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All Journal Jurnas Nasional Teknologi dan Sistem Informasi JAIS (Journal of Applied Intelligent System) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JOURNAL OF APPLIED INFORMATICS AND COMPUTING Abdimasku : Jurnal Pengabdian Masyarakat
Adhitya Nugraha
Universitas Dian Nuswantoro
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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The Development of Berbakti: Elder Caring Mobile Application in Indonesia Septian Enggar Sukmana; Heru Agus Santoso; Fahri Firdausillah; Adhitya Nugraha; Farah Zakiyah Rahmanti; Arkav Juliandri
Journal of Applied Informatics and Computing Vol 3 No 2 (2019): Desember 2019
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (806.047 KB) | DOI: 10.30871/jaic.v3i2.1501

Abstract

Children must care their parent as their devotion to their parent. In Indonesia, that kind condition is a common situation. But, to handling this situation in this global era is more difficult because many children choose going to another city or another region to do some activity like taking a job or going to college. It gives an impact to their parent especially when their parent is too old and needs to be cared. This motivation in this paper is based on this kind problem. The development of application uses Waterfall. The system must meet the requirement so not just technichal development is performed, social study must be conducted in the process. We use several testings such blackbox testing, server testing, and usefulness identity. Commonly, we got unsatisfied result based on testing, so some repairement must be conducted.
Malware Detection Using Decision Tree Algorithm Based on Memory Features Engineering Adhitya Nugraha; Junta Zeniarja
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.6735

Abstract

Malware is malicious software that can harm, manipulate, steal from victim's device system. Due to the diverse needs of using internet services, security threats are also increasingly difficult to detect. now attackers are starting to develop malware that can change their own signature which is referred to as polymorphism. Therefore, improvements in the traditional approach to detecting the presence of malware are needed to be improved. One of the malware detection approaches, memory-based analysis technique has proven to be a powerful and effective analytical technique in studying malware behavior. In this study, the implementation of a Decision Tree-based classification algorithm was carried out to analyze the data set. Classifier model was created for the purpose of classifying malware based on memory features engineering. The result shows that the Decision Tree machine learning algorithm has been well performed with accuracy to 99.982 %, a false positive rate equal to 0.1% and precision equal to 99.977%
Improving Multi-label Classification Performance on Imbalanced Datasets Through SMOTE Technique and Data Augmentation Using IndoBERT Model Leno Dwi Cahya; Ardytha Luthfiarta; Julius Immanuel Theo Krisna; Sri Winarno; Adhitya Nugraha
Jurnal Nasional Teknologi dan Sistem Informasi Vol 9, No 3 (2023): Desember 2023
Publisher : Jurusan Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v9i3.2023.290-298

Abstract

Sentiment and emotion analysis is a common classification task aimed at enhancing the benefit and comfort of consumers of a product. However, the data obtained often lacks balance between each class or aspect to be analyzed, commonly known as an imbalanced dataset. Imbalanced datasets are frequently challenging in machine learning tasks, particularly text datasets. Our research tackles imbalanced datasets using two techniques, namely SMOTE and Augmentation. In the SMOTE technique, text datasets need to undergo numerical representation using TF-IDF. The classification model employed is the IndoBERT model. Both oversampling techniques can address data imbalance by generating synthetic and new data. The newly created dataset enhances the classification model's performance. With the Augmentation technique, the classification model's performance improves by up to 20%, with accuracy reaching 78%, precision at 85%, recall at 82%, and an F1-score of 83%. On the other hand, using the SMOTE technique, the evaluation results achieve the best values between the two techniques, enhancing the model's accuracy to a high 82% with precision at 87%, recall at 85%, and an F1-score of 86%.
LITE-BoostTrack: A Hybrid Real-Time Multi-Object Tracking Architecture for Resource-Constrained Environments Ruri Suko Basuki; Adhitya Nugraha; Ardytha Luthfiarta; Ika Novita Dewi; Allifian Ilham Febriyana; Michael Surya Adi Prasaja; Dzawil Uqul
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 2, May 2026
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i2.2478

Abstract

Multi-object tracking (MOT) is a fundamental task in computer vision that underpins applications such as intelligent surveillance, autonomous driving, and crowd analysis. The primary challenge in MOT lies in maintaining identity consistency under frequent occlusions while ensuring real-time performance on resource-constrained devices. This study proposes LITE-BoostTrack, a hybrid tracking framework that combines the confidence-based association mechanism of BoostTrack with the lightweight embedding strategy of the Lightweight Integrated Tracking and Embedding (LITE) architecture. The proposed model extracts appearance descriptors directly from the internal feature maps of the YOLOv8 detector, thereby eliminating the need for an external re-identification network. This design significantly reduces computational complexity while preserving reliable identity association. Experiments were conducted on the MOT20 benchmark using standard MOT evaluation metrics, including HOTA, MOTA, IDF1, IDSW, and FPS, to assess both tracking accuracy and runtime efficiency. The results show that LITE-BoostTrack achieves a HOTA of 27.31 and IDF1 of 37.48, outperforming LITE-BoT-SORT (HOTA 25.73, IDF1 33.88), while reducing identity switches by 37% (2,939 vs. 4,674) and maintaining real-time performance at 13.22 FPS. These outcomes demonstrate that substantial efficiency gains can be achieved through detector-level feature integration without introducing additional deep embedding modules. Although occasional failures still occur under severe occlusion, LITE-BoostTrack provides a balanced and practical solution that effectively combines accuracy and efficiency for real-time multi-object tracking in edge-computing and embedded vision systems.
Pemanfaatan Aplikasi Artificial Intelligence (AI) Generatif untuk Pembelajaran Kreatif Guru PAUD dan SD Sugiyanto Sugiyanto; Yani Parti Astuti; Ifan Rizqa; Totok Sutojo; Heribertus Himawan; Adhitya Nugraha; Dewi Agustini Santoso
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 1 (2026): JANUARI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i1.3232

