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INDONESIA
Saturnus: Jurnal Teknologi dan Sistem Informasi
ISSN : 30319935     EISSN : 30319943     DOI : 10.61132
Core Subject : Science,
Saturnus : Jurnal Teknologi dan Sistem Informasi memuat naskah hasil-hasil penelitian di bidang Teknologi, dan Sistem Informasi
Articles 122 Documents
Analisis Prediksi Penjualan Bisnis Retail Menggunakan Metode Decision Tree dan Random Forest Agung Narayana Adhi Putra; I Wayan Sudiarsa; I Kadek Adi Gunawan; Kadek Bagus Karunia Dwi Dharmayasa; I Wayan Eka Saputra
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1409

Abstract

The retail industry generates an extremely large and continuously growing volume of transactional data along with the advancement of digital technology, thereby requiring sophisticated and systematic data analysis approaches to support effective and evidence-based business decision-making. This study aims to analyze retail sales data by utilizing the Retail Sales Dataset obtained from the Kaggle platform, which consists of 100,000 transaction records and broadly represents the characteristics of retail transactions. The main focus of this study is to classify product categories and predict customer segments, including the identification of high-spending customers (high spenders), based on demographic attributes such as age and gender, as well as various transaction-related features. The research methodology includes data preprocessing, label encoding, and feature engineering to generate additional variables, including Age_Group, Is_Holiday, and Spender_Group, which are expected to enhance the predictive capability of the models. Several machine learning algorithms, namely Decision Tree, Random Forest, and XGBoost, were implemented and evaluated to compare their respective performance. The experimental results indicate that multiclass product category classification achieves relatively low accuracy, ranging from 27% to 34%. These findings suggest the high complexity of retail data and highlight the need for further model optimization, class balancing techniques, and feature refinement to improve predictive performance in future studies.
Implementasi Jaringan Syaraf Tiruan dalam Peramalan Harga Cpo Menggunakan Backpropagation Eva Andini; Lailan Sofinah Harahap; Siti Nurjanah
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1410

Abstract

This study examines the development of a Crude Palm Oil (CPO) price forecasting model using an artificial neural network algorithm, specifically the backpropagation algorithm. As one of Indonesia’s main export commodities, CPO has a significant economic impact and influences the income of oil palm farmers. The CPO price data used in this study were obtained from CIF Rotterdam, covering the period from January 2019 to December 2023. The research methodology consists of several stages, including data collection, preprocessing, model design, and model implementation using Python programming. The training results of the backpropagation algorithm show an error value of 0.537829578 after 1,000 epochs, while the evaluation using Mean Squared Error (MSE) indicates an MSE of 0.022709 during the training process and 0.017604 during the testing process. The model also produces CPO price predictions for the next three months, namely 932.578 for the first month, 949.568 for the second month, and 774.855 for the third month. These findings indicate that the developed model is capable of predicting future CPO prices with adequate accuracy, which can assist companies in making better financial decisions and managing risks associated with CPO price fluctuations.
Peran Media Digital dalam Menyatukan Pandangan Masyarakat dan Pemerintah untuk Mewujudkan Smart City Medan Rio Irawan Munthe; Putri Nabila; Dermawan Wijaya Harahap; Ahmad Tamrin Sikumbang
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1413

Abstract

Digital media is currently the main key to public communication to convey aspirations in government policies. Medan is also one of the major cities in Indonesia that is striving to realize the concept of a smart city through digital media. The role of digital media is very important in realizing a smart city. This study aims to analyze how digital media plays a role in uniting the views of the community and the Medan city government in the effort to realize a smart city in Medan. The method used in this study is a qualitative descriptive approach with a library research approach and observation of digital communication activities, online news, and public statements from the government to the public in Medan. In realizing a smart city, optimizing digital communication is essential to strengthen the synergy between the community and the government. The results of the study indicate that digital media plays a crucial role as a means of two-way communication, information dissemination, and as a medium for public participation. However, challenges such as weak digital literacy and limited infrastructure are obstacles to the sustainability of this effort.
Perancangan Website Pelayanan Klien dan Pra-Pendaftaran Perkara di Kantor Hukum Kofipindo Cici Pratiwi; Zaskia Maghfira
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1293

