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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURIKOM (Jurnal Riset Komputer) J-Kesmas: Jurnal Kesehatan Masyarakat (Indonesian Journal of Public Health) Jurnal Kacapuri : Jurnal Keilmuan Teknik Sipil Jurnal Ilmu Pemerintahan, Administrasi Publik, dan Ilmu Komunikasi (JIPIKOM) Nabawi: Journal of Hadith Studies Formosa Journal of Applied Sciences (FJAS) Prosiding Seminar Nasional Teknik Sipil UMS Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi Media Journal of General Computer Science (MJGCS) Jurnal Pengabdian Masyarakat Inovasi Indonesia
Abdul Harris
Jurusan Peternakan, Fakultas Pertanian, Universitas Syiah Kuala
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Public Health Social Sciences

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The Isolation of Staphylococcus Epidermidis Bacteria in White Snapper Salted Fish (Lates Calcalifer) of Sibolga City, North Sumatera Province Lestari, Rafika; Admi, Masda; Rastina, Rastina; Dewi, Maryulia; Nurliana, Nurliana; Harris, Abdul; Riady, Ginta
J-Kesmas: Jurnal Fakultas Kesehatan Masyarakat (The Indonesian Journal of Public Health) Vol 7, No 1 (2020): April 2020
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/j-kesmas.v7i1.1918

Abstract

Salted fish is vulnerable to contamination by microbial. Staphylococcus epidermidis is one of the bacteria that can contaminate the salted fish. This research aims to isolate the Staphylococcus epidermidis bacteria contamination in salted white snapper fish sold in Sibolga City, North Sumatra Province. The sample used was white snapper salted fish, amounting to 10 samples from 10 traders. The isolation of Staphylococcus epidermidis was carried out using the Carter method. White snapper salted fish are mashed using a blender, then planted on Nutrient Broth (NB) as a bacterial growth media. Furthermore, identification of bacterial colonies grew using gram staining, Manitol Salt Agar (MSA) media, Blood Agar Plate (BAP) media, catalase test and confectionery media (Manitol and Glucose). The data obtained were analyzed descriptively. The results of this study suggest that Staphylococcus epidermidis contains bacterial contamination. Based on the data collected, it can be concluded that 7 out of 10 samples of white snapper salted fish sold in Sibolga City, North Sumatra Province, are contaminated with 70 percent Staphylococcus epidermidis bacteria.
Deteksi Serangan ICMP Flood pada Internet of Things dengan Feature Selection dan Machine Learning Harid, Harid; Kurniabudi, Kurniabudi; Harris, Abdul
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8554

Abstract

IoT devices have played an important role in driving DDoS attacks, and are a threat to IoT networks. One of them is the ICMP Flood attack. To overcome attacks on IoT, one of them uses an Intrusion Detection System (IDS). However, on the other hand, IDS has challenges in handling the complexity of high-dimensional data. One of the suggested solutions to overcome the problem of data dimensions is the use of feature selection techniques. The Forward Selection feature selection technique is used to eliminate irrelevant features. This study compares the performance of the Random Forest and SVM algorithms. For experimental purposes, this study used the CICIoT2023 dataset, which represents IoT traffic. The use of Forward Selection obtained 11 selected features that will be used in the machine learning process using the Random Forest and SVM methods. Feature selection affects the computation time or processing time, because the fewer features used, the more the system's workload in carrying out the classification process. The test results show that the use of feature selection improves the performance of random forest with an accuracy of 100%. Meanwhile, the SVM model gets better accuracy by using feature selection with the highest accuracy of 99.4508% in the supplied test set test.
The role of PT. Raharja Services in Road Traffic Accidents (Study of Constitutional Court Decision Number 88/PUU-XV/2017 Regarding Review of Law Number 34 of 1964 concerning Compulsory Road Traffic Accident Insurance Funds) Julianti, Firginia; Ginting, Budiman; Nasution, Faisal Akbar; Harris, Abdul
Formosa Journal of Applied Sciences Vol. 2 No. 11 (2023): November 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjas.v2i11.6833

