Abstract:Abstract: Human metapneumovirus (HMPV) poses a global health threat, but its detection remains challenging due to limited environmental monitoring. This study aims to develop a portable diagnostic tool for rapid HMPV detection…
ection by integrating cutting-edge biotechnology (CRISPR-Cas system and immunoassay) with air quality sensors on an Internet of Things (IoT)-based microfluidic platform controlled by an ESP32 microcontroller. The system is supported by a companion application and data analysis using Vertex AI, and is capable of providing results in less than fifteen minutes. The development results demonstrate the potential for improving detection accuracy and reliability, particularly with further development of virus-specific biosensors, sensor optimization, and algorithms. This technology is effective as a complementary tool for early screening and environment-based risk management in areas with limited laboratory facilities, although it does not completely replace molecular diagnostic methods such as PCR. A rapid diagnostic approach based on environmental sensors, IoT, and artificial intelligence is a promising strategy to improve early HMPV detection, accelerate public health responses, and strengthen respiratory infection prevention through integrated environmental monitoring and education functions.
Keywords: air quality; CRISPR-Cas; Human Metapneumovirus (HMPV); Internet of Things, portable diagnostic; public health; rapid detection; sensors.
Abstrak: Human metapneumovirus (HMPV) merupakan ancaman bagi kesehatan global, namun pendeteksiannya masih sulit akibat keterbatasan pemantauan lingkungan. Studi ini bertujuan mengembangkan alat diagnostik portabel untuk deteksi cepat HMPV melalui integrasi bioteknologi mutakhir (sistem CRISPR-Cas dan immunoassay) dengan sensor kualitas udara pada platform mikrofluida berbasis Internet of Things (IoT) yang dikendalikan mikrokontroler ESP32. Sistem ini didukung aplikasi pendamping dan analisis data menggunakan Vertex AI, serta mampu memberikan hasil dalam waktu kurang dari lima belas menit. Hasil pengembangan menunjukkan potensi peningkatan akurasi dan keandalan deteksi, terutama dengan pengembangan lanjutan berupa biosensor spesifik virus, optimalisasi sensor, dan algoritma. Teknologi ini efektif sebagai alat pelengkap untuk skrining awal dan manajemen risiko berbasis lingkungan di wilayah dengan keterbatasan fasilitas laboratorium, meskipun tidak sepenuhnya menggantikan metode diagnostik molekuler seperti PCR. Pendekatan diagnostik cepat berbasis sensor lingkungan, IoT, dan kecerdasan buatan menjadi strategi menjanjikan untuk meningkatkan deteksi dini HMPV, mempercepat respons kesehatan masyarakat, serta memperkuat pencegahan infeksi saluran pernapasan melalui fungsi pemantauan dan edukasi lingkungan yang terintegrasi.
Kata kunci: CRISPR-Cas; diagnostik portabel; deteksi cepat; Human Metapneumovirus (HMPV); kesehatan masyarakat; IoT (Internet of Things); sensor kualitas udara.
Abstract:Abstract: The rapid degradation of mangrove ecosystems threatens coastal biodiversity, shoreline stability, and carbon sequestration capacity, particularly in areas experiencing intense human activity. However, community-based…
-based participatory mangrove monitoring remains limited due to the lack of accessible and user-friendly digital tools. This study aims to design an intuitive mobile application for mangrove tree detection and participatory ecological monitoring using a User-Centered Design (UCD) approach. The research was conducted iteratively through user needs analysis, prototype development, and usability evaluation involving local governments, conservation practitioners, and non-expert users. The proposed application integrates machine learning for automated mangrove recognition with geospatial visualization and real-time feedback to support field-based monitoring. Usability evaluation using the System Usability Scale (SUS) yielded an overall score of 82.3, categorized as excellent usability, indicating high user satisfaction and intuitive interaction. The results demonstrate that integrating UCD and machine learning enhances usability, user engagement, and the accuracy of mangrove documentation under real field conditions. Overall, this study presents a field-ready, user-centered mobile solution that bridges usability engineering and participatory mangrove monitoring as a replicable model for inclusive ecological application development.
