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CSRID
Published by Universitas Potensi Utama
ISSN : 20851367     EISSN : 2460870X     DOI : https://doi.org/10.22303/csrid
Core Subject : Science,
Computer Science & IT
CSRID (Computer Science Research and Its Development Journal) is a scientific journal published by LPPM Universitas Potensi Utama in collaboration with professional computer science associations, Indonesian Computer Electronics and Instrumentation Support Society (IndoCEISS) and CORIS (Cooperation Research Inter University).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 126 Documents
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Digital Marketing Strategy as a Promotional Effort Purwokerto Speciality Food CV. Eka Sari Rafian Tri Akso; Fiby Nur Afiana; Gustin Setyaningsih
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-.16.3.2024.286-298

Abstract

In the context of digital marketing, which is increasingly important in the digital era, this research focuses on analyzing the digital promotion strategies implemented by CV. Eka Sari, a distributor of specialty food products in Purwokerto . The main objective is to evaluate the effectiveness of digital strategies in creating product differentiation and reaching a wider market. Using SWOT analysis method, business canvas model, and Porter's Five Forces, this research identifies the strengths, weaknesses, opportunities, and threats faced by CV. Eka Sari, as well as factors that affect competition in the market. The results show that CV. Eka Sari effectively utilizes digital marketing strategies, especially through social media, to strengthen brand awareness and attract the interest of the target market which includes students, productive employees, and families. Unique product differentiation and modern concepts have increased market share and strengthened their market position in the specialty food industry. The findings offer valuable insights for other specialty food product distributors in developing effective digital promotion strategies in the face of intensifying competition in the market.
Plagiarism Detection System Level of Similiarity of Title Thesis Using the Winnowing Algorithm (Case Study: Information Systems Study Program) Ginting, Riah Ukur; Purba, Adelina; Situmorang, Harold; Rahmad, Iwan Fitrianto
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-.16.3.2024.316-329

Abstract

The Winnowing Algorithm is a system built to determine the similarity of the title of a proposed thesis with previously existing thesis titles, so it is necessary to apply an algorithm to determine the similarity of titles. One of the algorithms for determining the similarity of titles is the Winnowing algorithm. The Winnowing algorithm is a method used to detect similar words/sentences (common subsequence) in two thesis titles being compared. Two thesis titles are known to have the same words / sentences if a fingerprint is found in the document, this fingerprint will be used as a basis for comparison between thesis titles, this algorithm will look for fingerprints (similarities in the two thesis titles) by changing the n-gram of the title into the form The number value is called a hash value, the technique for finding this value is hashing. The research results show that the winnowing algorithm is proven to be effective in detecting similarities in thesis titles in information systems study programs with a threshold of 10%. The system built is able to provide accurate and fast results in identifying similarities in thesis titles, and this system really helps students in finding topics that are original and have never been researched before. Apart from that, the supervisor can easily verify the similarity of the thesis title to avoid plagiarism.
Penerapan Next.js dan GraphQL dalam Pengembangan Mobile Web Sistem Informasi Manajemen Puskesmas Dwi Aulia Anugerah; Kosasi, Sandy
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-.16.3.2024.247-258

Abstract

This research focuses on the development of a Mobile Web-based Puskesmas Management Information System (SIMPUS) motivated by the need for the Puskesmas Rawat Inap Jungkat to improve information services and data management. The problem being faced by the Puskesmas Rawat Inap Jungkat is that the management of patient data visiting the health center is still manual and is done repeatedly, which results in the efficiency and effectiveness of services being hampered and data redundancy. SIMPUS mobile web development applies Next.js for the front-end and Laravel for the back-end, with GraphQL as the data retrieval protocol. This system is designed to simplify the patient registration process, polyclinic data management from registered patients, and efficient service management. This research uses the Design Science Research (DSR) method with data collection techniques in the form of observations, interviews, and documentation studies to develop a mobile web information system and puskesmas management that focuses on patient registration until the patient's data that registers directly enters the intended polyclinic. The System Modeling with Unified Modeling Language (UML) with White-Box testing to ensure system functionality. The results of the study are expected to make a positive contribution in improving the quality of health services at the Puskesmas Rawat Inap Jungkat, increasing operational efficiency and effectiveness, and facilitating access to information for patients and health center staff.
Analisis Model Keputusan Dengan Metode TOPSIS untuk Menilai Kualitas Air Minum Isi Ulang Sinaga, Mikha Dayan; Hardiyanti, Yeni; Sembiring, Nita; Haryanto, Edy Victor; Nababan, Labuan; Sianturi, Charles Jhony Mantho
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-.17.1.2025.20-32