Abstract

The approach used in this research is normative juridical. using secondary data consisting of primary, secondary and tertiary legal materials, which are then analyzed using analytical descriptive analysis. The results of this research, PT. Jasa Raharja has carried out its responsibilities in accordance with the regulations that regulate it, but based on the rejection of the application as a whole by the judge in the Constitutional Court Decision No. 88/PUU-XV/2017 concerning Review of Law Number 34 of 1964 concerning Compulsory Road Traffic Accident Insurance Funds, it still has not been implemented. there is a regulation in the form of a law (rechtvacuum) regarding compensation for victims who experience a single accident, payment of compensation for victims who experience a single accident is only through Ex-Gratia which is the limited authority of PT. Jasa Raharja so that the presence of the state in providing social protection for single accident victims is very necessary.
Deteksi Bahasa Isyarat Bisindo Menggunakan Metode Machine Learning Agus Nugroho; Setiawan, Roby; Harris, Abdul; Beny
Jurnal PROCESSOR Vol 18 No 2 (2023): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2023.18.2.1380

Abstract

This study aims to develop a machine learning-based application capable of detecting hand gestures and patterns in Indonesian Sign Language (BISINDO). Sign language plays a crucial role in non-verbal communication, particularly for individuals with speech impairments like the deaf. However, the challenge of comprehending sign language often inhibits interactions between the deaf and others. In an effort to address this barrier, the research leverages machine learning techniques with a focus on the Convolutional Neural Network (CNN) method, utilizing a dataset annotated with hand gesture landmarks. Landmark information providing detailed positions and shapes of key points on the hand, the CNN model can learn specific features essential for classification. The resulting application aims to bridge communication between the deaf and other individuals who may not understand sign language. By harnessing this technology, a significant improvement in the accuracy of hand gesture classification in sign language is anticipated, thereby strengthening the communication and interaction capabilities of the deaf within their environment.
Peran Mahasiswa dalam Pelaksanaan Pengerjaan Sloof dan Balok pada Proyek Gedung Puskesmas Harapan Baru Wahyuni, Eka; Pratiwi, Dheka Shara; Agustina, Fitriyati; Liana, Ulwiyah Wahdah Mufassirin; Yatnikasari, Santi; Siregar, Adde Currie; Harris, Abdul; Pane, Ivindra
Jurnal Pengabdian Masyarakat Inovasi Indonesia Vol 3 No 3 (2025): JPMII - Juni 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jpmii.792

Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan dalam bentuk pendampingan teknis pada proyek pembangunan Gedung Puskesmas Harapan Baru di Samarinda, Kalimantan Timur, dengan fokus pada pekerjaan struktur Sloof dan balok. Mahasiswa Program Studi Teknik Sipil terlibat secara aktif sebagai peserta pengabdian dengan peran utama sebagai pengawas lapangan sekaligus pembelajar. Melalui pendekatan observasi partisipatif, mahasiswa mendampingi proses konstruksi mulai dari persiapan, pembesian, pemasangan bekisting, hingga pengecoran Sloof dan balok. Selain mengamati dan mencatat prosedur teknis, mahasiswa juga memantau penerapan aspek Keselamatan dan Kesehatan Kerja (K3) serta mendokumentasikan kendala teknis di lapangan. Hasil dari kegiatan ini menunjukkan adanya peningkatan pemahaman mahasiswa terhadap praktik konstruksi nyata, terutama terkait metode pelaksanaan dan kontrol mutu pekerjaan struktur. Di sisi lain, keberadaan mahasiswa turut membantu meningkatkan kesadaran pekerja terhadap pentingnya penggunaan alat pelindung diri (APD) secara konsisten. Program ini memberikan kontribusi ganda, yakni penguatan kompetensi mahasiswa di bidang teknik sipil terapan dan dukungan terhadap kelancaran serta kualitas pembangunan fasilitas kesehatan masyarakat.
Co-Authors Adde Currie Siregar Afrio Arisman, Afrio agus Nugroho Ali Fahrudin, Ali Ameliah, Siska Amri, Naufal Nuzulul Azhar Azhar Beny BUDIMAN GINTING Eka Wahyuni ENDRI ENDRI Fachry Abda El Rahman Faisal Akbar Nasution Faishal Agil Al Munawar Fitriyati Agustina Gilang Ramadhan Ginta Riady Harid, Harid Ivindra Pane Julianti, Firginia Khairiyah, Revinda Dwi Artanti Khairul Umam Kurniabudi, Kurniabudi Lestari, Rafika Lola Yorita Astri, Lola Yorita M Hasan Maryulia Dewi Masda Admi N.A, Zuhrawati Nasrulloh Nasrulloh Natania, Salwa Novianto, Yudi NURLIANA NURLIANA Pratiwi, Dheka Shara Rastina, Rastina ROBY SETIAWAN Santi Yatnikasari Selphia , Megah siahaan, uliasi patricia Sugito Sugito Ulwiyah Wahdah Mufassirin Liana VERONICA VERONICA WILLY RIYADI