Article Per Year (5 Year)
p-Index From 2021 - 2026
0.92
P-Index
This Author published in this journals
All Journal Jurnal Pertahanan : Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity, Nasionalism dan Integrity BHUMI: Jurnal Agraria dan Pertanahan Komatika: Jurnal Pengabdian Kepada Masyarakat Journal of Data Insights LamLaj
Wawan Rukmono, Linus Yoseph
Universitas Pertahanan Republik Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Education Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Geospatial and Community Participation Combination in Complete Systematic Land Registration Implementation in Hulu Sungai Tengah Regency Sa’dianoor Sa’dianoor; Linus Yoseph Wawan Rukmono; Edy Saptono; Moelyanto Moelyanto; Irdam Ahmad; Sobar Sutisna; Syamsul Maarif
BHUMI: Jurnal Agraria dan Pertanahan Vol. 5 No. 3 (2019): Bhumi: Jurnal Agraria dan Pertanahan (Special Edition)
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat, Sekolah Tinggi Pertanahan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31292/jb.v5i3.391

Abstract

Land certification provides land legal certainty for every citizen of the Republic of Indonesia, especially, farmers, who constitute the majority of the population of Indonesia. The importance of the agricultural land has been explained in the Republic of Indonesia’s Defense White Paper that the growing amount of agricultural land has a detrimental effect on the Indonesian nation which is agrarian. Decreasing agricultural land is the main factor causing reduced food security. Geospatial technologies such as remote sensing and terrestrial surveys are very helpful for Complete Systematic Land Registration (PTSL) activities. However, the implementation in the field of technology has not yet been optimized due to the lack of the support from Regional Government and the Community. By taking the PTSL implementation in two villages in Barabai Subdistrict, Hulu Sungai Tengah Regency, it was found that problems related to the absence of certaintyof village boundaries, accurate and scattered control points and community understanding of the importance of the legality of their land are inhibiting factors for PTSL activities. By combining this technology with community participation it will produce the right and ideal combination.
Sinergi Bela Negara dan Kemanusiaan dalam Kegiatan Pengabdian Kepada Masyarakat Prodi Teknik Mesin Unhan RI di RSIA Melania Cibinong Linus Yoseph Wawan Rukmono; Arie Sukma Jaya
Komatika: Jurnal Pengabdian Kepada Masyarakat Vol. 1 No. 1 (2021): Mei 2021
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat, Institut Informatika Indonesia Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.601 KB) | DOI: 10.34148/komatika.v1i1.352

Abstract

Kewajiban utama masyarakat akademis di lingkungan Program Studi (Prodi) Teknik Mesin Universitas Pertahanan Republik Indonesia (Unhan RI) adalah melaksanakan Tri Dharma Perguruan Tinggi, yang salah satu komponennya adalah Pengabdian Kepada Masyarakat (PKM). Berada di dalam kelembagaan Kementerian Pertahanan, masyarakat akademis di lingkungan Unhan RI ditekankan untuk menjadi cendekiawan Bela Negara. Oleh karena itu, Prodi Teknik Mesin Unhan RI merancang kegiatan PKM yang tidak hanya bertujuan untuk menerapkan keahlian Teknik Mesin bagi masyarakat umum tetapi juga menyebarluaskan semangat Bela Negara. Puncak dari setiap kegiatan PKM tersebut adalah pelaksanaan sosialisasi Bela Negara dalam rangka memberikan kesadaran pelaksanaan Bela Negara melalui profesi masing-masing. Artikel ini membahas terwujudnya sinergi Bela Negara dan Kemanusiaan melalui kegiatan PKM Prodi Teknik Mesin Unhan RI di Rumah Sakit Ibu dan Anak (RSIA) Melania Cibinong. Tahap pertama kegiatan PKM ini adalah penerapan keahlian Teknik Mesin melalui perbaikan berbagai peralatan pendukung operasional rumah sakit seperti komputer, genset dan alat RO (Reverse Osmosis). Selanjutnya, tahap kedua PKM ini adalah kegiatan sosialisasi Bela Negara pada pimpinan dan karyawan rumah sakit. Melalui kegiatan PKM ini, semangat Bela Negara masyarakat akademis di lingkungan Teknik Mesin Unhan RI terwujud melalui penerapan keahliannya dalam mendukung keberlangsungan pelayanan kemanusiaan terhadap masyarakat. Di lain pihak, pimpinan dan karyawan RSIA Melania Cibinong memiliki kesadaran bahwa Bela Negara dapat diwujudkan melalui tanggung jawab profesinya dibidang pelayanan kemanusiaan. Pemilihan institusi kesehatan sebagai tempat dilaksanakannya PKM Prodi Teknik Mesin Unhan RI menjadi contoh sinergi antara semangat Bela Negara dan Kemanusiaan yang mendukung kehidupan berbangsa dan bernegara yang sehat dan humanis.
THE BIOMIMETIC FIN PERFORMANCE EVALUATION FOR AN EFFICIENT AUTONOMOUS UNDERWATER VEHICLE (AUV) TO SUPPORT THE REVOLUTION IN MILITARY AFFAIRS (RMA) IN UNDERWATER DEFENSE Arie Sukma Jaya; Linus Yoseph Wawan Rukmono
Jurnal Pertahanan: Media Informasi ttg Kajian & Strategi Pertahanan yang Mengedepankan Identity, Nasionalism & Integrity Vol 7, No 3 (2021)
Publisher : The Republic of Indonesia Defense University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33172/jp.v7i3.1262

