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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) IJoICT (International Journal on Information and Communication Technology) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA JSiI (Jurnal Sistem Informasi) JURIKOM (Jurnal Riset Komputer) INTEK: Jurnal Penelitian Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Data Science and Its Applications BERNAS: Jurnal Pengabdian Kepada Masyarakat Decode: Jurnal Pendidikan Teknologi Informasi eProceedings of Engineering Nuansa Informatika Jurnal Pemanfaatan Teknologi untuk Masyarakat
Mahendra Dwifebri Purbolaksono
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Analisis Sentimen Kategori Aspek Pada Ulasan Produk Menggunakan Metode KNN Dengan Seleksi Fitur Mutual Information Wilantapoera, Alex Wira; Astuti, Widi; Purbolaksono, Mahendra Dwifebri
eProceedings of Engineering Vol. 10 No. 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Analisis sentimen adalah bidang yang cukup populer untuk menganalisis opini, sikap, dan emosi terhadap suatu subjek dari banyak orang. Dalam hal ini teks ulasan menjadi alat untuk menilai, menimbang, dan mengkritik sebuah produk yang diulas. Produk adalah suatu hal yang dapat memuaskan seorang konsumen dalam bentuk yang beragam seperti barang, jasa, dan sebagainya. Pada penelitian ini dilakukan sebuah implementasi sebuah klasifikasi pada ulasan produk kecantikan dari situs Female Daily dengan menggunakan metode k-Nearest Neighbor (kNN). Metode kNN merupakan metode yang umum digunakan untuk klasifikasi. Lalu menggunakan Mutual Information (MI) sebagai metode seleksi fiturnya. Pada penelitian ini dihasilkan nilai akurasi 91,59% pada aspek price, 90,33% pada aspek packaging, 50,05% pada aspek product, dan 85,89% pada aspek aroma.Kata kunci-k-Nearest Neighbour, Ulasan Produk, Ulasan, Produk, Mutual Information, Analisis sentimen.
Perbandingan Algoritma Machine Learning untuk Analisis Sentimen Berbasis Aspek pada Review Female Daily Wicaksono, Muhammad Hadiyan; Purbolaksono, Mahendra Dwifebri; Faraby, Said Al
eProceedings of Engineering Vol. 10 No. 3 (2023): Juni 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Beredar produk produk kecantikan yang di jual di internet oleh berbagai macam produsen baik luar negeri maupun dalam negeri. Akan tetapi masih diragukan kualitas kosmetik yang dijual oleh tiap produsen, agar mengetahui apakah produk tersebut baik digunakan maka produsen perlu mendapatkan ulasan/review dari konsumen yang memakai produk tersebut. Untuk itu agar produsen lebih mudah untuk mencari produk yang relevan dengan kesehatan maka dibutuhkan sebuah sistem untuk mengklasifikasikan review produk tersebut termasuk kategori relevan atau tidak relevan terhadap aspek kesehatan. Pada Tugas Akhir ini digunakan Machine learning pada klasifikasi sentimen menggunakan Random Forest, Support Vector Machine(SVM), dan K-Nearest Neighbour(KNN) untuk mencari accuracy tertinggi dan F1-score dari ketiga algoritma tersebut dengan menggunakan feature extraction yaitu chi-square dengan feature selection menggunakan Selected K Best untuk proses preprocessing. Dalam penelitian ini telah diperoleh analisis hasil bahwa algoritma SVM dengan kernel Linear mendapatkan nilai akurasi terbaik sebesar 67.10%.Kata kunci-perbandingan, analisis sentimen, KNN, random forest, SVM, chi- square, selected K Best, female daily, kesehatan
Performance and Efficiency Testing Analysis of Database Systems in Academic Information Systems: Analisis Pengujian Kinerja dan Efisiensi Sistem Basis Data dalam Sistem Informasi Akademik Utami Kusuma Dewi; Ryan Lingga Wicaksono; Mahendra Dwifebri Purbolaksono; Villy Satria
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.438

