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All Journal ELINVO (Electronics, Informatics, and Vocational Education) Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Faktor Exacta INOVTEK Polbeng - Seri Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) KOMPUTIKA - Jurnal Sistem Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Onoma: Pendidikan, Bahasa, dan Sastra Klasikal: Journal of Education, Language Teaching and Science Jurnal Teknik Informatika (JUTIF) Panrannuangku Jurnal Pengabdian Masyarakat Chemistry Education Review Online Learning in Educational Research Seminar Nasional Pengabdian Kepada Masyarakat Teknovokasi : Jurnal Pengabdian Masyarakat Jurnal Pendidikan Terapan Vokatek : Jurnal Pengabdian Masyarakat Journal of Embedded Systems, Security and Intelligent Systems Ininnawa: Jurnal Pengabdian Masyarakat Journal of Security, Computer, Information, Embedded, Network and Intelligence System Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Journal of Deep Learning, Computer Vision and Digital Image Processing Jurnal Sipakatau Journal of Progressive Information, Security, Computer and Embedded System Jurnal MediaTIK Journal of Computers, Informatics, and Vocational Education Media Elektrik
Muhammad Fajar B
Universitas Negeri Makassar
Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : Journal of Embedded Systems, Security and Intelligent Systems

 1 
FEATURES SIMPLIFICATION USING CUBIC BEZIER PROPERTIES FOR GAIT RECOGNITION ON SMARTPHONE Kurnia Prima Putra; Marwan Ramdhany Edy; M. Syahid Nur Wahid; Muhammad Fajar B; Fadhlirrahman Baso
Journal of Embedded Systems, Security and Intelligent Systems Vol. 3 No. 1 (2022): Vol 3, No 1 (2022): May 2022
Publisher : Program Studi Teknik Komputer

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Abstract

Smartphone is widely used around the world. It’s user authentication usually used pin code, pattern code, fingerprint and conventional login authentication. This kinds of authentication mechanism is intrusive because those mechanisms requires users to give exclusive interaction for user authentication during the process. One of authentication method which is non-intrusive during data collection is authentication by using gait. This mechanism classified as non-intrusive because this mechanism could gather biometric data without being noticed by the authentication subjects. Since it is non-intrusive, this mechanism allows re-authentications without bothering the authentication subjects. One of the recent gait recognition is using accelerometer on smartphone to measure and capture acceleration data on gait. This method extract step cycles in various length, map and interpolate the data into higher sample count, and then use each of mapped and interpolated data as feature using recognition. Regardless the classification or recognition method, using each mapped and interpolated data as features would result in high processing time during classification or recognition due to high feature count. In this research, we try to simplify the features of gait data with minimum data loss so it might give robust result with less latency by aligning cubic Bezier curve to step cycle data and extracting the Bezier properties.
Analisis Prediksi Tingkat Penyebaran COVID-19 di Sulawesi Selatan Menggunakan Teknik Data Mining Naive Bayes Muhammad Nur Yusri; Andi Akram Nur Risal; Muhammad Fajar B; Dewi Fatmarani Surianto; Fhatiah Adiba
Journal of Embedded Systems, Security and Intelligent Systems Vol. 3 No. 2 (2022): Vol 3, No 2 (2022): November 2022
Publisher : Program Studi Teknik Komputer

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Abstract

Pandemi atau wabah virus corona atau biasa disebut juga dengan COVID-19 yang bermula dari Wuhan, Provinsi Hubei, China, terus menyebar ke berbagai negara, termasuk Indonesia. Jumlah kasus positif COVID-19 terus meningkat tiap harinya secara signifikan dan menyebar secara cepat ke berbagai provinsi di Indonesia, termasuk di provinsi Sulawesi Selatan. Hingga saat ini, telah tercatat kasus positif corona di Sulawesi Selatan sebanyak 18.683 dan 470 orang meninggal dunia. Peningkatan kasus yang signifikan ini, mengakibatkan pembacaan data terkait kasus positif COVID-19 di Sulawesi Selatan dinilai kurang akurat. Oleh karena itu, penelitian ini dilakukan sebagai langkah antisipasi terhadap pandemi COVID-19 dengan memprediksi tingkat penyebaran COVID-19 terutama di Sulawesi Selatan agar mendapatkan keakurasian data yang lebih baik. Metode penelitian yang di terapkan pada penelitian ini ialah analisis masalah dan studi literatur, mengumpulkan data dan implementasi.
Comparative Analysis of the Performance of Hadith Text Classification Methods: A Case Study with ANN and SVM Surianto, Dewi Fatmarani; Fajar B, Muhammad; Mulia, Musda Rida; Indanasufya, Indanasufya
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 1 (2024): March 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i1.2942

Abstract

Hadith is the second holy book for Muslims after the Quran, containing instructions from the Prophet Muhammad SAW, and narrated by Ulama / Mufti. As one of the main sources of Islamic teachings, hadith is used to explain and illustrate the teachings of the Quran. This study aims to compare the performance of hadith text classification using Artificial Neural Network (ANN) and Support Vector Machine (SVM) with Hadith Bukhari dataset. The stages include preprocessing, feature extraction with TF-IDF, classification, and evaluation. The evaluation results show different performance between ANN and SVM in two scenarios: with and without stemming. The use of stemming has a significant impact on model performance, reducing word variation and can result in a decrease in accuracy. The SVM model consistently showed higher accuracy than ANN in both scenarios, with the highest accuracy reaching 85% for classification without stemming. This study provides insight into the application of ANN and SVM in hadith text classification, emphasizing the importance of selecting a method that suits the characteristics of the data.
A Hybrid Framework for Plagiarism Detection: Integrating Token-Based Similarity with Density-Based Clustering Fajar B, Muhammad; Lestary, Fitriyanty Dwi; Surianto, Dewi Fatmarani
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 1 (2025): March 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i1.7664

