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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 1,011 Documents
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Market Basket Analysis for Determine Goods Layout Using FP-Growth Algorithm Alfitra, Domi; M. Afdal, M. Afdal; Fronita, Mona; Saputra, Eki
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4268

Abstract

The retail industry has undergone a significant transformation. Jumbo Mart is one of the retail businesses that consistently meet customer needs in Pekanbaru city. The number of similar businesses makes Jumbo Mart need to have a competitive advantage to compete. One of them is by improving the shopping experience, especially in the aspect of goods layout. However, based on observations and interviews, the determination of the layout of goods at Jumbo Mart is still not optimal. The number of products and variety of items sold is one of the reasons. In addition, customer transaction history has not been used further and is only stored as an archive of monthly reports. Whereas analyzing the data can be an effective solution in arranging the layout of goods based on customer behavior. Therefore, this research proposes a data mining technique with the FP-Growth algorithm to find association rules between categories of goods. The implementation results with a minimum support value of 15% and confidence of 50% get 7 association rules, but only 6 are proven valid. The valid association rules are then proposed to be placed close together so that it can make it easier for buyers to find the desired items. In addition, items with the consumption category are dominant as consequents, which can be found in the four association rules. This indicates that items with consumption categories have great appeal and are an important part of customers' shopping behavior and habits.
Comparison of the Performance of the VADER and RoBERTa Algorithms on Twitter Nurmadewi, Dita; Jailani, Zakul Fahmi; Manik, Ni Kadek Sri
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4198

Abstract

This research compares the performance of two sentiment analysis algorithms, namely VADER (Valence Aware Dictionary and Entiment Reasoner) and RoBERTa (Robustly Optimized BERT Pretraining Approach), using a dataset of public opinions regarding climate change on twitter. Analysis is carried out to determine the sentiment distribution of the tweets described, whether they are positive, negative or neutral. In addition, this research identifies the keywords that appear most frequently from the collection of tweets that have been analyzed. Time series analysis was also carried out to see the distribution of sentiment over 12 months. The relationship between the two models was evaluated using matrix scatter plot analysis for tweets per two months, to assess the correlation and consistency of sentiment results between VADER and RoBERTa. The results show that VADER is more effective in situations that require rapid responses to changes in public sentiment, while RoBERTa is superior in in-depth analysis of more complex and ambiguous content.
Systematic Review of Decentralized and Collaborative Computing Models in Cloud Architectures for Distributed Edge Computing Zangana, Hewa Majeed; Mohammed, Ayaz khalid; Zeebaree, Subhi R. M.
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4169

Abstract

This systematic review paper delves into the evolving landscape of cloud architectures for distributed edge computing, with a particular focus on decentralized and collaborative computing models. The aim of this systematic review is to synthesize recent advancements in decentralization techniques, collaborative scheduling, federated learning, and blockchain integration for edge computing. As edge computing becomes increasingly vital for supporting the Internet of Things (IoT) and other distributed systems, innovative strategies are needed to address challenges related to latency, resource management, and data security.The key findings highlight the benefits of latency-aware task management, autonomous serverless frameworks, and the collaborative sharing of computational resources. Additionally, the integration of federated learning and blockchain technologies offers promising solutions for enhancing data privacy and resource allocation. The versatility of edge computing is showcased through its applications in diverse domains, including healthcare and smart cities. Future research directions emphasize the need for optimized resource management, improved security protocols, standardization efforts, and application-specific innovations. By providing a comprehensive review of these developments, this paper underscores the critical role of decentralized and collaborative models in advancing the capabilities and efficiency of edge computing systems.
Greedy Algorithm to Support the Decision of Choosing the Fastest Aid Distribution Route After Flooding Harahap, Sukma Ananda; Triase, Triase
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4345

Abstract

Flooding is one of the most common natural disasters in Indonesia, including in Merbau Sub-district, North Labuhan Batu Regency, North Sumatra. This disaster can cause huge losses, both material and non-material. One of the efforts to reduce the impact of flooding is to immediately distribute aid to affected communities. The distribution of post-flood aid requires careful planning so that it can run quickly and on target. In this research, we propose the use of greedy algorithm to support the decision of choosing post-flood aid distribution route in Merbau District. The greedy algorithm is an algorithm that chooses the best solution at each step, hoping to find the optimal solution as a whole. This research was conducted using data on the location of disaster points, the location of aid distribution points, and the distance between points. The results showed that the greedy algorithm can produce a faster aid distribution route compared to the conventional route.
Implementation of Content Based Filtering Algorithm in Comic Recommendation System Alana, Reyhan; Hartanto, Adi
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.2944

Abstract

Currently, the interest of comic readers in Indonesia is increasing and has become a popular culture. With so many comics released each year, it makes it difficult for the readers to find comics that fulfill their criteria, therefore the recommendation system becomes a feature that is quite important and has a role in helping the readers. The data used is comic data totaling 1219 comics, with details of 471 physical comics published by Elex Media Komputindo publishers and 748 digital comics released on the Line Webtoon Indonesia platform. This research uses the Content Based Filtering algorithm because it only utilizes title and synopsis data from the comic. The Cosine Similarity method is used to calculate the similarity value of a comic data with the criteria that has been entered and can test the data 10 times until the system successfully gives suitable comic recommendations with an average precision score of 94.86%.
Sales Data Visualization to Determine Business Insight Using Metabase in a Global Retail Company Utomo, Fandy Setyo; Lubna, Zuhriyatul
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.3870

