Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi

Analisis Perilaku Malware Menggunakan Pendekatan Analisis Statis dan Dinamis

Khansa Khalda, Dwi Kurnia Wibowo — Wed, 15 Jan 2025 00:00:00 +0000

Deteksi malware merupakan tantangan krusial dalam perkembangan keamanan siber. Penelitian ini mengeksplorasi integrasi analisis statis dan dinamis untuk meningkatkan akurasi deteksi malware. Analisis statis meneliti file malware tanpa eksekusi, memberikan wawasan tentang metadata dan atribut strukturalnya, sedangkan analisis dinamis mengamati perilaku malware selama eksekusi di lingkungan terkendali. Menggunakan dataset 5000 sampel, termasuk ransomware, trojan, spyware, dan worm, alat seperti IDA Pro, PE Studio, dan platform sandbox digunakan. Hasil menunjukkan 87% sampel malware menggunakan code obfuscation untuk menghindari deteksi, dan 95% menunjukkan aktivitas runtime mencurigakan, seperti modifikasi registry dan komunikasi jaringan terenkripsi. Model pembelajaran mesin (Deep Neural Networks, Random Forest, Support Vector Machine) yang dilatih pada dataset hybrid mencapai akurasi 96,4% dengan DNN, menunjukkan keunggulan dibandingkan pendekatan metode tunggal. Tantangan seperti kebutuhan komputasi tinggi diatasi melalui implementasi berbasis cloud.

Automation of Remote Laboratory Device Configuration File Management

Putu Gde Qwat Bayu Liandaru, Gani Indriyanta, Joko Purwadi — Wed, 29 Jan 2025 00:00:00 +0000

This study develops a Python-based configuration file management application to automate backup and recovery of network devices in the Universitas Kristen Duta Wacana laboratory, which uses Cisco and Mikrotik devices. The goal is to understand the impact of automation on the effectiveness of backup and recovery, support for remote configuration file management, reduction of recovery time, and its impact on operational sustainability. The Waterfall method is applied with the stages of analysis, design, implementation, testing, and evaluation, using network topology data, device information, and network protocols collected through observation, interviews, documentation, and literature studies. Testing includes scenarios of full and partial backup and recovery, error handling (credentials, lost files, unresponsive devices), and FTP server and database failure conditions on a network topology consisting of four identical blocks with Mikrotik routers and switches. The test results show that the application functions as expected, with all scenarios running smoothly without significant failures, including the ability to filter data according to parameters and detect credential errors. This system is concluded to have met the test objectives and is ready to be implemented.

Forsyth-Edwards Notation in Chess Game Clustering: A Depth-Based Evaluation

Feri Wijayanto — Sat, 11 Jan 2025 00:00:00 +0000

Chess games clustering poses the challenge of accurately grouping games with similar strategies and positions, especially when the openings are similar. Previous research has used Portable Game Notation (PGN) as a feature for clustering, but its emphasis on move order can limit position transposition. This research addresses this limitation by evaluating Forsyth-Edwards Notation (FEN), which focuses on board position, as an alternative. Hierarchical clustering with complete linkage and K-means clustering were used to analyze 100 chess games at move depths of 20, 30, 40, and 60. Both methods effectively cluster games involving the English Opening and the Queen's Gambit Declined, with FEN providing slightly better differentiation than PGN. However, challenges remain in grouping French Defence variations, especially the Poulsen Attack and variations with 6.a3, due to positional similarities. This study underlines the robustness of FEN for clustering tasks and its compatibility with hierarchical clustering, highlighting the important role of move depth. The results provide a basis for refining clustering methods and using larger data sets to deepen insights into chess strategies.