Abstract

This research aims to design and build a client service website and pre-registration of cases at the KOFIPINDO Law Office as a solution to administrative problems that are still carried out manually. The system is developed using the waterfall method through the stages of needs analysis, system design, coding, testing, and maintenance. The website that was built provides features for account registration, filling in case data, uploading supporting documents, and verification by the admin so that the file is ready to be submitted to the e-Court system. In addition, the system is equipped with a case status monitoring dashboard, automatic notifications to clients, and submission history that can be accessed at any time. The results of the study show that this platform is able to improve service efficiency, minimize administrative errors, and speed up the pre-registration process of cases. The implementation of this system also helps to increase the transparency of communication between law firms and clients. Furthermore, the use of this website has the potential to reduce the administrative workload of staff, optimize the management of case data, and improve the accuracy of legal documentation. The system is also designed with the client's data security and privacy aspects in mind in accordance with the principles of digital information protection. Thus, this system can be an effective, structured, and integrated digital means to support the modernization of legal services at KOFIPINDO, improve service professionalism, and strengthen the competitiveness of law offices in the digital ecosystem.
Analisis Pola Aktivitas Belajar Mahasiswa pada Learning Management System Menggunakan Teknik Clustering Nurfaizah Nurfaizah
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1365

Abstract

The increasing use of Learning Management Systems (LMS) in higher education generates large amounts of student activity data that have the potential to provide deeper insights into learning processes. However, in practice, these data are still rarely analyzed systematically to understand variations in students’ learning activity patterns, limiting their practical use in supporting teaching and learning. This study aims to explore students’ learning activity patterns in an LMS using a clustering approach based on activity data.This research utilizes the publicly available Open University Learning Analytics Dataset (OULAD), focusing on a single course and a single academic term. LMS activity data were processed through data cleaning and feature extraction, followed by student clustering using the K-Means algorithm. The quality of the clustering results was evaluated using the Silhouette Score, and visual analysis was applied to support the interpretation of the results.The results indicate that students’ learning activities can be grouped into two main patterns, namely a group of students with high learning activity and a group with lower or moderate activity levels. These findings highlight the existence of heterogeneous learning behaviors among students, even within the same learning context.The identified learning activity patterns provide an initial foundation for utilizing LMS data to monitor student engagement and to support the development of more responsive, data-driven learning approaches in higher education.
Perancangan Enterprise Architecture Absensi SMK Swasta Dwitunggal 2 Tanjung Morawa Menggunakan TOGAF ADM Laila Azizah; Indah Dwi Pancari; Afini Tri Agustina; Ajeng Triandari; Hamza Dwi Aulia Warhana
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1418

Abstract

The attendance process at SMK Swasta Dwitunggal 2 Tanjung Morawa is still carried out manually, potentially causing inefficiency, delays, and inaccuracies in attendance data. This condition results in the difficulty of managing attendance data and less than optimal support for managerial decision-making in the school environment. This study aims to design an Enterprise Architecture (EA) for a school attendance system using the TOGAF Architecture Development Method (ADM) framework. The research method used is a qualitative approach with a case study design. The analysis is carried out through mapping existing conditions (AS-IS) and designing expected conditions (TO-BE) in several TOGAF ADM phases, including business architecture, information system architecture, technology architecture, as well as the Opportunities and Solutions and Migration Planning phases. The results of the study are an enterprise architecture blueprint and a migration roadmap that can serve as guidelines for the gradual implementation of a technology based attendance system. This design is expected to improve the efficiency of attendance management, data accuracy, and support the decision-making process in schools.
Dampak Kualitas Informasi dan Sistem Aplikasi Shopee Partner terhadap Kinerja Kurir di Kota Medan Indah Dwi Pancari; Muhammad Irwan Padli Nasution
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1419