Abstract

The world is facing the global trend of Industry 4.0 in the manufacturing sectors. The concept of the Internet of Underwater Thing (IoUT) presents the trends in the underwater region. The Autonomous Underwater Vehicle (AUV) as a data collector and transmitter becomes the central component in the connected system of the IoUT. The efficiency of the platform is crucial to lengthening the range and duration of the mission. The biomimetic method of utilizing the caudal fin propulsion could enhance the efficiency of the small and low-speed AUV. From the defense perspective, there is a concept of Revolution in Military Affairs (RMA) that supports technological modernization for defense purposes. Technically, this study aims to combine the technical aspects of mechanical engineering and the defense concept of RMA in the technological advancement of AUV for the advanced and efficient defense strategy in the underwater region. The evaluations involved numerical simulation with Computational Fluid Dynamics (CFD) method. The simulation results show that the fully tapered flexible fin enhances the efficiency by 25%, while the narrow flexible fin enhances the efficiency by 30%. These results indicate that a flexible tapered fin should be the primary consideration in designing the high-efficiency biomimetic fin. The visualization of the force vectors shows that the flexibility of the fin acts as a thrust vectoring factor that directs more force vectors in the thrust direction. This study supports the RMA concept implementation by technological modernization, such as efficient biomimetic AUV development, to develop doctrines in the State's defense in the underwater region.
Machine Learning Based Water Level Forecasting for Tidal Flood Mitigation in Indonesian Coastal Regions: Peramalan Ketinggian Air Berbasis Pembelajaran Mesin untuk Mitigasi Banjir Pasang Surut di Wilayah Pesisir Indonesia Sugiarto Sugiarto; Riduan Riduan; Linus Yoseph Wawan Rukmono
Journal of Data Insights Vol 4 No 1 (2026): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v4i1.1167

Abstract

Changes in coastal water levels significantly impact maritime logistics and tidal flood risks, which are categorised as non-military threats to national security and socio-geographical stability. This study aims to develop and compare water level prediction models using Random Forest, Long Short-Term Memory (LSTM), and their ensemble as a technology-based disaster mitigation strategy in Indonesian coastal areas. The dataset was obtained from the Tanjung Priok Maritime AWS in August 2024 and comprises meteorological features (rainfall, air temperature, air pressure, wind speed) and oceanographic data (sea surface temperature), with water level as the target variable. Data preprocessing involved time-based linear interpolation and feature standardisation. Model evaluation was conducted using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and residual analysis. The results indicate that Random Forest provides stable performance (RMSE 0.2957, MAE 0.2130), while LSTM is more responsive to daily temporal fluctuations despite slightly higher errors (RMSE 0.3156, MAE 0.2339). A simple ensemble of both models achieved the most optimal and robust performance (RMSE 0.2954, MAE 0.2132) with a well-distributed residual. This study concludes that implementing the ensemble model enhances the reliability of tidal flood early warning systems, serving as a crucial pillar of non-military defence strategies to safeguard national logistical security in Indonesia's coastal zones.
The AI-Enabled Pharmacovigilance for Defence Health Surveillance: Automatic Detection of Adverse Drug Events from Patient Reviews Using BioClinical ModernBERT: Farmakovigilans Berbasis AI untuk Pengawasan Kesehatan Pertahanan: Deteksi Otomatis Kejadian Efek Samping Obat dari Ulasan Pasien Menggunakan BioClinical ModernBERT Nanang Yulian; R. Djoko Andreas Navalino; Linus Yoseph Wawan Rukmono; Riduan Riduan
Journal of Data Insights Vol 4 No 1 (2026): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v4i1.1192

