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Wawan Gunawan
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Format : Jurnal Ilmiah Teknik Informatika, Fakultas Ilmu Komputer Universitas Mercu Buana, Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650 Tlp./Fax: +62215840816
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Kota adm. jakarta barat,
Dki jakarta
INDONESIA
Format : Jurnal Imiah Teknik Informatika
Published by Universitas Mercu Buana
ISSN : 20895615     EISSN : 27227162     DOI : http://doi.org/10.22441/format
Core Subject : Science,
Computer Science & IT
Format : Jurnal Ilmiah Teknik Informatika merupakan jurnal peer-review yang berasal dari hasil-hasil penelitian dan kajian ilmiah di bidang Ilmu Komputer khususnya Informatika. Cakupan naskah artikel yang dapat dipublikasikan difokukuskan pada bidang berikut (namun tidak terbatas): ICT, Rekayasa Perangkat Lunak, Sistem Informasi Geografis, Data mining and Big Data, Komunikasi Data, Mobile Computing, Kesercasan Buatan, E-Learning, Multimedia and Pengolahan Gambar, Sistem Keamanan dan Basisdata, IOT, dan Jaringan Komputer. Format : Jurnal Ilmiah Teknik Informatika diterbitkan oleh Program Studi Informatika, Universitas Mercu Buana Jakarta. Periode penerbitan adalah setahun dua kali, yaitu pada bulan Januari dan bulan Juli.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 10 Documents
 1 
Search results for , issue "Vol 14, No 2 (2025)" : 10 Documents clear
Perancangan Aplikasi Media Sosial TeiTei Chairulsyah, Diofavian Rafif; Panggabean, Claudio Nehemia; Wibowo, Aditya Dwi; Salamah, Umniy
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.003

Abstract

Digital transformation has driven the need for social media platforms that can provide simple, personal, and effective interactions. However, many existing applications tend to offer complex features that are less relevant to user needs. This research aims to design and develop TeiTei, a web-based social media application that emphasizes ease of use, convenience, and interactivity. This research includes identifying user needs, designing a user-friendly interface using the CSS Bootstrap framework, developing a PHP-based system with the Laravel framework, and managing the database using MySQL. In addition, a search algorithm was implemented to improve the efficiency of finding other users on the platform. The results of this research produced a web-based social media application prototype that can meet user needs through an intuitive interface design and relevant features. The implementation of search algorithms also adds value by expanding users' social networks. This research is expected to make a significant academic contribution to the development of social media applications, as well as serve as a reference for similar studies aimed at enhancing digital social interaction experiences.
Development of a web-based real estate application at Raya Houses Saputra, M Julius; Ramayanti, Desi
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.004

Abstract

This research develops a web-based real estate management system to enhance property management efficiency at Raya Houses, Jakarta. The system includes listing management, filter-based property search, AI-generated property articles, popular property analysis based on visits, and automated sales contract generation. A hybrid development approach combines Waterfall for linear structure and Kanban for iterative flexibility. Data were gathered through online observation and agent interviews, followed by functional testing of key features. Testing results show all features function as specified, improving agent operational efficiency and data accuracy. Implemented using Laravel, MySQL, and Docker, this system provides an innovative solution for automating real estate business processes, leveraging AI and document generation features underexplored in prior work.
Sistem Pendukung Keputusan Pemilihan Perumahan Menggunakan Kombinasi Metode ROC dan ARAS Septiana, Ristasari Dwi; Herdiansah, Arief; Septarini, Ri Sabti; Irfan, Muhammad
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.005

Abstract

Selecting a suitable house is a multifaceted process that involves several considerations, including cost, location, available facilities, security, and access to transportation. Because decisions are often made subjectively, there is a risk of inefficiency, which highlights the need for a structured decision-making approach. This study presents the development of a web-based decision support application that combines the Rank Order Centroid (ROC) method for assigning criterion weights based on their priority order, and the Additive Ratio Assessment (ARAS) method for evaluating and ranking housing alternatives based on relative utility scores. The system was implemented using PHP and MySQL, incorporating modules for managing criteria, alternatives, inputting evaluations, and generating automated calculations and visual outputs. A case study with five housing options and five main evaluation criteria was conducted. The research employed a structured methodology involving problem identification, criteria selection, weight calculation using ROC, alternative evaluation using ARAS, system development, and black-box testing for validation. The findings revealed that Taman Permata achieved the highest utility score of 0.8616, placing it as the top-ranked alternative. Functional testing through a black-box approach verified that all components operated as intended. Overall, the system offers a transparent and effective tool to support users in identifying the most appropriate housing option according to their individual needs and priorities.
Implementation of SVM Algorithm on Software Define Network to Detect and Mitigate DDOS Attacks on Network Servers purnomo, andi; Achyar, Avrijsto Amandri
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.001