Keywords: Carbon sequestration; mangrove monitoring; mobile application; user-centered design; usability evaluation
Abstrak: Degradasi ekosistem mangrove yang semakin cepat mengancam keanekaragaman hayati pesisir, stabilitas garis pantai, dan kapasitas sekuestrasi karbon, terutama di wilayah dengan aktivitas manusia yang intens. Namun, pemantauan mangrove secara partisipatif berbasis komunitas masih terbatas akibat kurangnya perangkat digital yang mudah diakses dan ramah pengguna. Penelitian ini bertujuan merancang aplikasi mobile yang intuitif untuk deteksi pohon mangrove dan pemantauan ekologi partisipatif dengan menggunakan pendekatan User-Centered Design (UCD). Penelitian dilakukan secara iteratif melalui analisis kebutuhan pengguna, pengembangan prototipe, dan evaluasi kegunaan dengan melibatkan pemerintah daerah, praktisi konservasi, serta pengguna non-ahli. Aplikasi yang diusulkan mengintegrasikan pembelajaran mesin untuk pengenalan mangrove secara otomatis dengan visualisasi geospasial dan umpan balik waktu nyata guna mendukung pemantauan di lapangan. Evaluasi kegunaan menggunakan System Usability Scale (SUS) menghasilkan skor keseluruhan sebesar 82,3 yang termasuk dalam kategori kegunaan sangat baik, menunjukkan tingkat kepuasan pengguna yang tinggi dan interaksi yang intuitif. Hasil penelitian menunjukkan bahwa integrasi UCD dan pembelajaran mesin meningkatkan kegunaan, keterlibatan pengguna, serta akurasi dokumentasi mangrove dalam kondisi lapangan. Secara keseluruhan, penelitian ini menyajikan solusi mobile berbasis UCD yang siap digunakan di lapangan dan menjembatani rekayasa kegunaan dengan pemantauan mangrove partisipatif sebagai model replikatif bagi pengembangan aplikasi ekologi yang inklusif.
Kata kunci: Carbon sequestration; mangrove monitoring; mobile application; user-centered design; usability evaluation
Abstract:Abstract: In the era of the Internet of Things (IoT), cyber threats are increasingly complex and dynamic, thus demanding an adaptive and intelligent network security system. This study proposes a Convolutional Neural Network…
work (CNN)-based Intrusion Detection System (IDS) implemented through a Federated Learning (FL) approach in a Non-Independent and Identically Distributed (Non-IID) data environment. This approach allows the model to be trained in a distributed manner across multiple IoT devices without having to collect sensitive data to a central server, thereby maintaining data privacy while increasing the efficiency of the training process. The experiment used the CIC IoT 2023 dataset, which represents various modern IoT network traffic patterns. The results show that the proposed CNN–FL model achieves an overall accuracy of 0.99, with excellent performance in detecting various types of network traffic. The model obtains a perfect recall value (1.00) for normal traffic (Benign), as well as a very high F1-score for DDoS (0.99) and DoS (0.99) attacks. Stable and consistent performance across all five federation rounds demonstrates that this approach is a reliable, efficient, and accurate solution for detecting threats in distributed and privacy-preserving IoT networks.
