Article Per Year (5 Year)
p-Index From 2021 - 2026
2.926
P-Index
This Author published in this journals
All Journal CESS (Journal of Computer Engineering, System and Science) JMM (Jurnal Masyarakat Mandiri) JURNAL INSTEK (Informatika Sains dan Teknologi) INTEK: Jurnal Penelitian MONSU'ANI TANO Jurnal Pengabdian Masyarakat Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Matematika UNAND Building of Informatics, Technology and Science Jurnal Pengabdian UNDIKMA Journal of System and Computer Engineering Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal Sains dan Kesehatan
Muh Ikhsan Amar
Institut Teknologi Bacharuddin Jusuf Habibie
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 17 Documents
Search

 1   2 
A Deterministic Mathematical Model of Meningitis Transmission Dynamics with Vaccination and Screening Amar, Muh Ikhsan; Nisardi, Muhammad Rifki; Nurahmad, Muhammad Fadhil
Jurnal Matematika UNAND Vol. 14 No. 1 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.1.14-30.2025

Abstract

This study aims to examine the mathematical model of meningitis transmission as a deterministic model. The model includes five compartments: susceptible (S), carrier (C), infected (I), treatment (T), and recovered (R). We also consider vaccination and screening as interventions in disease transmission. In this work, we obtained two equilibrium points: disease-free equilibrium point and endemic equilibrium point. The next generation matrix is employed to compute the basic reproduction numbers ($R_0$). We also analyzed the sensitivity of parameters concerning $R_0$. If $R_0 < 1$, then the disease-free equilibrium point exists and is locally stable, whereas the endemic equilibrium point exists when $R_0 > 1$ and is locally stable if the Routh-Hurwitz criterion is satisfied. We use the Runge-Kutta 4th order method to confirm the stability properties of the equilibrium points and also show that vaccination and screening affect the transmission dynamics of Meningitis
PENDAMPINGAN BIDAN MELALUI PELATIHAN PEMBUATAN PERANGKAT EDUKASI DENGAN MENGGUNAKAN TEKNOLOGI AUGMENTED REALITY DALAM PENINGKATAN KEMAMPUAN MENGGUNAKAN TEKNOLOGI Jumrah Sudirman; Stang Stang; Muh. Ikhsan Amar; Suriani B.
JMM (Jurnal Masyarakat Mandiri) Vol 7, No 5 (2023): Oktober
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v7i5.17045

Abstract

Abstrak: Upaya untuk meningkatkan pengetahuan tentang pencegahan dan faktor resiko berbagai penyakit dan kondisi yang ada di masyarakat adalah dengan melakukan edukasi menggunakan media interaktif. Kegiatan pengabdian ini dilakukan untuk melakukan pelatihan kepada bidan sebagai Upaya meningkatkan kemampuan bidan dalam mendesain media edukasi dengan teknologi Augmented Reality. Pelaksanaan Kegiatan dilakukan secara hybrid, dimana peserta mengikuti secara online sebanyak 40 peserta dan yang mengikuti secara online sebanyak 260 peserta. Metode yang digunakan adalah ceramah, diskusi dan simulasi. Pelaksaan kegiatan ini bermitra dengan Pengurus Daerah IBI Provinsi Sulawesi Selatan. Hasil yang didapatkan menunjukkan peserta yang mengisi postes sebanyak 252 orang, dimana 73.01% peserta telah memiliki pengetahuan yang baik. Kegiatan terlaksanan dengan tertib sesuai rencana kegiatan.Abstract: Efforts to increase knowledge about prevention and risk factors for various diseases and conditions that exist in the community are by conducting education using interactive media. This service activity is carried out to conduct training for midwives as an effort to improve the ability of midwives in designing educational media with Augmented Reality technology. The implementation of the activity was carried out in a hybrid manner, where as many as 40 participants took part online and 260 participants took part online. The methods used are lectures, discussions and simulations. The implementation of this activity partnered with the IBI Regional Management of South Sulawesi Province. The results obtained showed that there were 252 participants who filled out the posttest, of which 73.01% of the participants had good knowledge. Activities carried out in an orderly manner according to the activity plan.
Analisis Model Klasifikasi Penerima Bantuan Langsung Tunai Menggunakan Algoritma Naive Bayes Amar, Muh. Ikhsan; Muh. Faizal Rajib
CESS (Journal of Computer Engineering, System and Science) Vol. 10 No. 2 (2025): Juli 2025
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v10i2.67178

