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All Journal Techno.Com: Jurnal Teknologi Informasi EDUMATIC: Jurnal Pendidikan Informatika Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika International Journal of Informatics and Computation Jurnal Informatika Ekonomi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Journal Automation Computer Information System (JACIS) Brilliance: Research of Artificial Intelligence Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Joong-Ki : Jurnal Pengabdian Masyarakat Jurnal Informasi Sains dan Teknologi (ISAINTEK) SMART Management Journal STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Indonesian Research Journal on Education Journal Of Informatics And Busisnes VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Komputer dan Teknologi (JUKOMTEK) SAINTEK Jurnal Media Akademik (JMA) Joong-Ki Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan SISFOTENIKA Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Expert Net: Exploration Journal of Technological Education Trends Joong-Ki Jurnal Rekayasa Teknologi Nusa Putra Jejak digital: Jurnal Ilmiah Multidisiplin Jurnal Cakrawala Akademika Jurnal Sistem Informasi dan Ilmu Komputer
Elkin Rilvani
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Pembelajaran Berbasis Aplikasi Di SMK Al Mujahidin Cikarang Rilvani, Elkin; Butsianto, Sufajar; Romli, Ikhsan
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 1 (2024): Juni 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i1.88

Abstract

Dalam era digital saat ini, integrasi teknologi dalam pendidikan menjadi sebuah keharusan untuk meningkatkan efektivitas proses pembelajaran. SMK Al Mujahidin Cikarang menyadari pentingnya penggunaan aplikasi dalam proses pembelajaran untuk mempersiapkan siswa menghadapi tantangan di dunia kerja yang semakin kompleks. Pelatihan ini bertujuan untuk memberikan pengetahuan dan keterampilan kepada para guru dalam menggunakan berbagai aplikasi pembelajaran yang relevan dengan kurikulum dan kebutuhan siswa. Metode pelatihan yang digunakan meliputi ceramah, demonstrasi, dan praktek langsung. Para peserta diperkenalkan pada aplikasi-aplikasi seperti Google Classroom, Kahoot, Quizizz, dan aplikasi produktivitas lainnya yang dapat menunjang proses pembelajaran. Selain itu, pelatihan ini juga mencakup strategi integrasi teknologi dalam perencanaan pembelajaran, pengelolaan kelas, dan evaluasi pembelajaran. Hasil dari pelatihan ini diharapkan mampu meningkatkan kompetensi guru dalam penggunaan teknologi, sehingga proses pembelajaran menjadi lebih interaktif, menarik, dan efektif. Dengan demikian, siswa dapat lebih termotivasi dan terlibat aktif dalam proses belajar mengajar. Pelatihan ini juga diharapkan dapat berkontribusi pada peningkatan kualitas pendidikan di SMK Al Mujahidin Cikarang secara keseluruhan.
Penerapan Metode Oversampling SMOTE Pada Algoritma Random Forest Untuk Prediksi Kebangkrutan Perusahaan Nugroho, Agung; Rilvani, Elkin
Techno.Com Vol. 22 No. 1 (2023): Februari 2023
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/tc.v22i1.7527

Abstract

Kemajuan teknologi informasi berkembang kearah finansial dalam melakukan prediski. Banyak model algoritma prediksi data keuangan telah dikembangkan. Prediksi kebangkrutan merupakan sesuatu yang sangat penting bagi organisasi atau perusahaan dalam mengambil keputusan yang diperlukan oleh pemodal dan investor. Prediksi kebangkrutan termasuk dalam permasalahan ketidakseimbangan kelas dalam model kalsifikasi karena jumlah data yang termasuk dalam kelas bangkrut jauh lebih sedikit dibandingkan dengan data yang termasuk dalam kelas tidak bangkrut. Tujuan dari penelitian ini adalah untuk menghasilkan model klasifikasi yang baik untuk prediksi risiko kebangkrutan pada perusahaan. preprocessing data dilakukan untuk melakukan optimasi algoritma klasifikasi dengan metode oversampling SMOTE agar menghasilkan model kalsifikasi yang optimal. Algoritma klasifikasi yang digunakan adalah Random Forest Classification untuk mendapatkan hasil prediksi kebangkrutan yang optimal. Berdasarkan hasil pengujian yang telah dilakukan didapatkan bahwa performa klasifikasi meningkat sebesar 7,40% setelah dilakukan preprocessing data dengan menggunakan teknik oversampling SMOTE pada algoritma Random Forest Classifier.
Perbandingan Teknik pada Struktur Sistem File Windows & Linux Zacky Rafian Fawwauzy; Taufik Eka Albani; Elkin Rilvani
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 1 (2025): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i1.343

Abstract

This research compares the techniques used in the file system structures of Windows and Linux. Each operating system employs distinct approaches to data organization, access, and management, as reflected in their respective file systems: NTFS for Windows and ext4 for Linux. The study explores the strengths, weaknesses, and applications of these systems under various conditions. By analyzing both theoretical documentation and empirical experiments, this research highlights the technical and philosophical aspects influencing the design and performance of file systems in Windows and Linux. The findings provide insights for selecting an appropriate file system based on specific requirements, emphasizing performance, reliability, and usability.
Struktur Sistem Operasi Windows dalam Mendukung Kinerja Operasional Ramadhan Ardi Iman Prakoso; Anindha Latiefa Zahra; Elkin Rilvani
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 1 (2025): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i1.346