Keywords: cnn; federated_learning; ids; non-iid; ciciot2023
Abstrak: Dalam era Internet of Things (IoT), ancaman siber semakin kompleks dan dinamis, sehingga menuntut sistem keamanan jaringan yang adaptif dan cerdas. Penelitian ini mengusulkan Intrusion Detection System (IDS) berbasis Convolutional Neural Network (CNN) yang diterapkan melalui pendekatan Federated Learning (FL) pada lingkungan data yang bersifat Non-Independent and Identically Distributed (Non-IID). Pendekatan ini memungkinkan model dilatih secara terdistribusi di berbagai perangkat IoT tanpa harus mengumpulkan data sensitif ke server pusat, sehingga mampu menjaga privasi data sekaligus meningkatkan efisiensi proses pelatihan. Eksperimen menggunakan dataset CIC IoT 2023, yang merepresentasikan berbagai pola lalu lintas jaringan IoT modern. Hasil penelitian menunjukkan bahwa model CNN–FL yang diusulkan mencapai akurasi keseluruhan sebesar 0.99, dengan performa yang sangat baik dalam mendeteksi berbagai jenis lalu lintas jaringan. Model memperoleh nilai recall sempurna (1.00) untuk lalu lintas normal (Benign), serta nilai F1-score yang sangat tinggi untuk serangan DDoS (0.99) dan DoS (0.99). Kinerja yang stabil dan konsisten di seluruh lima putaran federasi membuktikan bahwa pendekatan ini merupakan solusi yang andal, efisien, dan akurat untuk mendeteksi ancaman pada jaringan IoT yang bersifat terdistribusi dan menjaga privasi (privacy-preserving).
Kata kunci: cnn; federated_learning; ids; non-iid; ciciot2023
Abstract:Abstract: Uterine disease is a serious threat to women's health, which can affect fertility and quality of life. Delayed diagnosis often results in patients not getting optimal early treatment at the H. Abdul Manan Simatupang…
upang Kisaran Regional General Hospital. This study aims to develop a fuzzy logic-based expert system to diagnose uterine disease based on the symptoms experienced by patients. This system receives symptom data as input, then performs analysis using the fuzzy logic method to determine the level of possibility of a disease. The final results produced are an initial diagnosis and treatment recommendations. System testing shows that this method is able to identify uterine disease with fairly good accuracy, where one case showed the possibility of Endometriosis with a confidence level of 63%. With this system, patients can obtain initial information about their health condition, so they can take more appropriate and faster medical steps.
Keywords: expert system; fuzzy logic; uterine disease.
Abstrak: Penyakit rahim merupakan ancaman serius bagi kesehatan wanita, yang dapat berdampak pada kesuburan dan kualitas hidup. Keterlambatan diagnosis sering kali menyebabkan pasien tidak mendapatkan penanganan dini yang optimal di Rumah Sakit Umum Daerah H. Abdul Manan Simatupang Kisaran. Penelitian ini bertujuan untuk mengembangkan sistem pakar berbasis logika fuzzy guna mendiagnosis penyakit rahim berdasarkan gejala yang dialami pasien. Sistem ini menerima data gejala sebagai input, kemudian melakukan analisis menggunakan metode logika fuzzy untuk menentukan tingkat kemungkinan suatu penyakit. Hasil akhir yang dihasilkan berupa diagnosis awal dan rekomendasi penanganan. Pengujian sistem menunjukkan bahwa metode ini mampu mengidentifikasi penyakit rahim dengan akurasi yang cukup baik, di mana salah satu kasus menunjukkan kemungkinan penyakit Endometriosis dengan tingkat kepercayaan sebesar 63%. Dengan adanya sistem ini, pasien dapat memperoleh informasi awal mengenai kondisi kesehatannya, sehingga dapat mengambil langkah medis yang lebih tepat dan cepat.
Kata kunci: fuzzy logic; penyakit rahim; sistem pakar.
Abstract:Abstract: The advancement of network security faces growing challenges as cyberattacks become more sophisticated. Traditional rule-based systems struggle with zero-day attacks and obfuscation techniques. This study examines…
nes the development trends of AI-based algo-rithms, particularly machine learning and deep learning, in threat detection. A literature review evaluates AI-driven approaches, including support vector machines, random for-est, deep neural networks, convolutional neural networks, and reinforcement learning. Findings show that AI enhances detection accuracy, adaptability, and reduces false posi-tives. Machine learning efficiently classifies known attacks, while deep learning excels in identifying complex patterns such as distributed denial-of-service and advanced persis-tent threats. Unsupervised learning improves anomaly detection without labeled data. However, AI models require high-quality data, substantial computational resources, and remain vulnerable to adversarial attacks. Despite these challenges, AI provides a dynam-ic and adaptive security solution, surpassing traditional systems. Future research should enhance AI scalability and resilience for evolving cybersecurity threats.
