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All Journal Jusikom : Jurnal Sistem Komputer Musirawas Martabe : Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Jurnal Software Engineering and Computational Intelligence Media Journal of General Computer Science (MJGCS)
Muhammad Sulkhan Nurfatih
Universitas Serelo Lahat
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Social Sciences

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Designing consensus algorithm for collaborative signature-based intrusion detection system Eko Arip Winanto; Mohd Yazid Idris; Deris Stiawan; Mohammad Sulkhan Nurfatih
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp485-496

Abstract

Signature-based collaborative intrusion detection system (CIDS) is highly depends on the reliability of nodes to provide IDS attack signatures. Each node in the network is responsible to provide new attack signature to be shared with other node. There are two problems exist in CIDS highlighted in this paper, first is to provide data consistency and second is to maintain trust among the nodes while sharing the attack signatures. Recently, researcher find that blockchain has a great potential to solve those problems. Consensus algorithm in blockchain is able to increase trusts among the node and allows data to be inserted from a single source of truth. In this paper, we are investigating three blockchain consensus algorithms: proof of work (PoW), proof of stake (PoS), and hybrid PoW-PoS chain-based consensus algorithm which are possibly to be implemented in CIDS. Finally, we design an extension of hybrid PoW-PoS chain-based consensus algorithm to fulfill the requirement. This extension we name it as proof of attack signature (PoAS).
Build Up Aplikasi Verifikasi Kemurnian Balok Karet dengan Whale Optimization Algorithm Firza Septian; Muhammad Sulkhan Nurfatih
Jurnal Software Engineering and Computational Intelligence Vol 2 No 01 (2024)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v2i01.4146

Abstract

The rubber industry requires precise quality control of rubber blocks to maintain product consistency and customer satisfaction. This study develops an application to verify the purity of rubber blocks using the Whale Optimization Algorithm (WOA). The application aims to provide an accurate, efficient, and automated solution for detecting impurities. Inspired by the bubble-net hunting strategy of humpback whales, WOA is effective in solving complex optimization problems. In this research, WOA optimizes parameters for impurity detection, enhancing verification accuracy. The application integrates image processing techniques and machine learning algorithms. Images of rubber blocks are captured and processed to extract relevant features, which are then analyzed using WOA to identify impurities. Extensive testing demonstrated that the application achieves high accuracy in impurity detection, outperforming traditional methods. The use of WOA significantly reduces processing time, making the application suitable for real-time industrial verification. This study highlights the potential of the Whale Optimization Algorithm to improve quality control processes in the rubber industry. The developed application offers a reliable and efficient tool for ensuring rubber block purity, thereby enhancing product quality and operational efficiency.
Analysis of Accreditation's Impact on Student Numbers in South Sumatra Private Universities Using K-Means Clustering Muhammad Sulkhan Nurfatih; Yusi Nurmalasari; Agustian Prakarsyah
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.23

Abstract

Private universities in Indonesia are essential in meeting the educational needs of the country's increasing number of students. Among the key determinants of student enrollment is the accreditation status of these institutions. This study investigates how accreditation status influences student numbers at private universities in South Sumatra, employing the K-Means clustering method for analysis. Data from various institutions across South Sumatra were collected and analyzed, revealing distinct patterns in how universities are grouped based on their accreditation and enrollment figures. The findings shed light on the significant relationship between accreditation status and student enrollment, offering valuable insights for policymakers and university administrators. These insights can inform the development of effective student admission strategies, ultimately contributing to the growth and success of private universities in the region. This research not only highlights the importance of accreditation but also provides a comprehensive understanding of the factors driving student growth at private universities in South Sumatra.
AI-OPTIMIZATION FOR LESSON PLANNING TO ADDRESS STUDENT PSYCHOLOGY GAPS IN ELEMENTARY SCHOOLS Nurfatih, Muhammad Sulkhan; Zikry, Arief
Jusikom : Jurnal Sistem Komputer Musirawas Vol 9 No 2 (2024): Jusikom : Jurnal Sistem Komputer Musirawas DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusikom.v9i2.2393