Abstract

This study examines the performance and efficiency of database systems within academic information systems, acknowledging the increasing demand for responsiveness and reliability in managing complex academic data. As educational institutions increasingly rely on digital systems, performance testing becomes essential to ensure that these systems continue to support the learning environment effectively. Guided by the ISO/IEC 25010 standard, the research focuses on evaluating three key aspects of performance efficiency: time behavior, resource utilization, and capacity. Using JMeter, a range of user load scenarios were simulated, and the results were examined through Control Quality Charts and Nelson Rules to detect underlying issues affecting system performance. The findings reveal that 82.5% of queries demonstrated good time behavior, and 80% performed well in resource usage. However, half of the tests related to capacity highlighted the need for further improvements. Some queries experienced delays and consumed excessive CPU and memory resources, indicating areas where optimization is required. These insights highlight the importance of refining queries and managing resources more effectively to ensure a seamless user experience. Future research should consider automated optimization, machine learning-based performance prediction, and system scalability, especially in more dynamic and distributed academic environments.
Digitalisasi Informasi Kualitas Udara melalui Signage Interaktif untuk Meningkatkan Kesadaran Lingkungan Ruang Publik Novian Anggis Suwastika; Mahendra Dwifebri Purbolaksono; Said Al Faraby3
JAPATUM: Jurnal Pemanfaatan Teknologi untuk Masyarakat Vol 4 No 1 (2025): Maret, 2025
Publisher : MATRADIPTI

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Abstract

Permasalahan kualitas udara menjadi isu penting yang berdampak langsung terhadap kesehatan masyarakat dan keberlanjutan lingkungan, terutama di wilayah yang belum memiliki sistem pemantauan yang memadai. Keterbatasan akses informasi kualitas udara secara real-time menyebabkan rendahnya kesadaran masyarakat dalam menjaga lingkungan. Kegiatan pengabdian ini bertujuan untuk mengembangkan sistem CJUC (Cek Jaga Udara Cerdas) berbasis Internet of Things (IoT) yang terintegrasi dengan signage interaktif dan dashboard digital guna menyajikan informasi kualitas udara secara real-time dan mudah dipahami. Metode yang digunakan meliputi analisis kebutuhan, perancangan dan pengembangan sistem, implementasi, serta sosialisasi kepada masyarakat. Kegiatan dilaksanakan selama 12 minggu di Desa Banjar Agung, Kabupaten Tulang Bawang, dengan sasaran 3.580 jiwa atau 270 kepala keluarga. Hasil pengabdian menunjukkan bahwa sistem mampu meningkatkan akses informasi kualitas udara serta mendorong perubahan perilaku masyarakat, seperti mengurangi pembakaran sampah dan meningkatkan penghijauan. Dengan demikian, digitalisasi informasi kualitas udara berbasis IoT terbukti efektif dalam meningkatkan kesadaran lingkungan dan mendukung pembangunan berkelanjutan.
WORD EMBEDDING ANALYSIS IN SENTIMENT ANALYSIS USING MACHINE LEARNING: A CASE STUDY OF STEAM RPG GAME REVIEWS Ardian Adam Alfarisyi; Mahendra Dwifebri Purbolaksono; Alfian Akbar Gozali
Jurnal Sistem Informasi Vol. 12 No. 2 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i2.10917

