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Jurnal Informatika Terpadu
Published by STT Terpadu Nurul Fikri
ISSN : -     EISSN : 24608998     DOI : -
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Education
Jurnal Informatika Terpadu memuat jurnal ilmiah di bidang Ilmu Komputer, Sistem Informasi dan Teknik Informatika. Jurnal Informatika Terpadu diterbitkan oleh LPPM STT Nurul Fikri dengan periode dua kali dalam setahun, yakni pada bulan Maret dan September.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 10 Documents
 1 
Search results for , issue "Vol 11 No 2 (2025): September, 2025" : 10 Documents clear
Desain Web Dashboard Berbasis Pengguna: Menggunakan Design Thinking untuk Meningkatkan Pengelolaan Data Wahyudi, M. Ilham; Silmina, Esi Putri
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.1616

Abstract

This study aims to design a user-based web dashboard by applying the Design Thinking methodology to improve data management in organizations. In the digital era, effective data management is crucial for supporting informed decision-making. The Design Thinking method involves five stages: Empathize, Define, Ideate, Prototype, and Test, which focus on understanding user needs. Through interviews and observations, specific user needs were identified, creating a clear problem statement. Innovative ideas were then collected, and a dashboard prototype was developed using Figma. Testing was carried out to assess the effectiveness of the resulting solution. The results indicate that the designed dashboard can improve the ease of use and efficiency in data management. 80% of respondents felt that features such as graphs, tables, and bubble maps helped in data analysis, but some users had difficulty navigating and understanding these features. Therefore, this study recommends further development, such as adding user guides and interactive tutorials, to make the dashboard more user-friendly and relevant to user needs.
Deteksi Fraud Kartu Kredit dengan Logistic Regression, Random Forest, dan Gradient Boosting Irawan, Herlambang
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.1826

Abstract

This study aims to develop a credit card transaction fraud detection model using machine learning approaches, namely Logistic Regression, Random Forest, and Gradient Boosting Classifier. The dataset used is sourced from real credit card transactions with a fraud proportion of 0.17%, which reflects the problem of class imbalance. To overcome this, the Synthetic Minority Over-sampling Technique (SMOTE) and feature transformation using Principal Component Analysis (PCA) were applied. The evaluation was carried out using accuracy, precision, recall, F1-score, and ROC-AUC metrics. The results show that Random Forest and Gradient Boosting Classifier produced the best performance with near-perfect accuracy and ROC-AUC values (ROC-AUC > 0.999), while Logistic Regression gave very good results but slightly below the other two models. However, the near-perfect ROC-AUC value may indicate potential overfitting, requiring further validation on different datasets. Unlike previous studies that only used one algorithm, this study compared three models simultaneously and integrated SMOTE and PCA to improve detection performance. The practical implication of this study is that the proposed model can be implemented in digital financial systems to assist banking institutions in detecting fraud in real time and reducing potential financial losses.
Implementasi Sistem Pemesanan Hotel Menggunakan Algoritma Haversine untuk Optimalisasi Rekomendasi Lokasi Adhani, Hamka Lukmanul Hakim; Bianto, Mufti Ari; Pratama, Alif Nanda; Hidayah, Septina Alfiani
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2030

Abstract

A location-based lodging recommendation system helps users find nearby hotels efficiently through a web-based platform. The system utilizes the Haversine algorithm to calculate the distance between the user's location and the hotel by automatically retrieving coordinates via the Geolocation API. Calculated distances are compared with hotel data stored in a MySQL database, and the results are displayed on a web interface integrated with the Google Maps API. Testing was conducted on six hotels with distances ranging from 6.73 km to 23.97 km, and results were compared with Google Maps estimates. The system achieved an average distance difference of 0.0183 km, with an accuracy rate of 99.83%. These findings indicate that the Haversine algorithm provides highly accurate distance estimations and is reliable for location-based hotel recommendation systems.
Penerapan Metode Multi-Factor Evaluation Process dalam Keputusan Pemilihan Hewan Pemeliharaan untuk Anak Ghufriyyah, Shinta; Adelia, Tsania Shidqi; Muzid, Syafiul
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.1865