Keywords: anomaly detection; artificial intelligence; deep learning; machine learning; network security
Abstrak: Perkembangan keamanan jaringan menghadapi tantangan yang semakin besar seiring meningkatnya kompleksitas serangan siber. Sistem berbasis aturan tradisional kesulitan mendeteksi zero-day attack dan teknik penyamaran. Penelitian ini mengkaji tren pengembangan algoritma berbasis AI, khususnya machine learning dan deep learning, dalam deteksi ancaman. Literature review mengevaluasi pendekatan berbasis AI, termasuk support vector machines, random forest, deep neural networks, convolutional neural networks, dan reinforcement learning. Hasil penelitian menunjukkan bahwa AI meningkatkan akurasi deteksi, adaptabilitas terhadap ancaman baru, serta mengurangi false positive. Machine learning efektif mengklasifikasikan serangan yang telah diketahui, sementara deep learning unggul dalam mengenali pola kompleks seperti distributed denial-of-service dan advanced persistent threats. Unsupervised learning meningkatkan deteksi anomali tanpa memerlukan data berlabel. Namun, AI masih bergantung pada data berkualitas tinggi, sumber daya komputasi besar, dan rentan terhadap adversarial attack. Meskipun demikian, AI menawarkan solusi keamanan yang lebih dinamis dan adaptif dibandingkan sistem tradisional. Penelitian selanjutnya perlu difokuskan pada peningkatan skalabilitas dan ketahanan AI dalam menghadapi ancaman siber yang terus berkembang.
Kata kunci: deteksi anomali; jaringan keamanan; kecerdasan buatan; pembelajaran dalam; pembelajaran mesin
Abstract:Abstract: Cyberattacks like SQL injection and syn flood attacks can threaten the information system security of an organisation or company. The Intrusion Detection and Prevention System (IDPS) is used as a solution to detect,…
tect, prevent, and respond to these attacks. However, the effectiveness of IDPS in protecting information systems needs to be evaluated through performance analysis. IDPS performance analysis for mitigating SQL injection and syn flood attacks will use Suricata tools, where performance analysis will include evaluation of system accuracy and efficiency in detecting attacks, as well as the impact of the system on network or information system performance. By doing this performance analysis, it can be seen how effective the IDPS is in providing defences against such attacks. The results of the IDPS performance analysis can help an organisation or company select and implement the right IDPS according to the needs and conditions of the information system. Thus, organisations or companies can improve the security of their information systems from threatening cyber attacks.
Keywords: IDPS; SQL_Injection; Suricata; Syn_Flood_Attack
Abstrak: Serangan cyber seperti SQL Injection dan Syn Flood Attack dapat mengancam keamanan sistem informasi suatu organisasi atau perusahaan. Intrusion Detection and Prevention System (IDPS) digunakan sebagai solusi untuk mendeteksi, mencegah, dan merespons serangan-serangan ini. Namun, efektivitas IDPS dalam melindungi sistem informasi perlu dievaluasi melalui analisis performa. Analisis performa IDPS untuk mitigasi SQL Injection dan Syn Flood Attack ini akan menggunakan tools suricata dimana analisa performa akan meliputi evaluasi terhadap akurasi dan efisiensi sistem dalam mendeteksi serangan, serta dampak dari sistem terhadap kinerja jaringan atau sistem informasi. Dengan melakukan analisis performa ini, dapat diketahui seberapa efektif IDPS dalam memberikan perlindungan terhadap serangan-serangan tersebut. Hasil dari analisis performa IDPS dapat membantu organisasi atau perusahaan dalam memilih dan mengimplementasikan IDPS yang tepat sesuai dengan kebutuhan dan kondisi sistem informasi yang dimiliki. Dengan demikian, organisasi atau perusahaan dapat meningkatkan keamanan sistem informasi mereka dari serangan-serangan cyber yang mengancam.