Abstract

Pharmacovigilance is a critical component of post-marketing drug safety, yet conventional adverse drug event (ADE) reporting systems remain constrained by substantial underreporting. In defence health systems, the timely detection of medication-related safety signals is not only a clinical concern but also a matter of force health protection, medical readiness, and operational resilience. Patient-generated health narratives from online forums, drug review platforms, and social media provide a complementary source of pharmacovigilance intelligence, but their informal, unstructured, and context-dependent nature creates significant challenges for automated analysis. This study evaluates BioClinical ModernBERT, a biomedical–clinical long-context encoder based on the ModernBERT architecture, for automatic ADE detection from patient reviews. Its performance is compared with three representative BERT-based transformer baselines: BERT-base, BioBERT, and ClinicalBERT. Experiments were conducted using the CSIRO Adverse Drug Event Corpus (CADEC), a benchmark corpus of patient-reported medication experiences from online health forums. The corpus was pre-processed through sentence segmentation, text cleaning, medical entity normalization, and sentence-level label alignment for binary ADE/non-ADE classification. All models were fine-tuned using a 70:15:15 training, validation, and test split and evaluated using accuracy, precision, recall, and F1-score. The results show that BioClinical ModernBERT achieved the highest overall performance, with an F1-score of 0.891, outperforming ClinicalBERT (0.847), BioBERT (0.832), and BERT-base (0.798). Confusion matrix analysis further indicates that BioClinical ModernBERT reduced false negative errors, particularly in long, multi-clause, and clinically implicit patient narratives. These findings suggest that combining biomedical–clinical domain adaptation with long-context representation provides a meaningful advantage for detecting ADE signals in complex patient-generated text. From a defence health perspective, such capability may support the development of AI-enabled pharmacovigilance surveillance systems that enhance medication safety, health intelligence, and readiness-oriented risk monitoring across civilian–military health ecosystems.
Diplomatic-Domestic Paradox of Indonesian Autonomous Weapons: A Sui Generis Regulatory Model for the KSOT Submarine System Sugiarto; Linus Yoseph Wawan Rukmono; Tivensandro Tivensandro
Lambung Mangkurat Law Journal Vol. 11 No. 1 (2026): March
Publisher : Program magister Kenotariatan Fakultas Hukum Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32801/abc.v11i1.288

Abstract

The development of artificial intelligence-based Autonomous Weapons Systems (AWS) has created significant legal and ethical challenges, particularly for an archipelagic nation like Indonesia, which is modernizing its maritime defense. This study aims to analyze the suitability of AWS use with the principles of Just War Theory, identify regulatory gaps in Indonesian defense law, and formulate an accountable regulatory model. This study employs a normative juridical method, drawing on legislative, conceptual, and comparative approaches. The results show that Indonesia faces a domestic-diplomacy paradox, where Indonesia internationally supports AWS restrictions, but domestically develops systems such as the KSOT-008 autonomous submarine within an inadequate legal framework. Law Number 3 of 2002 and Law Number 3 of 2025 do not explicitly regulate the limits of AWS autonomy and accountability mechanisms, particularly in Military Operations Other Than War, which may create an accountability gap. Furthermore, the limitations of acoustic communication in the underwater domain limit the application of meaningful human control. To address these issues, this study recommends a sui generis regulatory model that includes a ban on fully autonomous systems, expanded command responsibility through the concept of algorithmic mens rea, recognition of institutional responsibility, and the establishment of a national oversight mechanism. This model is expected to ensure that the use of AWS remains in line with the principles of international humanitarian law, legal accountability, and the supremacy of national law.
Co-Authors Irdam Ahmad Jaya, Arie Sukma Moelyanto Moelyanto Nanang Yulian R. DJoko Andreas Navalino Riduan Riduan Riduan Riduan Sa’dianoor Sa’dianoor Sobar Sutisna Sugiarto Sugiarto Sugiarto Syamsul Maarif Tivensandro Tivensandro