Abstract

The development of information technology has significantly improved the efficiency of application-based delivery services, including Shopee Partner Driver couriers. However, several issues such as delays in information updates, system errors, and inaccurate delivery data still affect courier performance. This study aims to analyze the effect of Information Quality and System Quality on the Performance of Shopee Partner Driver Couriers in Medan City. This research used a quantitative method with a questionnaire survey distributed to 100 active couriers. The instrument applied a fivepoint Likert scale, and data were analyzed using validity and reliability tests, descriptive statistics, and multiple linear regression analysis with SPSS software. The results indicate that both Information Quality and System Quality have a positive and significant effect on Courier Performance. The coefficient of determination (R²) of 0.625 shows that these two variables explain 62.5% of courier performance variance, while the remaining 37.5% is influenced by other factors. These findings support the DeLone and McLean (2003) model of information system success, emphasizing the importance of system and information quality in enhancing user performance.
Design Of A Transaction Data Security System In A Bouqet Sales Application Using An Aes Algorithm Ibnu Rusydi; Laila Ali Putri; Maria Ulfa
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1422

Abstract

This research presents the development of a transaction data protection mechanism for a bouquet sales application by utilizing the Advanced Encryption Standard (AES) algorithm. The rapid growth of digital commerce has led to an increase in online transactions, which in turn raises serious concerns regarding the security of sensitive transaction data. Information such as customer identities, order details, delivery addresses, and payment data are vulnerable to unauthorized access, data leakage, and manipulation if not properly secured. To address these issues, this study applies the AES-128 encryption algorithm using a 128-bit secret key to secure transaction data before it is stored in the system database. The encryption process follows the standard AES workflow, including key expansion, initial transformation, multiple encryption rounds, and a final transformation stage. Decryption is restricted exclusively to authorized users who possess the correct encryption key. The research methodology includes system analysis, AES integration into the application, and functional testing of the encryption and decryption processes. Data integrity is validated by comparing the original plaintext with the decrypted output, while system performance is evaluated based on processing time and decryption accuracy. Experimental results indicate that the average encryption and decryption time remains under 10 milliseconds per transaction, without affecting system performance. The findings confirm that AES-128 effectively enhances transaction data confidentiality and integrity in the bouquet sales application
Analisis Klasifikasi Keputusan Belanja Konsumen Pada Toko Online XX Menggunakan Algoritma Decision Tree Putri Maria Theresia Kehi; I Wayan Sudiarsa; Maria Oktaviani Suryati; Yosefina Dehadi; Maria Karlinda
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1436

Abstract

This study aims to analyze consumer purchasing behavior on e-commerce platforms using the Decision Tree algorithm as an easily interpretable classification method. The dataset used consists of 12,330 transaction records with 18 attributes representing visitor characteristics and user activities during interactions with the e-commerce platform. The research stages include data exploration to identify initial patterns, data preprocessing to handle missing values and class imbalance, splitting the data into training and testing sets, training the Decision Tree model, evaluating model performance, and visualizing the tree structure to analyze decision rules.The test results show that the Decision Tree model with a maximum depth of 3 achieves fairly good performance, with an average accuracy of 89.78%, precision of 69.82%, recall of 59.95%, and an F1-score of 64.51% for the buyer class. The visualization of the decision tree provides clear interpretation of the main attributes influencing purchasing decisions, thereby facilitating understanding for non-technical decision makers. Overall, this study demonstrates that the Decision Tree method is effective in modeling consumer purchasing behavior in e-commerce and can be utilized as a basis for data-driven business decision making, particularly in marketing strategies and improving sales conversion rates.
Sistem Informasi Sederhana untuk Identifikasi Gen Penyebab Penyakit Putri Ramadani; Nur Aisyah Pandia; Salsabila Putri Hati Siregar; Sulindawaty Sulindawaty
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 4 No. 1 (2026): Januari : Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v4i1.1444

Abstract

The development of bioinformatics has led to the availability of large amounts of genetic data through public databases such as NCBI Gene, OMIM, and Ensembl. However, the complexity of data presentation and the dominance of English language hinder students, novice researchers, and the general public in understanding the relationship between genes and disease. This research aims to develop a simple web-based information system to identify disease-causing genes with concise, Indonesian-language, and user-friendly information presentation. The method used is Research and Development (R&D), which includes literature study, needs analysis, system design, implementation, testing, and evaluation. The system was developed using a MySQL relational database with a web interface that displays basic gene information, chromosome location, biological function, and gene-disease relationships, complete with simple visualizations. Black Box testing results indicate that all main functions run according to user requirements. This system is expected to improve bioinformatics literacy and become an effective learning medium.

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