Abstract

The selection of suitable pets for children requires consideration of several criteria, including gentle temperament, care needs, safety, and social interaction. This study applies the Multi-Factor Evaluation Process (MFEP) method to recommend the most appropriate pets for children based on predefined criteria. MFEP is a decision-making technique that determines preference values by weighting each criterion and evaluating performance scores. A quantitative approach was employed with five pet alternatives and five evaluation criteria: safety, interaction level, care cost, ease of maintenance, and allergy potential. The evaluation results show that ornamental fish achieved the highest preference score of 0.92, followed by turtles with 0.87, indicating their suitability as ideal pets for children. These findings demonstrate that the MFEP method supports structured and objective decision-making in pet selection. Future studies are recommended to include additional criteria tailored to children’s specific needs, such as allergies or physical limitations.
Analisis Sentimen Ulasan Aplikasi Gojek Menggunakan Support Vector Machine Dan Random Forest Aditya, Azka Bima; Samsudin, Syafri; Rizki, Winahyu Pandu; Mahendra, Mahir; Setiawan, Arif
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.1884

Abstract

The rapid development of digital transportation, such as Gojek, requires a deep understanding of user satisfaction. This study analyzes the sentiment of Gojek application reviews to evaluate public opinion and compare the performance of the Support Vector Machine (SVM) and Random Forest models. A quantitative experimental method was applied to 30,055 user reviews for versions "4" and "5" from the Google Play Store. The data underwent comprehensive text preprocessing, automatic sentiment labeling using VADER enriched with an Indonesian lexicon, and TF-IDF feature extraction. The training data imbalance was addressed using SMOTE before the data was split for training and testing. The results show that user sentiment was dominated by positive (38.9%) and neutral (38.2%) categories. In the performance evaluation, the SVM model demonstrated superior performance with 96% accuracy and an F1-score of 0.96, outperforming the Random Forest model, which achieved 93% accuracy and an F1-score of 0.93. In conclusion, SVM is a more effective model for sentiment classification of Gojek reviews. Future research is recommended to refine the lexicon and implement aspect-based analysis to obtain more detailed insights.
Perancangan Prototype Sistem Monitoring Ternak Ruminansia dengan Metode Human Centered Design Putriana, Rena; Pradini, Risqy Siwi; Haris, M. Syauqi
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2553

Abstract

The ruminant livestock sector, such as sheep and cattle, makes a significant contribution to food security and the national economy. However, livestock data management, which is still carried out manually, remains a major challenge in improving operational efficiency, as seen in the Sarwa Adem Mulya (SAM) Cooperative. This study aims to design a prototype of a mobile-based livestock monitoring system called Ruminant Watch, using the Human-Centered Design (HCD) approach to align with the needs and limitations of field users. The research was conducted through five main stages: literature review, specification of the usage context, identification of user needs, design solution development using Figma, and usability evaluation through the System Usability Scale (SUS) questionnaire. The testing results showed an average SUS score of 87, which falls into the “Excellent” category. This indicates that the developed prototype system is not only easy to use but also relevant and effective in supporting livestock monitoring activities. This design is expected to serve as an initial step toward the digitalization of ruminant farming that is more efficient and adaptive to users’ capabilities.
Pendekatan Agile Software Development dalam Sistem Informasi Berbasis Web untuk Optimalisasi Manajemen Data Iklan Herawati, Afni Kurnia; Putri, Dwi Ismiyana
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2572

Abstract

Advertising data management in Emtek Digital's Open Marketplace (OMP) division continues to face such as fragmented documentation, the risk of data duplication, and limited transparency in real-time ad performance tracking. These issues reduce strategic effectiveness and slow down the decision-making process. This study aims to develop an integrated information system that can improve efficiency, accuracy, and transparency in advertising data management. Using the Agile Software Development method, a web-based system was designed to be adaptive to changing user needs and equipped with data automation, report validation, and user and partner management features. Testing was conducted using the Blackbox and User Acceptance Test (UAT) methods, obtaining an average score of 83.3% in the “Very Good” category. These results indicate that the developed system is feasible for implementation and capable of supporting fast and accurate data-driven decision-making. Unlike the previous non-integrated system, this research introduces innovations in integration and reporting process automation, thereby improving the efficiency and transparency of advertising data management.
Implementasi Strategi Instagram Marketing Berbasis Model AIDA untuk Optimalisasi Konten UMKM Kuliner Bayanussabil, Muhammad Syahid; Pramudiawardani, Shelly; Rusmanto, Rusmanto
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2689