Abstract

Bantuan Langsung Tunai (BLT) menjadi salah satu kebijakan Pemerintah dalam memenuhi hak jaminan sosial masyarakat. Penyaluran BLT didasarkan untuk membantu masyarakat miskin agar dapat tetap memenuhi kebutuhannya sehingga menjadi stimulus dalam mempercepat pemulihan ekonomi nasional. Namun dalam implementasinya, proses penyaluran penerima BLT kerap menimbulkan subjektifitas dan keakuratan data yang rendah, sehingga tidak menyentuh secara optimal kepada penerima manfaat, yang berpotensi mempengaruhi stabilitas sosial. Penelitian ini bertujuan untuk melakukan analisis dan perancangan model untuk sistem klasifikasi penerima Bantuan Lansung Tunai (BLT). Penelitian ini menggunakan konsep Machine Learning dengan menerapkan algoritma Naïve Bayes, yang diklasifikasi kedalam tiga parameter kriteria yaitu sangat layak, layak, dan tidak layak. Penerapan model dilakukan dengan menggunakan dataset masyarakat Kecamatan Citta Kabupaten Soppeng. Jumlah data yang digunakan sebanyak 8.046 record sesuai dengan jumlah penduduk Kecamatan Citta yang diperoleh dari BPS Kabupaten Soppeng dan pendataan langsung di lapangan. Dari hasil pengujian model, diperoleh hasil nilai Accuracy sebesar 88.89%, nilai Precision sebesar 89% Recall sebesar 89% dan nilai F1-Score sebesar 89%. 
Pelatihan Pemanfaatan Teknologi Augmented Reality dan Virtual Reality Sebagai Media Pembelajaran Inovatif bagi Guru di SMP Negeri 10 Parepare Rafrin, Mardhiyyah; Maharani, Putri Ayu; Muh. Agus; Amar, Muh. Ikhsan; Intizhami, Naili Suri; Nuranti B, Eka Qadri; Bahar, Nur Aini Sri Oktaviani; Armansyah, Muhammad Dicky; S., St. Aisyah; Kandi, Damar; Malika, Saphira Nur
Jurnal Pengabdian UNDIKMA Vol. 6 No. 4 (2025): November
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v6i4.18210

Abstract

This community service program aims to enhance teachers’ skills in utilizing AR and VR technologies as innovative instructional media in the classroom. The program was implemented using a structured training model involving 20 teachers from SMPN 10 Parepare. The evaluation instrument consisted of a questionnaire, and the responses were analyzed using descriptive techniques. The results show that the training was highly aligned with teachers’ needs at the school (average response score: 4.75), easy to follow (4.66), very beneficial in improving the quality of learning (4.85), and motivating for teachers to adopt AR and VR technologies in their instructional practices (4.58). Overall, this training activity provided a significant contribution to enhancing teachers’ digital literacy, particularly in the use of innovative learning media.
ANALISIS REVERSE ENGINEERING MALWARE WINRAR SFX MENGGUNAKAN GHIDRA UNTUK DETEKSI TEKNIK OBFUSCATION DAN UAC BYPASS Rosmiati; Muh. Ikhsan Amar; Muhammad Arham Arsyad
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 10 No 2 (2025): OCTOBER
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v10i2.60503

Abstract

Ancaman malware yang semakin kompleks dan sulit dideteksi menuntut pendekatan analisis yang lebih mendalam dalam keamanan siber. Penelitian ini bertujuan untuk menganalisis efektivitas penerapan reverse engineering berbasis analisis statis dalam mendeteksi dan mengklasifikasikan malware. Parameter keberhasilan analisis diukur melalui kemampuan mengidentifikasi struktur PE abnormal, deteksi API mencurigakan, indikasi teknik evasion, serta klasifikasi tingkat ancaman (threat level). Sampel malware diperoleh dari platform MalwareBazaar dan dianalisis menggunakan PE Studio, Detect It Easy, Strings, dan Ghidra. Tahapan penelitian meliputi ekstraksi metadata, identifikasi API call, disassembly, serta deteksi teknik packing dan obfuscation. Hasil analisis menunjukkan bahwa malware menyamarkan diri sebagai aplikasi sah (WinRAR SFX), menggunakan command-line injection, bypass UAC, dan teknik obfuscation lanjutan untuk menghindari deteksi. Ditemukan pula indikasi teknik evasif seperti anti-debugging dan komunikasi antar-proses melalui shared memory. Berdasarkan parameter keberhasilan tersebut, pendekatan analisis statis dengan Ghidra terbukti mampu mengungkap pola perilaku malware tingkat menengah secara efektif. Temuan ini menegaskan pentingnya reverse engineering dalam mendeteksi ancaman malware sejak tahap awal tanpa perlu menjalankan kode berbahaya.
Investigating LOLBAS-Based Malware Using Hybrid Analysis: A Case Study of PowerShell-Driven Fileless Execution Rosmiati Rosmiati; Muh. Ikhsan Amar; Muhammad Arham Arsyad; Hariani Hariani
Journal of System and Computer Engineering Vol 7 No 2 (2026): JSCE: April 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i2.2623