Abstract

Plagiarism detection in academic assignments remains a critical challenge in maintaining academic integrity in higher education. This study proposes an automated method to detect content similarity between student assignment documents by combining Jaccard Similarity and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithms. The process begins with the collection of student assignment files in digital format, followed by text extraction to form a set-based representation of each document. Jaccard Similarity is then used to compute the degree of similarity between every document pair, and the resulting similarity matrix is transformed into a distance matrix as input for DBSCAN. Experiments conducted on 23 documents yielded 253 unique document pairs. The results demonstrate that the method successfully identified pairs with high similarity scores—such as 0.9114 and 0.7226—which were visually confirmed through a heatmap and effectively grouped into clusters by DBSCAN. Parameter settings of eps = 0.3 and min_samples = 1 proved optimal for distinguishing original documents from those exhibiting substantial content overlap. This approach is not only accurate and efficient, but also eliminates the need for predefined cluster numbers, making it suitable for deployment in automated plagiarism detection systems for academic texts.
Co-Authors AA Sudharmawan, AA Abdul Muis Mappalotteng Abdul Wahid Abdul Wahid Abidin, Muh. Rais Adiba, Fhatiah Afdhaliyah, Mukhlishah Aglaia, Alifya Nuraisyar Akmal Hidayat Akmal Hidayat Al Imran Alfiani Alfiani Alfiani Ananda, Sukma Riski Ananta Dwi Prayoga Alwy Andi Ahmad Taufiq Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Andi Nurul Izzah Andi Tenriola Andika Isma Anwar Wahid Arifiyanti, Fitria Asis Nojeng Asri Ismail Ayu Hasnining Azis Azis Azzahra Eka Bahar, Muhammad Mahdinul Bakri, Muh. Fajrin Bakri Baso Riadi Husda Baso, Fadhlirrahman Bukhari Naufal Nur Ag Dary Mochamad Rifqie Della Fadhilatunisa Dewi Fatmarani Surianto Dewi, Shabrina Syntha Dirawan, Gufran Darma Edy Sabara Edy, Marwan Ramdhani Fadhlirrahman Baso Fajrin, Farid Fathahillah Fathahillah Fhatiah Adiba Fhatiah Adiba Fitriyanty Dwi Lestary Hamda, Hamda Hanum Zalsabilah Idham Hardy M, Galang Harisma Dita Ansyar Harisma Dita Ansyar Dita Ansyar Hastuti Hidayat, Almisri I Nyoman Prayana Trisna Indanasufya, Indanasufya Indriani, Gebby Irwansyah Suwahyu Israwati Hamsar Iwan Suhardi Jamaluddin Jamaluddin Jamaluddin Jariah S.Intam, Rezki Nurul Jumadi Mabe Parenreng Jumadin Khaeruddin, Faizah Kurnia Prima Putra Lavicza, Zsolt Lestari, Nunik M. Miftach Fakhri M. Syahid Nur Wahid Makmur, Haerunnisya Mangesa, Riana T Mappangara, Surianto Mapparenta, Muwaffiq Nurimansyah Marwan Ramdhany Edy Muh Fuad Zahran Firman Muh. Bhilal Halim Muh. Irfan Nur Muhammad agung Muhammad Agung Muhammad Agung Muhammad Agung Muhammad Akbar Amir Muhammad Akil Muhammad Ansarullah S. Tabbu Muhammad Asriadi Muhammad Fardhan Muhammad Farham Saputra Muhammad hasim Muhammad Nur Yusri Muhammad Yahya Mulia, Musda Rida Nasrullah, Asmaul Husnah NFH, Alifya NIRMALA, PUTRI Novitasari, Ervi Nur Azizah Ayu Safanah Nur, Muh Irfan Nurjannah, Elma Nurul Amanda Pratiwi Hasbullah Nurul Fadhilah Nurul Mukhlisah Abdal Paisal, Destyfaini Perdana, Am Akbar Mabrur Prima Putra, Kurnia Putri Nanda Sari Rahman, Ahmad Fadhli Rahman, Khaidir Ramadhan, Haekal Febriansyah Ramly Ramly Ridwan Daud Mahande Rosidah Rosidah Rosidah Sanatang Sarah Lintang Sariwening Sasmita Sasmita Satnur, Muh. Alham Setialaksana, Wirawan - Soeharto Soeharto Suci Rahmania Sudarmanto Jayanegara Surianto, Dewi Fatmawati Syahrul Syahrul Syahrul Syam, Abd. Azis Trisakti Akbar Udin Sidik Sidin Wahid, M Syahid Nur Wahid, M. Syahid Nur Wahyono Wahyono Wahyu Hidayat M WAHYUDI Wahyudi Wahyudi Wahyudi Wahyudi Wahyuni, Maya Sari Wardani, Ayu Tri Wijayanto, Danur Wilda Inaya Syafdwi Wulandari Wulandari Yususf, Andi Zulfikar