Abstract

This study aims to design and implement an Instagram marketing strategy using the AIDA model (Attention, Interest, Desire, Action) to enhance consumer purchase interest for Mie Ayam Bakso Mas Dava, a micro, small, and medium enterprise (MSME). The research employs a qualitative descriptive method, collecting data through interviews, observations, and analysis of Instagram Insights. Data were analyzed using NVivo to identify themes aligned with the AIDA model, which was validated through triangulation. The results show that the strategy was successfully designed using AIDA-based Reels, Stories, and Feed content, achieving 5,171 views, 222 interactions, and 27 Linktree clicks, as recorded in Instagram Insights from April to May 2025. Reels were the most effective format, followed by Stories and Feed. The implementation increased purchase interest through aesthetic visuals and a clear call-to-action (CTA). However, limitations such as a low follower count (53) and geographical constraints suggest the need for increased Reels frequency and Instagram Ads. This study contributes to the development of digital marketing strategies for MSMEs.
Pengembangan Antarmuka Web Analitik Log Deteksi Intrusi Jaringan Berbasis Suricata Menggunakan Dash Berniawan, Nikita Putri; Saptono, Henry; Zaida, Efrizal
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

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

Abstract

The rapid growth of internet usage correlates with an increasing risk of network security threats. Attacks on network traffic may result in confidential data breaches and system disruptions. Suricata, a powerful Intrusion Detection System (IDS) tool, is used to generate rich detection logs. However, raw log data in JSON format remains difficult to analyze and interpret directly due to its complexity and large volume. This study proposes the development of a web-based application using the Dash framework to visualize intrusion detection results from Suricata. Dash is capable of presenting data in an interactive and informative manner through various components such as histograms, line charts, tables, and filter features. The purpose of this research is to assess Dash’s effectiveness in presenting intrusion data in a format that is accessible and easily interpreted by users. Evaluation results show that the Dash framework successfully visualized 24,526 alerts out of a total of 4,247,464 logs accurately. The application was also able to display all information components comprehensively and interactively. Thus, this application can contribute to improving both network security and operational efficiency.
Pengaruh Strategi Digital Marketing Tiktok Terhadap Peningkatan Penjualan Produk Yamara Fashion Santosa, Fadila Adelia Putri; Janah, Nurul; Mentari, Laisa Nurin
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2699

Abstract

TikTok has emerged as a dominant platform in digital marketing strategies, driven by its engaging short-form video content and algorithmic distribution tailored to user preferences. In Indonesia, TikTok reached 157.6 million users by July 2024, establishing itself as the fastest-growing social media platform in Southeast Asia and offering high potential for enhancing product visibility and sales, particularly for fashion businesses. Toko Yamara, a local enterprise specializing in fashion since 2020, actively utilizes TikTok for marketing; however, sales fluctuations observed from April to August 2024 highlight inconsistencies in its marketing approach. This study examines the impact of TikTok-based digital marketing strategies on sales performance at Toko Yamara, focusing on four key dimensions: accessibility, interactivity, entertainment, and informativeness, alongside engagement metrics—including likes, comments, shares, and saves—that reflect audience interaction. Employing an explanatory quantitative approach, the research involved 116 consumers exposed to Toko Yamara’s TikTok content, selected through purposive sampling. Data were collected using a Likert-scale questionnaire and analyzed through validity and reliability tests, simple linear regression, t-tests, and coefficient of determination. Results indicate a statistically significant influence of TikTok digital marketing on sales growth, with a coefficient of determination (R²) of 49.6%. These findings underscore the importance of optimizing informative and engaging content for small businesses to strengthen social media-based marketing efforts and provide empirical backing for consumer purchase decisions.

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