Abstract

This study aims to optimize the use of artificial intelligence technology, specifically GPT (Generative Pre-trained Transformer), in creating personalized lesson plans (RPP) tailored to the psychology and learning styles of students at SD Negeri 2 Muara Enim. The use of GPT is expected to assist teachers in understanding the individual psychological needs of students, addressing the limitations of counseling services at the school. The research methodology includes three main phases: analysis, system design, and implementation. During the analysis phase, demographic, academic, psychological, and contextual data of students were collected to identify key correlations influencing academic performance. This data was then used to train a machine learning model using the k-means clustering algorithm, aimed at grouping students based on their learning characteristics. The findings indicate that GPT was successfully implemented to generate lesson plans aligned with students' psychological profiles and learning styles. The developed web-based system enables teachers to effectively personalize the learning process. Moreover, the application simplifies the lesson plan creation process by offering teaching strategy recommendations relevant to each student group. In conclusion, the use of GPT proves beneficial in enhancing the effectiveness of classroom learning and provides a solution to teachers' challenges in understanding students' psychological needs.
OPTIMALISASI PENJUALAN IKAN SALAI BERBASIS DIGITAL MARKETING PADA UMKM KELUARGA MAJU BERSAMA DI KABUPATEN LAHAT Fitriadi, Heri; Zikry, Arief; Sulkhan Nurfatih, Muhammad
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 8, No 2 (2025): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v8i2.888-895

Abstract

Pengabdian masyarakat yang dilakukan di UMKM Keluarga Maju Bersama, Kabupaten Lahat, bertujuan untuk meningkatkan kualitas dan daya saing produk ikan salai melalui penerapan inovasi teknologi dan penguatan manajemen usaha. Program ini juga menitikberatkan pada diferensiasi produk dan pembentukan identitas merek yang khas, sehingga produk ikan salai mampu menonjol di pasaran. Selain itu, proyek ini bertujuan untuk mendorong praktik bisnis berkelanjutan dengan memberikan edukasi kepada pemilik UMKM tentang teknik produksi yang efisien dan pengelolaan sumber daya. Permasalahan utama yang dihadapi meliputi rendahnya kualitas kemasan dan strategi pemasaran yang kurang efektif, sehingga produk sulit bersaing di pasar. Metode yang digunakan mencakup pendekatan kuantitatif dengan desain deskriptif, pengumpulan data melalui observasi, wawancara, dan kuesioner, serta analisis deskriptif dan inferensial secara statistik. Hasil penelitian menunjukkan bahwa penerapan rumah pengasapan dan vacuum sealer secara signifikan meningkatkan kualitas dan daya tarik produk, serta memperpanjang masa simpan ikan salai. Selain itu, pelatihan pemasaran digital meningkatkan pemahaman dan keterampilan mitra dalam mempromosikan produk mereka, sehingga terjadi peningkatan penjualan sebesar 50% dalam enam bulan. Dengan demikian, kegiatan pengabdian masyarakat ini berhasil menciptakan model pengembangan UMKM berbasis teknologi dan pemasaran digital.
OPTIMALISASI PRODUKSI KERUPUK RENGGINANG MELALUI PEMANFAATAN TEKNOLOGI OVEN OTOMATIS DAN DIGITAL MARKETING DI UMKM MAKJA KABUPATEN EMPAT LAWANG Rusilawati Kasisariah, Tri; Sulkhan Nurfatih, Muhammad; Kesuma, Darwin
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 8, No 10 (2025): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v8i10.%p

Abstract

Program pengabdian ini bertujuan untuk meningkatkan produktivitas dan daya saing UMKM MAKJA di Desa Mekarti Jaya, Kabupaten Empat Lawang, melalui pemanfaatan teknologi oven otomatis dan strategi digital marketing. Permasalahan utama yang dihadapi mitra adalah rendahnya efisiensi produksi akibat proses pengeringan manual yang memakan waktu lama serta terbatasnya akses pasar karena belum optimalnya penggunaan media sosial. Kegiatan ini dilaksanakan melalui pendekatan partisipatif kolaboratif yang melibatkan mitra secara aktif dalam setiap tahapan, mulai dari koordinasi, pelatihan, praktik langsung, hingga monitoring. Intervensi yang dilakukan mencakup pelatihan penggunaan oven otomatis dan strategi pemasaran digital berbasis pada media sosial seperti facebook dan instagram. Hasil kegiatan menunjukkan adanya peningkatan signifikan dalam kapasitas produksi (dari ±200 menjadi ±500 keping per hari), efisiensi waktu pengeringan (dari 1–2 hari menjadi 3–5 jam), serta meningkatnya keterampilan mitra dalam mempromosikan produk secara digital. Kegiatan ini memberikan dampak positif terhadap kemandirian usaha dan membuka peluang replikasi untuk UMKM sejenis di wilayah lainnya.
Co-Authors Agustian Prakarsyah Arief Zikry Darwin Kesuma, Darwin Deris Stiawan Eko Arip Winanto Firza Septian Heri Fitriadi Mohd Yazid Idris Rusilawati Kasisariah, Tri Yusi Nurmalasari