Abstract

User reviews on gaming platforms such as Steam have become a crucial source of information for potential players before making purchasing decisions. Due to the varied nature of user opinions, sentiment analysis is essential for processing and interpreting these reviews. This study investigates the application of sentiment analysis to RPG game reviews on Steam, aiming to assist users by summarizing reviews through sentiment results and providing insights into the general perception of a game. To achieve this, the study applies sentiment analysis using Word2Vec and Support Vector Machine (SVM). It focuses on evaluating the impact of lemmatization during preprocessing and analyzing the performance of Word2Vec in sentiment classification. Word2Vec transforms review text into vector representations that capture semantic relationships, enhancing the model’s ability to understand context. Meanwhile, SVM is chosen as the classifier for its effectiveness in distinguishing between positive and negative reviews and handling high-dimensional data. The system developed uses Word2Vec with 300-dimensional vectors combined with an SVM Polynomial classifier, resulting in the best performance among the tested models. The final model achieves a macro-average F1-score of 88.6%, indicating a strong capability in accurately classifying sentiments in user reviews. These results highlight the potential of combining word embedding and machine learning techniques for analyzing sentiment in gaming platforms.   Keywords: sentiment analysis, Word2Vec, SVM, Steam, RPG
A Performance Comparison of Unity and Godot for First-Person Shooter Game Development Faiz Azizan Rashied; Mahendra Dwifebri Purbolaksono; Dody Qori Utama
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 6 No. 2: JULI 2026
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v6i2.1804

Abstract

The paper presents the results of an investigation aimed at identifying the differences between the game engines Unity and Godot in terms of First-Person Shooter (FPS) development. Although the use of the two is widespread, there is a lack of research comparing their performance when subjected to similar experiments. The current study helps to address this gap by measuring the performance of these engines against six key indicators, namely RAM, CPU, frames per second (fps), installation size, export time, and exported build size. The former two engines were chosen since they are the most popular in the industry. Unity 6 and Godot 4.4.1 were put through a series of tests while running the same FPS test scenes on the same hardware (Intel Core i7-10870H, 16 GB RAM, Windows 10). RAM and CPU consumption were measured using Windows Task Manager and verified with the built-in profiler of the engines after three runs. The rest of the variables were measured directly. On average, Godot performed slightly better in terms of RAM (1,108 ± 60 MB), CPU (9.8 ± 0.4%), and fps (143 versus 36), while the installation size of Unity was found to be approximately 71 times larger (170 MB versus 12.1 GB). In addition, Godot took approximately five seconds to export, which is significantly faster than 130 seconds for Unity. The exported build sizes were similar, amounting to 114 MB and 110 MB for Godot and Unity, respectively. Overall, the findings contribute to a preliminary understanding of which engine may be more beneficial in specific conditions, which may be subject to further verification across multiple devices.
Co-Authors Abdurrahman Al Afifi Adiwijaya Adnan Imam Hidayat Al Faraby, Said Alfian Akbar Gozali Amala, Ihsan Ahsanu Angelia Brigitta Maharani M.P Anggitha Yohana Clara Antika Putri Permata Wardani Ardian Adam Alfarisyi Bima Mahardika Wirawan Deninsyah Tiya Bella Pratama Dody Qori Utama Donni Richasdy Eko Darwiyanto Fahmi Hamzah Fahriza Ichsani Rafif Faiz Azizan Rashied Fakhri Taufiqurrahman Felia Novitasari Fhira Nhita Firdaus, Muhammad Abdurrahman Gde Agung Brahmana Suryanegara Gede Agung Ary Wisudiawan Ghinaa Zain Nabiilah Imam Prayoga Irfan Budi Prakoso Kemas Muslim Lhaksmana M. Mujahid Biagi Usama Mbake Woka, Adrian Yoris Muhammad Farhan Muhammad Irvan Tantowi Naufal Hilmiaji Novia Russelia Wassi Novian Anggis Suwastika Nugraha, Mohamad Rizki Pramoedya Syachrizalhaq Lyanda Pramoedya Syachrizalhaq Lyanda Rendhy Al-Farrel Rendi Kustiawan Rizal Adi Putranto Rizki Syafaat Amardita Rizkiyanto, Muhamad Dafa RIZKY, ACHMAD Ryan Lingga Wicaksono Said Al Faraby3 Tandya Rizky Pratama Tetuko Muhammad Hanurogo Utami Kusuma Dewi Villy Satria Wicaksono, Muhammad Hadiyan Widi Astuti Widi Astuti Wilantapoera, Alex Wira Winkie Setyono Yudi Priyadi