Kata kunci: IDPS; SQL_Injection; Suricata; Syn_Flood_Attack
Abstract:Abstract: The background of this research is that some of the risks of using technology that are classified as dangerous are often ignored by users of the monitoring system for learning activities at private universities…
so that there are several obstacles such as not being able to open the system because the system is hacked by irresponsible parties, the computer network used is often disrupted so that hampers the operational process, and the level of computer security is still relatively weak. This study aims to measure the likelihood of threats and risk impacts on the teaching and learning activity monitoring system and to provide recommendations for risk control of security problems that could become a threat that causes losses to universities. The framework used as a tool to measure the level of threat and risk impact is to use the NIST Special Publication 800-30r-1 framework. The framework of the NIST Special Publication 800-30r-1 has nine phases in carrying out risk assessments, namely introduction of system characteristics, recognition of threats, recognition of vulnerabilities, analysis of handling systems, determining likelihood, determining impact, risk determination, recommending control and determination of results. There are six risk assessment systems for monitoring learning activities at private universities, two of which are high so they are classified as very dangerous and the rest are moderate. The results of this study are used as a reference in making risk control standard documents as a form of improving the quality of a private university.
Keywords: Monitoring System; NIST Spesial Publication 800-30r1; Risk Assessment.
Abstrak: Latarbelakang penelitian ini adalah resiko penggunaan teknologi yang tergolong berbahaya sering tidak dihiraukan oleh pengguna sistem monitoring kegiatan belajar pada perguruan tinggi swasta sehingga terjadi beberapa kendala seperti tidak bisa membuka sistem karena sistem diretas oleh pihak yang tidak bertanggung jawab, jaringan komputer yang digunakan sering terganggu sehingga menghambat proses operasional, serta tingkat keamanan komputer yang masih tergolong lemah. Penelitian ini mempunyai tujuan yaitu mengukur seberapa besar kemungkinan terjadi ancaman dan dampak resiko terhadap sistem monitoring kegiatan belajar mengajar serta memberikan rekomendasi pengendalian resiko dari permasalahan keamanan yang bisa menjadi suatu ancaman yang menimbulkan kerugian pada perguruan tinggi. Framework yang digunakan sebagai alat untuk mengukur tingkat ancaman dan dampak resiko adalah menggunakan kerangka kerja NIST Special Publication 800-30r-1. Kerangka kerja NIST Special Publication 800-30r-1 ini mempunyai sembilan fase dalam melakukan penilaian resiko yaitu pengenalan karakteristik sistem, pengenalan ancaman, pengenalan kerentanan, analisis penanganan sistem, menentukan kemungkinan terjadi (likelihood), menentukan dampak (impact), risk determination, merekomendasikan pengendalian dan penetapan hasil. Penilaian resiko sistem monitoring kegiatan belajar pada perguruan tinggi swasta ada enam resiko yang dua diantaranya termasuk tinggi sehingga digolongkan sangat berbahaya dan selebihnya termasuk sedang. Hasil dari penelitian ini digunakan sebagai acuan dalam pembuatan dokumen standar pengendalian resiko sebagai bentuk peningkatan mutu suatu perguruan tinggi swasta.
Kata kunci: NIST Spesial Publication 800-30r; Penilaian Resiko; Sistem Monitoring
Abstract:Abstract: Negotiations in the release of hostages are the most important way in a rescue mission for hostages. If the officer is wrong in taking action in the negotiation process, the effect that can be caused is the safety…
ety threat of both the officer or personnel in charge and the safety of the hostage victims. The reason is the ineffectiveness of communication so that it always results in a shootout to complete the abduction. And the problem is resolved without communication between criminals and personnel. In this case, we designed a negotiating robot equipped with weapons so that the safety and security of the officers would also be a concern in carrying out their duties, both in the task of war against the enemy and in the task of freeing hostages. and officers who are responsible for the safety of the victims being taken hostage. With this military robot, the monitoring can help military members or personnel in negotiating and monitoring without having to sacrifice lives.