Abstract

In the era of dynamic business globalization, sales data analysis and visualization are key to strategic decision making. The application of Metabase as the main tool for visualization and analysis of sales data in the context of global retail companies, especially in the online sales sector. XYZ Company became the subject of research with complex challenges in managing extensive and diverse sales data. Metabase was adopted as a solution to deal with this complexity, enabling the company to gain deep insights into sales trends, consumer preferences, and hidden growth opportunities. Data visualization, through Metabase, plays a key role in transforming complex information into easy-to-understand visual representations, helping analysts and business stakeholders spot important patterns and trends. Research results reveal patterns of concurrent product purchases, providing opportunities to increase sales through promotions or product bundling. The identification of product categories that customers are interested in within a single transaction provides important insights for stock management and marketing strategies. Analysis of customer gender preferences opens up opportunities to direct more specific marketing strategies, focusing on the majority of a particular gender. The resulting recommendations include increased promotion or bundling of frequently purchased products together, as well as implementation of more focused marketing strategies based on product category preferences and customer gender. This article aims to contribute to the scientific literature on the practical application of data visualization in the context of sales analysis, with a focus on developing effective business decisions and marketing strategies.
Determining Customer Satisfaction Level to Determine Batik Business Development Using Naive Bayes Algorithm Arif, Mhd. Fakhrozi; Hasugian, Abdul Halim
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4283

Abstract

Batik is one of the cultural heritages that must be preserved and developed. every business actor must experience very tight competition conditions, namely in the batik clothing business. Customer satisfaction is a very important aspect to pay attention to in order to increase business profits. The purpose of this research is to make it easier for Batik Berjaya Labuhanbatu Utara to find out what are the factors that affect customer satisfaction for the future development of Batik Berjaya Labuhanbatu Utara's business, and to find out the rediction results by looking at the accuracy of Naïve Bayes so that Batik Berjaya Labuhanbatu Utara can meet customer satisfaction. This research uses the Naive Bayes Algorithm Method whose results can later facilitate batik business managers in making decisions and improving the quality of products and services provided to customers. By calculating the classification results using the Naive Bayes algorithm with a total of 132 data, as a manual calculation, 30 data are used, namely, 80% of the training data totaling 24, 20% of the test data totaling 6 obtained accuracy 83.33%, precision 100%, recall 75%, specifity 100% and f1-score 85.71. Using the Naive Bayes algorithm helps classification, data in the form of attributes and labels are held training data and test data, where training data labeling must be determined at the beginning in the form of categorical information, namely satisfied and dissatisfied, then predictions are made based on the highest data to get satisfied and dissatisfied labels from test data.
Implementation of Run Length Encoding (RLE) Algorithm on Text Data Compress using Python Siradjuddin, Hairil Kurniadi; Khairan, Amal; Albaar, Muhammad Ridha; Abdullah, Saiful Do
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4175

Abstract

Text data compression is done to make the file size smaller. Algorithm is a sequence of steps that aims to solve a problem. In this text data compress research using the Run Length Encoding (RLE) data compress method, it can be used to trim data to minimize the use of storage space so that it can be utilized better. As the function of the data compress itself to trim the file, its use is very beneficial for future technology. The programming applied is a python application, applying the concept of structured programming. Structured programming is a programming concept or paradigm that solves problems structurally, without looking at objects or divisions but must be structured, The result of this research is that the phyton application is able to trim text data so as to minimize the use of storage space so that it can be utilized better.
UI/UX Design of Waste Management Application Using Design Thinking Method Saraswati, Devy; Adnan, Fahrobby; Pandunata, Priza
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.2845

Abstract

Anyelir Waste Bank is one of the waste banks assisted by PLN's Jakarta Main Distribution Unit which is located in East Jakarta Regency. Ongoing activities are still carried out manually, resulting in various problems. Therefore, the role of technology is needed to overcome problems related to waste management through scientific media designing the fields of User Interface (UI) and User Experience (UX) by designing waste management applications using design thinking. Design thinking was chosen because it combines priorities based on user needs with appropriate technological capabilities and business needs. Application design is designed on a mobile platform for customers while management is on a website platform. This research produces solutions for application design and usability testing has been carried out. Usability testing according to the ISO 9241-11 standard includes aspects of effectiveness, efficiency and satisfaction. In carrying out usability testing to measure aspects of effectiveness and efficiency using task scenarios, while to measure aspects of satisfaction using System Usability Scale (SUS).
Application Rule Base on Facial Skin Type Identification Expert System using Forward Chaining Basir, Azhar; Tyas, Fitri Ayuning; Maghsyari, Yusril Ahzam
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4071

Abstract

Most people, especially women, have a great desire to have white, healthy, clean and well-maintained facial skin. However, their knowledge about facial skin types is still limited, even though consulting with an expert requires a lot of time and money which results in someone not paying attention to facial skin type when carrying out treatment. Therefore, an expert system is needed that can help identify facial skin types. A rule base is a rule created based on expert knowledge needed to create an expert system. The forward chaining method is a search method or forward tracing technique that starts from existing information and combines rules to produce a conclusion or goal. The research results show that this application can run well and is suitable for use. Based on the results of system testing from an expert, it was concluded that identifying facial skin types based on facial skin criteria using the forward chaining method had an accuracy rate of 84% where the results of system testing produced several conclusions about the appropriate type of facial skin with the selected criteria data.

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