Comparison of Machine Learning Algorithms in Classifying Districts/Cities in Indonesia According to the Human Development Index (HDI) in 2021

Ni Kadek Ayu Purnami Sari Dewi, Arie Wahyu Wijayanto, Joko Ade Nursiyono — Sun, 12 Jan 2025 00:00:00 +0000

The human development index (HDI) is one of the measuring tools for achieving the quality of life of a region or even a country, including Indonesia. There are 3 basic components of the HDI, namely the dimensions of health, knowledge, and decent living. Development in Indonesia is uneven as indicated by the Human Development Index (HDI) of districts/cities in 2021 which varies greatly. The purpose of this study is to compare several machine learning algorithms to classify districts/cities in Indonesia according to the Human Development Index (HDI) in 2021. There are six machine learning algorithms used in this study, namely Artificial Neural Network (ANN), Support Vector Machine (SVM), K-Nearset Neighbor (K-NN), Random Forest, Decision Tree, and Naive Bayes. The k-Fold Cross Validation method is applied to form the training set and testing set, with 10 folds and 1 repetition. The results of the study showed that the classification results of the SVM algorithm using the Radial Basis Function (RBF) kernel parameters with sigma = 0.4864648 and C = 1 were the best among the other five algorithms with an average accuracy of 76.08% and a maximum accuracy of 88.24%.

Implementasi Pompa Air Berbasis Teknologi Digital di Lahan Pertanian Tadah Hujan

Wed, 15 Jan 2025 00:00:00 +0000

Pompa air diesel manual/konvensional dapat diubah menjadi sistem pompa air otomatis dengan teknologi digital. Hal itu menjadi usulan solusi dari masalah masalah pompa air diesel yang terjadi. Berawal dari permasalahan operasional yang tidak mudah karena tidak semua warga mampu mengoperasikan pompa tersebut, membutuhkan tenaga lebih besar dalam pengoperasiannya, kondisi lokasi tempat pompa yang lembab, licin, dan rawan hewan berbisa menyulitkan operator dalam menyalakan dan mematikan pompa. Penelitian ini menggunakan metode waterfall dengan fokus pengujian dan implementasi sistem yang dibangun. Tujuan implementasi sistem ini adalah memudahkan petani di kawasan lahan pertanian tadah hujan dalam mengoperasikan pompa distribusi air. Sistem yang dibangun pada penelitian ini telah diterapkan pada kondisi sesungguhnya di kawasan tadah hujan, padukuhan Pagergunung, Sitimulyo, Piyungan. Di sisi lain, penelitian ini menggunakan sistem cerdas dengan pewaktu dan kontrol jarak jauh menggunakan antar muka pengguna Ubidots. Hal ini yang membedakan penelitian ini dengan penelitian sebelumnya. Sistem ini diuji dalam dua tahap yaitu tahap sebelum implementasi dan tahap sesudah implementasi. Tahap pertama dilakukan pengujian sebanyak enam sesi, sedangkan tahap kedua dilakukan sebanyak dua sesi. Hasil pengujian secara keseluruhan menunjukkan 97% percobaan tahap pertama berhasil, sedangkan tahap kedua mencapai keberhasilan 100%. Sistem dapat berjalan secara otomatis sesuai jadwal, juga dapat dikontrol dari jarak jauh melalui perangkat mobila maupun seluler.

Decoding Fan and Societal Sentiment: ABSA of The Saudi Pro League’s Recent Evolution

Dheya Ali Qasem Alraimi, Irving Vitra Paputungan — Fri, 24 Jan 2025 00:00:00 +0000

The Saudi Professional League (SPL) has attained global recognition through its recruitment of high-profile international players, yet this rise has intensified public scrutiny regarding incidents involving these athletes, such as Controversies surrounding sportsmanship, provocative celebrations, verbal altercations with spectators. This study analyzes (4,884) Arabic-language posts from (2021 to 2024), employing Aspect-Based Sentiment Analysis (ABSA) and the fine-tuned MARBERT model. The findings reveal a dominant negative sentiment (71.9%) across the dataset, with 'Player-Conduct' and 'Disciplinary-Action' emerging as the most frequently discussed aspects. Co-occurrence and correlation analyses indicate that negative sentiment is closely tied to perceptions of inadequate governance and cultural misalignment within the SPL, further intensifying public dissatisfaction. This research underscores the duality of high-profile players as drivers of global visibility and sources of domestic tension, particularly within culturally sensitive contexts. By addressing these challenges, the SPL can mitigate reputational risks while harmonizing its international ambitions with domestic expectations. This study advances Arabic Aspect-based sentiment analysis in the sports domain and provides actionable insights to enhance ethical governance, align with cultural sensitivities, and strengthen stakeholder engagement, thereby supporting the SPL’s long-term credibility and growth.