Abstract

This study aims to identify and understand the technical characteristics of the malware output.exe, obtained from the MalwareBazaar repository, through a hybrid reverse engineering approach. This method combines static and dynamic analyses to provide a comprehensive understanding of the malware’s internal structure, execution behavior, and evasion techniques. Static analysis revealed the invocation of system functions such as CreateProcessW and RegSetValueExA, as well as the use of syscall to execute PowerShell commands directly, indicating the implementation of the LOLBAS (Living off the Land Binaries and Scripts) technique. Dynamic analysis using CAPE Sandbox confirmed the malware’s actual behavior, including process injection into legitimate processes such as svchost.exe, launching powershell.exe for data compression, and establishing network communication via Discord Webhook for data exfiltration. Integration of both analyses shows that output.exe functions as an information stealer with fileless execution and advanced persistence mechanisms. These findings demonstrate that the hybrid analysis approach is effective in identifying modern malware that leverages legitimate system components to evade traditional signature-based detection methods.
Attention-Driven Contrastive Learning for the Identification of Rare Partial Discharge Signal in GIS Muhaimin Hading; Herviana Herviana; Muh. Ikhsan Amar; A. Syahrinaldy Syahruddin; Muhammad Irsan; Aulia Salsabila R.H
Journal of System and Computer Engineering Vol 7 No 3 (2026): JSCE: July 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i3.2664

Abstract

Gas-insulated switchgear (GIS) is a critical component in high-voltage power transmission systems, where partial discharge (PD) activity can indicate early-stage insulation defects. However, phase-resolved partial discharge (PRPD)-based fault diagnosis remains challenging due to noisy signals, perturbed measurement conditions, and severe class imbalance, particularly for rare floating-electrode defects. This study proposes an attention-driven contrastive learning framework for rare PD signal identification in GIS. PRPD data are represented as two-dimensional density matrices derived from phase angle, discharge magnitude, and occurrence count. The proposed framework applies PRPD-specific data augmentation, followed by ResUNet-based denoising, CBAM-based feature refinement, and supervised contrastive learning to improve feature separability among PD classes. The framework was evaluated using a public 550 kV GIS PRPD dataset containing corona-type, surface-type, floating-electrode-type, and noise classes. The results show that augmentation substantially improved robustness. When trained with raw data, the proposed model achieved 91.90% accuracy and 53.81% F1-score under the original test scenario, but decreased to 48.76% accuracy and 46.26% F1-score under IEC-perturbed testing. After augmentation, the model achieved 98.24% accuracy and 96.58% F1-score under the original scenario, and maintained 97.44% accuracy and 97.76% F1-score under IEC perturbation. These findings indicate that the proposed framework supports robust PRPD representation learning for GIS PD diagnosis under perturbed and imbalanced conditions.
Co-Authors A. Anwar Ishar A. Syahrinaldy syahruddin Abdul Zain Aminuddin Aminuddin Ariana Asri Armansyah, Muhammad Dicky Aulia Salsabila R.H Awaluddin Awaluddin Bahar, Nur Aini Sri Oktaviani Cakrawijaya, Muhammad Hidayat DA, Alvian Tri Putra Eka Qadri Nuranti Elisabeth Tri Juliana Kandakon Fatimah Fatimah FERAWATI Firmansyah Dahlan Hading, Muhaimin Hariani Herviana Herviana Imansyah, Nur Jumarti Suhaela Jumrah Sudirman Kandi, Damar Maharani, Putri Ayu Malika, Saphira Nur Mardhiyyah Rafrin, S.T., M.Sc. Mirfaidah Nadjamuddin Muh. Agus Muh. Faizal Rajib Muhammad Arham Arsyad Muhammad Arham Arsyad Muhammad Erwin Arif Muhammad Fadel Hasyim Muhammad Irsan Muhammad Irsyad Erlangga Muhammad Mukram Mustamin Muhammad Rifki Nisardi Muhammad Sofyan Daud Pujas Naili Suri Intizhami Naili Suri Intizhami, S.Kom., M.Kom. Nurahmad, Muhammad Fadhil Nuranti B, Eka Qadri Prof. Dr. Ir. Indar Chaerah Gunadin, ST.,MT.,IPM Putri Ayu Maharani, S.T., M.Sc. Putriani, Andi Ika Rafdah Pritama Saputri Rafrin, Mardhiyyah Ramdana, Ramdana Resky, Aprizal Risnawati Rosmiati Rosmiati Rusli, Kurnia S., St. Aisyah Stang Stang Suriani B Wahyuni Wahyuni