Abstract

Software Defined Network (SDN) is a network architecture that is very useful in the future where SDN can be used to manage network traffic on server networks. SDN can be implemented using a variety of controllers. In the controller the developer can configure it with various algorithms or other functions. At present, cyber crimes are increasingly numerous and dangerous. One of the most dangerous cyber attacks that is mostly carried out by both novice and professional hackers is the DDoS attack. DDoS attacks are aimed at crippling servers with server administration with multiple streams and packets. SDN as an architect for managing networks can be used to detect and counteract DDoS attacks so that servers are protected from these attacks. In this study researchers used SDN configured using the SVM algorithm to detect and mitigate DDOS attacks. In this study, the researchers obtained results where SDN with the SVM algorithm configuration obtained an accuracy rate of 99.67%. The SDN speed configured with the SVM algorithm does not exceed 0.30ms. Wireshark statistics show that SDN with the SVM algorithm configuration can stabilize and mitigate packets detected as DDOS.
Analisis Perancangan Sistem Informasi pada Perpustakaan Institut Teknologi Mitra Gama Hidayat, Arif; CANDRA, Dori GUSTI ALEX; Meiditra, Irzon; Putra, Budi Permana; Putra, Khelvin Ovela
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.002

Abstract

Perpustakaan sangat penting untuk membantu pendidikan, penelitian, dan pengembangan ilmu pengetahuan.Namun, masalah seperti pengelolaan data yang tidak terintegrasi, yang dapat menyebabkan pemrosesan yang terlalu lama, masih ada. Untuk mengatasi hal ini, sistem informasi kontemporer yang mampu mengelola data dan informasi dengan baik diperlukan. Tujuan studi ini adalah menganalisis dan mengoptimalkan sistem informasi suatu perpustakaan dengan menggunakan teknik Analisis Sistem Informasi (ASI), Diagram Konteks(CD), Diagram Flow Data (DFD), dan Diagram Hubungan Entitas (ERD). Metode ini membantu dalam memahami kebutuhan pengguna dan merancang struktur sistem informasi yang efisien. Penerapan sistem informasi ini diharapkan dapat membantu dalam memberikan layanan percetakan yang efisien dan dapat diandalkan.
Peningkatan Kreativitas Anak dengan Implementasi Augmented Reality Pembelajaran Hewan Berbasis Android Kusmawan, Dicky; Aryani, Diah; Yusuf, Mohamad
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.007

Abstract

This study aims to address challenges in early childhood education, which are often caused by regulations, limited educator readiness, and inadequate interactive learning media. Augmented Reality (AR) technology offers a solution by integrating the virtual and real worlds, enabling children to experience 3D objects immersively using smartphones. The research was conducted at SD Bedahan 01 with third-grade students learning Natural Science (IPA) topics about animals, including their characteristics, classifications, habitats, and benefits. Initial observations showed the average student score was 78, meeting the Minimum Competency Criteria (KKM) but requiring improvement to optimize learning outcomes. To address this, an AR-based learning media application for Android was developed using the Multimedia Development Life Cycle (MDLC) method, integrating 3D visuals, audio, and interactive features to create an engaging and immersive learning experience. The results demonstrated that the use of AR technology increased students’ interest and understanding of the material, as well as their ability to recall and apply concepts. This study highlights the potential of AR as an effective educational tool and contributes to the development of innovative and interactive learning media for elementary education, particularly in subjects requiring visualization. Future research may explore expanding AR features to include gamification and advanced interactivity for broader educational applications.
Klasifikasi Kepribadian Berdasarkan Dimensi Ekstraversi Berbasis Data Mining Menggunakan Extremely Randomized Trees Yanuardi, Yanuardi; Basri, Firdiansyah Firdaus; Aksani, Muhammad Luthfi
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.008

Abstract

Personality is one of the fundamental aspects that distinguishes individual behavior, thought patterns, and interaction styles. The extraversion dimension, which is part of the Big Five Personality Traits framework, reflects an individual’s tendency to engage in social interactions with two main poles, namely introvert and extrovert. Identifying personality based on this dimension has various applications, ranging from education to employee recruitment. This study aims to develop a personality classification model based on the extraversion dimension using the Extremely Randomized Trees (ERT) algorithm and to compare its performance with other algorithms, namely Decision Tree, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). The dataset used in this study was obtained from the Kaggle platform, consisting of 2,900 entries and including social behavior indicators represented by five numerical variables and two categorical variables. The research methodology involves data preprocessing, exploratory data analysis, model construction, and evaluation using confusion matrix, precision, recall, F1-score, accuracy, and ROC-AUC. The results indicate that ERT achieves the best performance compared to the other algorithms. The ERT model obtained an accuracy of 92.69%, an F1-score of 0.9269, and a ROC-AUC of 0.9429, outperforming SVM (F1 0.9173; AUC 0.9300), KNN (F1 0.9086; AUC 0.9146), and Decision Tree (F1 0.8879; AUC 0.8876). The superiority of ERT is supported by its tree-based ensemble mechanism with high randomization, which enhances generalization, reduces variance, and captures complex non-linear interactions among behavioral variables. Therefore, ERT is proven to be effective in consistently distinguishing introvert and extrovert tendencies.
Sistem Otomatis Ringkasan Laporan Keuangan Berbasis PDF Menggunakan Metode NLP Transformer Nugraha, Fahmi; Surahmat, Asep
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.009

