October 2024, with key attributes including product codes, product names, quantity, unit price, total price, and discounts. This research follows the Knowledge Discovery in Databases (KDD) framework, which includes stages of data selection, data cleaning, transformation, pattern collection, and result evaluation. The research findings indicate that the FP-Growth algorithm successfully identified significant associative relationships between various products. For example, there is a relationship between the products "Snack and Roti" and "Susu," which shows a lift value of 1.414861701, indicating a strong correlation between them. These findings provide the basis for marketing strategy recommendations such as product bundling, optimizing shelf layouts, and more efficient stock management. Additionally, the results of this study have the potential to improve consumer shopping experiences by offering products that are frequently bought together. Overall, this study highlights the effectiveness of the FP-Growth algorithm in uncovering consumer purchase patterns, which can support data-driven decision-making and improve marketing strategy efficiency in the retail sector. The implementation of this technique can serve as a valuable tool for store managers to enhance their competitiveness and business performance.
Analisis Pola Penjualan Produk Ritel Menggunakan Algoritma Apriori di Toko Reika Zulfa Ummu Hani; Tahyudin, Imam
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.71-92

Abstract

This research aims to analyze product purchasing patterns at Toko Reika by utilizing the Apriori algorithm as a data mining method. The analysis process is conducted through a series of stages in Knowledge Discovery in Database (KDD), which includes data selection, cleaning, transformation, analysis, and evaluation. The results of this study successfully identified 36 association rules from the analyzed transactions, illustrating various combinations of related products. One of the most striking findings is the rule with the highest lift value, which is the combination of Basic Needs, Food Supplements, and Food Ingredients, with a lift value of 8.7. This indicates that these three products have a very strong correlation in consumer transactions. Additionally, the combination of Snacks, Basic Needs, and Food Ingredients also stands out, with a confidence value reaching 76%. This suggests that consumers who purchase one product from this combination are highly likely to purchase the other products as well. The analysis also reveals significant purchasing patterns within certain categories, such as Skincare, Food Supplements, and Bathing Supplies, which show high lift values and meaningful relationships between products in a single transaction. The insights gained from this research can be utilized to design data-driven marketing strategies, such as bundling promotions, product arrangement, and more effective stock management. It is hoped that these findings can help retail stores improve operational efficiency, maximize sales, and provide a better shopping experience for consumers.
Co-Authors Agustina, Nur Ngaenun Al-Haq, Ahnaf Vanning Al-Haq Alam, Yusuf Nur Alfirnanda, Weersa Talta Ammar Fauzan, Ammar Ananda, Fahesta Ananda, Rona Sepri Andrianto Andrianto Anggraini, Lintang Wahyu ANNISA HANDAYANI Anton Satria Prabuwono Arifa, Pujana Nisya Aris Munandar Azhari Shouni Barkah Bayu Surarso Berlilana Berlilana Che Pee, Ahmad Naim Daffa, Nauffal Ammar Dani Arifudin Dhanar Intan Surya Saputra Diniyati, Faoziyah Fahiya Eko Priyanto Eko Winarto Evania Adna Faiz Ichsan Jaya Fajariyanti, Alya Nur Fandy Setyo Utomo Fatmawati, Karlina Diah Febryanto, Bagas Aji Fitriani, Intan Indri Giat Karyono Hadie, Agus Nur Hellik Hermawan Hermanto, Aldy Agil Hidayah, Septi Oktaviani Nur Ilham, Rifqi Arifin Irfan Santiko Iskoko, Angga Isnaini, Khairunnisak Nur Khoerida, Nur Isnaeni khusnul khotimah Kuat Indartono Kusuma, Bagus Adhi Lestari, Silvia Windri Ma'arifah, Windiya Maulida, Trisna Melia Dianingrum Miftahus Surur, Miftahus Muhammad Reza Pahlevi Murtiyoso Murtiyoso Musyafa, Muhamad Fahmi Nabila, Putri Isma Najibulloh, Imam Kharits Nanjar, Agi Nazwan, Nazwan Nur Adiya, Az Zahra Dwi Nur Faizah Nur holifah, Anggita Oyabu, Takashi Prasetya, Subani Charis Prastyo, Priyo Agung PUJI LESTARI Purwadi Purwadi Purwadi Purwadi Putra, Bernardus Septian Cahya Putra, Feishal Azriel Arya R Rizal Isnanto Rahayu, Dania Gusmi Rahma, Felinda Aprilia Ramadani, Nevita Cahaya Rizaqi, Hanif Rozak, Rofik Abdul Rozak, Rofiq 'Abdul Rozak, Rofiq Abdul Rozak, Rofiq ‘Abdul Rozaq, Hasri Akbar Awal Saefullah, Ufu Samsul Arifin Santoso, Bagus Budi Sarmini Sarmini Satriani, Laela Jati Setiabudi, Rizki Sholikhatin, Siti Alvi Syafaat, Alif Yahya Syafiq, Bayu Ibnu Taqwa Hariguna Tikaningsih, Ades Tri Retnaningsih Soeprobowati Triana, Latifah Adi Triawan, Puas Wardani, Syafa Wajahtu Widiawati, Neta Tri Widya Cholid Wahyudin Wini Audiana Wulandari, Hendita Ayu Yarsasi, Sri Zainal Arifin Hasibuan Zulfa Ummu Hani Zumaroh, Agnis Nur Afa