Keywords: Arduino; FPV; GPS ;Robot; Sensor.
Abstrak: Negosiasi dalam pembebasan sandera merupakan cara terpenting dalam sebuah misi penyelamatan sandera, Jika petugas salah dalam mengambil tindakan dalam proses negosiasi maka efek yang dapat ditimbulkan adalah ancaman keselamatan baik petugas atau personil yang berwajib maupun keselamatan dari pihak korban yang disandera. Penyebabnya adalah tidak efektifnya komuniskasi sehingga mengakibatkan selalu terjadinya baku tembak untuk menyelesaikan penyandraan tersebut. Dan masalah terselesaikan tanpa ada komunikasi antara penjahat dan personil. Dalam hal tersebut kami merancang sebuah robot negosiasi yang dilengkapi dengan senjata agar keselamatan dan keamanan petugas juga menjadi perhatian dalam menjalankan tugas, baik dalam tugas perang melawan musuh maupun dalam tugas pembebasan sandera.Dalam hal pembebasan sandera perlu dilakukan berbagai cara agar mendapatkan kesepakatan terbaik antara musuh dan petugas yang berwajib guna keselamatan korban yang disandera. Dengan adanya robot militer pemantau ini dapat membantu anggota atau personil militer dalam melakukan negosiasi dan pemantauan tanpa harus mengorbankan nyawa.
Kata kunci: Arduino; FPV; GPS; Robot; Sensor.
Abstract:The teaching profession plays a strategic role in advancing national education, as mandated by the 1945 Constitution of the Republic of Indonesia. However, teachers frequently face challenges, including threats of physical…
al violence from students’ parents, which undermine their dignity and safety in the educational environment. This study addresses the problem of how legal frameworks provide protection for teachers and whether existing regulations adequately ensure their rights and security. The research aims to analyze the effectiveness of legal protection for teachers under the Criminal Code, Law No. 14 of 2005 on Teachers and Lecturers, Law No. 35 of 2014 on Child Protection, and Ministerial Regulations concerning teacher protection. The study employs a normative juridical method with a statute, conceptual, and case approach, relying on primary, secondary, and tertiary legal materials, analyzed through qualitative interpretation and juridical argumentation. The results indicate that although legal instruments exist, their implementation remains weak due to the absence of technical regulations, limited institutional coordination, and insufficient support systems for teachers at the school level. The study concludes that derivative regulations and integrated mechanisms are essential for ensuring effective protection. It recommends strengthening inter-agency coordination, establishing school-level protection units, and enhancing teachers’ legal literacy.
Abstract:Justice collaborators, or "crown witnesses," have become essential in modern criminal justice systems, particularly in dismantling organized crime and uncovering complex murder cases. This study explores the legal protections…
tions afforded to justice collaborators in Indonesia through a doctrinal analysis of the Supreme Court Decision No. 1704 K/PID.SUS/2022, commonly known as the Richard Eliezer verdict. The objective is to critically examine the adequacy and application of legal safeguards provided to individuals who cooperate with law enforcement while implicated in serious crimes. Employing normative legal research methods and a statutory and case approach, the paper reveals discrepancies in the implementation of protections for justice collaborators. While the Indonesian Witness and Victim Protection Agency (LPSK) offers procedural protections, this analysis identifies significant gaps in enforcement, judicial interpretation, and institutional coordination. The findings underscore a need for stronger legislative frameworks and consistent judicial standards to uphold the rights and safety of justice collaborators. The implications extend to criminal law reform and the balancing of retributive justice with restorative mechanisms. This study contributes to the legal discourse on human rights protections in criminal procedure, particularly concerning vulnerable individuals assisting the justice system under duress or threat.