Abstract

Kompleksitas dan volume laporan keuangan perusahaan yang terus meningkat menjadi tantangan bagi analis dan pemangku kepentingan dalam menginterpretasikan informasi secara cepat dan akurat. Analisis manual cenderung memakan waktu lama dan rentan terhadap kesalahan. Penelitian ini mengusulkan sistem otomatis untuk melakukan peringkasan laporan keuangan berbasis PDF dengan menggunakan metode Natural Language Processing (NLP) berbasis Transformer. Sistem dikembangkan menggunakan Python serta memanfaatkan PyPDF2/pdfplumber untuk ekstraksi teks, NLTK untuk prapemrosesan, dan model BART/T5 dari Hugging Face Transformers untuk menghasilkan ringkasan. Evaluasi dilakukan pada laporan tahunan perusahaan multinasional dengan panjang 50–200 halaman. Hasil pengujian menunjukkan sistem mampu mereduksi teks hingga 10–15% dari panjang asli, dengan nilai rata-rata ROUGE-1 = 0,72; ROUGE-2 = 0,62; dan ROUGE-L = 0,70. Ringkasan yang dihasilkan mempertahankan informasi penting seperti tren pendapatan, laba bersih, beban operasional, dan arus kas. Pendekatan ini dapat mempercepat analisis keuangan, mengurangi beban kognitif analis, serta menghasilkan ringkasan yang konsisten. Ke depan, penelitian dapat dikembangkan dengan fine-tuning model pada korpus keuangan serta integrasi analisis sentimen untuk memperkaya interpretasi manajerial.
Kinerja Komparatif LSTM dan XGBoost untuk Peramalan Radiasi Matahari Perkotaan Tropis Indriyanti, Prastika; Fajriah, Riri
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/10.22441/format.2025.v14.i2.010

Abstract

The increasing reliance on clean energy has accelerated the development of solar energy infrastructure. However, its intermittent nature—especially in tropical urban climates—poses significant challenges to maintaining grid stability. This study compares the performance of two machine learning algorithms, Long Short-Term Memory (LSTM) and Extreme Gradient Boosting (XGBoost), for hourly solar irradiance forecasting in two climatically distinct tropical cities: Jakarta and Bogor. Using a 10-year historical dataset from NASA POWER that includes solar irradiance and relevant meteorological variables, this research addresses the gap in comparative analysis of deep learning versus ensemble models within high-granularity tropical data settings. The methodology involves data acquisition, preprocessing, feature engineering, model development, hyperparameter tuning, and evaluation using RMSE, MAE, and R² metrics. The results show that LSTM consistently outperforms XGBoost in both cities. In East Jakarta, LSTM achieved a RMSE of 29.24, MAE of 15.63, and R² of 0.9875, compared to XGBoost with RMSE of 38.65, MAE of 18.92, and R² of 0.9782. Similarly, in Bogor Regency, LSTM achieved RMSE of 30.73, MAE of 16.89, and R² of 0.9862, outperforming XGBoost which recorded RMSE of 38.41, MAE of 18.68, and R² of 0.9785. These findings highlight LSTM's superior ability to capture complex temporal dependencies and nonlinear trends in solar irradiance time-series data, especially under the fluctuating weather patterns characteristic of tropical urban environments. The results provide strong empirical support for implementing LSTM-based forecasting in solar energy management systems across similar geographic regions.
Decision Support System in Determining the Optimal Raw Material Supplier Using a Combination of Entropy and MOORA Wang, Junhai; Ahmad, Imam; Setiawansyah, Setiawansyah
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.006

Abstract

The selection of the right raw material supplier plays a crucial role in ensuring the efficiency and sustainability of supply chain management. However, the decision-making process is often complex due to the multiple criteria that must be considered simultaneously, such as quality, price, delivery timeliness, production capacity, and flexibility. To address this challenge, this study applies a decision support system that integrates the Entropy method for objective weighting of criteria and the MOORA method for ranking alternatives. Entropy weighting provides an unbiased determination of the importance of each criterion based on data variation, while MOORA delivers a systematic ranking of suppliers by combining benefit and cost criteria into a comprehensive performance score. The results of the analysis on eight supplier alternatives show that Supplier S8 achieves the highest ranking, followed by Supplier S3 and Supplier S6, indicating their superior ability to meet the defined criteria, especially in capacity and flexibility. Meanwhile, Supplier S4 ranks the lowest, reflecting its relatively weaker performance across several aspects. These findings demonstrate that the combination of Entropy and MOORA provides a reliable, objective, and transparent framework to support decision-making in supplier selection.

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