Abstract

Dalam perkembangan teknologi, setiap orang di dunia ini akan mengikutinya baik anak – anak maupun orang tua. Perkembangan teknologi juga tidak lepas dengan dunia Pendidikan dari berbagai jenjang. Jenjang pada dunia Pendidikan saat ini sudah dimulai sejak anak berusia 2 tahun yang disebut dengan Pendidikan Anak Usia Dini (PAUD). Setelah PAUD ada Kelompok Bermain(KB), kemudian Sekolah Dasar (SD) dan seterusnya yang semua orang sudah mengetahuinya. Dengan adanya Pendidikan di usia dini, maka seorang pendidik harus siap untuk mendampingi secara ekstra dalam pembelajarannya. Pendampingan ini dilakukan karena begitu pesatnya perkembangan teknologi yang sudah mempengaruhi anak – anak balita. Untuk itu seorang pendidik harus dibekali dengan pembelajaran yang dikaitkan dengan perkembangan teknologi. Teknologi yang dipakai yang saat ini dikenal dengan AI dan salah satunya Adalah AI Generatif. AI generatif ini bisa digunakan sebagai media pembelajaran karena menarik dan interaktif. Pada kegiatan ini akan dikenalkan berbagai macam AI Generatif sesuai dengan kebutuhannya. AI Generatif yang dimaksud diantaranya ChatGpt/Gemini/Copilot, Canva AI, DALL-E/Bing Image Creator/Leonardo.ai, Synthesia/Pictory dan MusicGen/Mubert/Soundraw. Dengan diadakannya pelatihan tentang AI Generatif diharapkan guru atau pendidik pada PAUD, KB dan juga SD bisa memberikan arahan dan pengetahuan kepada siswa agar pembelajaran lebih interaktif dan menarik.
Pemberdayaan mahasiswa melalui bisnis kopi gerobak berbasis keterampilan interpersonal dan kewirausahaan Yani Parti Astuti; Erwin Yudi Hidayat; Abu Salam; Cinantya Paramita; Etika Kartikadarma; Adhitya Nugraha; Junta Zeniarja
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 2 (2026): MEI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i2.3340

Abstract

Pendidikan tinggi modern menuntut mahasiswa untuk tidak hanya unggul secara akademis, tetapi juga memiliki keterampilan praktis seperti kewirausahaan dan interpersonal. Pengembangan jiwa kewirausahaan mahasiswa juga menjadi salah satu upaya penting dalam menciptakan generasi muda yang mandiri, kreatif, dan produktif. Kegiatan ini merupakan implementasi pembelajaran berbasis pengalaman (experiential learning) dalam mata kuliah Keterampilan Interpersonal melalui realisasi bisnis nyata, yaitu “DiSanka Kopi,” sebuah usaha kopi gerobak keliling. Kegiatan ini bertujuan untuk menerapkan teori kewirausahaan, mulai dari perencanaan, analisis keuangan, operasional, hingga pemasaran, serta mengasah kemampuan kerja sama tim, komunikasi, dan pemecahan masalah. Usaha ini telah beroperasi selama dua bulan di lingkungan strategis di Jalan Baru dekat kampus Universitas Diopnegoro Fakultas Psikologi, menyasar segmen mahasiswa dan masyarakat umum. Metode pelaksanaan meliputi riset, pengembangan produk, analisis HPP, branding, dan eksekusi operasional harian. Hasil kegiatan menunjukkan respons pasar yang positif dengan penjualan rata-rata 40 cup per hari dan berhasil mencapai titik impas (BEP) dalam waktu singkat. Analisis keuangan menunjukkan Return on Investment (ROI) yang diproyeksikan tercapai dalam 2,14 bulan, membuktikan kelayakan model bisnis. Lebih penting, proyek ini berhasil menjadi sarana efektif bagi mahasiswa untuk mengembangkan kompetensi interpersonal dan manajerial secara langsung di lapangan.
Co-Authors Abu Salam Allifian Ilham Febriyana Ardytha Luthfiarta Arkav Juliandri Cinantya Paramita Dewi Agustini Santoso Dzawil Uqul Erwin Yudi Hidayat Etika Kartikadarma Fahri Firdausillah Farah Zakiyah Rahmanti Heribertus Himawan Heru Agus Santoso Ifan Rizqa Ika Novita Dewi Julius Immanuel Theo Krisna Junta Zeniarja Leno Dwi Cahya Michael Surya Adi Prasaja Ruri Suko Basuki Septian Enggar Sukmana Sri Winarno Sugiyanto Sugiyanto Totok Sutojo Yani Parti Astuti