Abstract

Water is one of the basic needs for every living thing, including humans. About three-quarters of our body consists of water and no one can survive more than 4-5 days without drinking water. Drinking water with clean quality is very important for the human body, because if the water drunk is not clean water, it will cause various diseases in the human body. Quality drinking water is very important for water depot businesses as one of the attractions in product marketing, if wrong in determining the quality of water, it will have an impact on decreasing marketing and sales of the business, so that business profits are not optimal. The problem that many drinking water depot business actors face today is the difficulty of determining suppliers of quality drinking water providers based on detection of drinking water quality so that the water produced is in accordance with health standards. The TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) is one of the decision-making techniques that can be used to evaluate various alternatives based on predetermined criteria. The results of the study showed significant variations in the quality of refill drinking water among the samples tested. Based on the calculation using the TOPSIS method, Supplier A obtained the highest ranking with a preference score of 0.61493219, while Supplier 5 had the lowest ranking with a score of 0.16023232. This study emphasizes the importance of selecting a quality water provider and the need for stricter supervision from the government. The results of the study are expected to provide useful information for consumers and refill drinking water providers, as well as become a basis for further research in the field of water quality.
Rancang Bangun Game Edukasi Eksplorasi Wisata dan Budaya Tasikmalaya Anwar, Dede Syahrul; Mufizar, Teuku; Shafarulloh, M. Hisyam; Maulana, Akmal
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-.17.1.2025.127-135

Abstract

Tasikmalaya, a region rich in tourism and cultural diversity, is still not widely recognized by the public. In the digital era, interactive media such as games can serve as an effective tool to introduce and promote its potential. This research focuses on designing and developing an educational adventure game that explores the tourism and cultural aspects of Tasikmalaya. The novelty of this study lies in its interactive and educational approach, specifically designed to educate users, particularly the younger generation, about Tasikmalaya's tourist attractions and cultural heritage. By utilizing game technology, it is expected to provide an engaging and informative learning experience.The research method used is the Multimedia Development Life Cycle (MDLC). The concept stage involves identifying the game's needs and objectives. The design stage includes story development, character creation, and user interface design. The material collection stage focuses on gathering necessary information and media assets. The assembly stage involves the technical development of the game. Testing is conducted to ensure the game's quality and functionality, while the distribution stage delivers the game to users.The final result of this research is an educational game aimed at enhancing public knowledge and appreciation of Tasikmalaya's tourism and culture, while also contributing to scientific development through research publication.
Pengembangan Virtual Assistant (Chatbot) Bebrbasis NLP (Natural Language Processing) Untuk Portal Informasi Terpadu Pariwisata Tasikmalaya Hidayat, Cepi Rahmat; Sumaryana, Yusuf; Syahrul Anwar, Dede; Fadilah, Ai Linda Nurahmah; Saputra, Muhammad Randika
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-.17.1.2025.136-148

Abstract

Tasikmalaya, known for its natural beauty and cultural richness, has great potential as an attractive tourist destination. One of the main challenges faced is how to convey accurate and integrated information to tourists quickly and easily so that it can be used to improve marketing strategies and destination development. This study aims to develop a virtual assistant (chatbot) based on Natural Language Processing (NLP) for the integrated Tasikmalaya tourism information portal in handling high volumes of questions simultaneously, reducing the workload of human staff and optimizing the service process. The research method uses a waterfall model by applying the NLP approach. The final result of this study is to produce a virtual assistant (chatbot) application that allows users to get information related to Tasikmalaya tourism destinations in a more flexible way. The application was tested using the black box method and showed that the application ran as expected while the SUS test carried out obtained a final score of 72.30 in the Good category.
Penerapan Algoritma FP-Growth Untuk Menentukan Pola Penjualan Najah Mart Serli, Serli; Saputro, Rujianto Eko
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-.17.1.2025.1-19

Abstract

This research aims to apply the FP-Growth algorithm at Najah Mart with a focus on identifying significant sales patterns. By recognizing products that are frequently purchased together, this study is expected to help Najah Mart optimize inventory management, enhance customer shopping experiences, and design more efficient marketing strategies. The methodology employed in this study includes collecting sales transaction data and preprocessing to ensure optimal data quality. Subsequently, the FP-Growth algorithm is applied to uncover patterns and associations within the sales data. The analysis focuses on identifying strong product correlations based on customer purchasing patterns. The research findings reveal relevant and significant purchasing patterns, such as combinations of specific products frequently bought together. These insights can be utilized to improve marketing strategies and inventory management. This study not only provides practical benefits for Najah Mart in enhancing operational effectiveness and supporting strategic decision-making but also contributes to the advancement of knowledge by expanding the application of the FP-Growth algorithm in the retail sector, particularly in sales data analysis to support business growth.
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.

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