Abstract

The structure of the Windows operating system plays an important role in supporting the operational performance of computers, especially in business environments and professional users. This system is designed with a modular and layered architecture, which includes various components such as Hardware Abstraction Layer (HAL), I/O device manager, virtual memory management, and an integrated security system. Windows also supports energy management and plug-and-play mechanisms, which improve power efficiency and hardware compatibility. This architectural approach allows Windows to optimize interactions between hardware and applications, supports multitasking, and provides an efficient user interface. Thus, the structure of the Windows operating system is able to significantly improve device performance, which leads to optimization of operational performance.
sistem operasi mobile Komparasi Struktur Sistem Operasi Mobile Dampak Pengelolaan Memori dan Performa Aplikasi Sukmana Wibowo, Mohamad Hegar; Al Ayubi, Muhammad Din; Rilvani, Elkin
Jurnal Informasi, Sains dan Teknologi Vol. 7 No. 2 (2024): Desember: Jurnal Informasi Sains dan Teknologi
Publisher : Politeknik Negeri FakFak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/isaintek.v7i2.265

Abstract

Mobile operating systems are software designed to manage the fundamental functions of devices. The most dominant mobile operating systems in today's market are Android and iOS, each capturing their respective user segments with distinct approaches. iOS is a mobile operating system developed by Apple, tailored for its smartphones, while Android is designed by the Open Handset Alliance (led primarily by Google) and developed for Android smartphones and tablets. This study employs a comparative method to analyze the performance and memory management of Android 11 and iOS 14. The findings reveal that iOS 14 is more efficient, with an average memory allocation time of 90 ms, compared to Android 11’s 120 ms. Android 11 offers greater flexibility in handling heavy applications but at the cost of higher memory consumption. Conversely, iOS 14 demonstrates superior efficiency and stability in memory usage, particularly for lightweight and medium applications.
Linear Regression Algorithm Analysis for Predicting Electrical Panel Painting Quality Susilo, Arif; Widodo , Edy; Rilvani, Elkin; Suryana, Syahro
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4096

Abstract

Industry is increasingly developing rapidly and has an impact on the emergence of competition between companies, both private and state, both companies engaged in manufacturing and service companies. Linear Regression is used to find out how the dependent/criterion variable can be predicted through independent variables or predictor variables, individually. Based on the results of the tests that have been carried out, the variables or attributes used in this research (minute and thinkness results) have a significant effect on this research. It is proven that using the linear regression algorithm is able to provide good results with a Root Mean Squared Error value of 0.273 +/- 0.000. This is because there is a correlation or functional relationship (cause - effect) between one variable (dependent or criterion) and another variable (independent or predictor). This testing process is carried out to identify stock needs using a linear regression algorithm
Recruitment Classification of Security Unit PT. Satria Kencana Abadi Using Naïve Bayes Method Rilvani, Elkin; Surojudin, Nurhadi; Danny, Muhtajuddin; Yoga Pratama, Evan
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4138

Abstract

To get human resources according to company standards, the problem faced in the company is the difficulty of the selection process with a short time and the complexity of the decision making process resulting in subjective decision making. The purpose of this research is to assist the assessment process in making decisions for determining the selection of security units (SATPAM) to be more targeted so that it can help the company. In this study the data used were 697 data with 558 training data and 139 testing data. This test data was carried out using the Naïve Bayes algorithm method to classify so that it can determine accurate and efficient decision making, using Rapidminer tools which have 82 accuracy, 01%, 81.61% Precision, and 88.75% recall. This shows that the Naïve Bayes algorithm method has a good performance in determining decision making during the selection of security forces (SATPAM) at PT. Satria Kencana Abadi.
Analisis Manajemen Proses pada Sistem Operasi Linux : Permasalahan dan Solusi Muhammad Albedri; Yudha Purnama Putra; Elkin Rilvani
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 1 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i1.615

Abstract

This study aims to analyze process management in the Linux operating system, focusing on how processes are managed from creation, scheduling, to termination. Linux utilizes various scheduling and memory management mechanisms to ensure system efficiency and stability. One of the schedulers used is the Completely Fair Scheduler (CFS), which provides a fair distribution of CPU time based on the priority and needs of the processes. This research also discusses the use of techniques such as paging for memory management and how Linux handles inter-process communication through pipes and shared memory. Experiments were conducted to measure CPU usage, memory consumption, and execution time by various processes with different priorities. The results show that Linux effectively manages resources, provides fair time-sharing, and maintains security by isolating the address space between the kernel and user-space. This study is expected to contribute to the further development of process management in Linux and provide insights for developers and system administrators to optimize operating system performance.
Keamanan Kernel Linux : Pendekatan Hardening dan Perlindungan terhadap Serangan Eksploitasi Zalfa Dewi Zahrani; Novianto Andi Hardiansyah; Elkin Rilvani
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 1 (2025): Januari: Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i1.620

Abstract

Linux kernel security is a critical aspect of ensuring the integrity and stability of operating systems. Vulnerabilities like Dirty COW (CVE-2016-5195) illustrate how exploitative threats can severely impact systems, particularly those that are not regularly updated. This study analyzes the working mechanism of Dirty COW, its impact, and mitigation strategies based on Linux kernel hardening techniques, including the use of security modules like SELinux and AppArmor, as well as the Address Space Layout Randomization (ASLR) technique. Through attack simulations and mitigation evaluations, the findings emphasize the importance of regularly applying kernel patches to maintain system security. This study aims to provide practical guidance for enhancing Linux kernel resilience against exploitation attacks.
Optimizing Distributed Management in Cloud Computing Operating Systems Silvi Fara Dita; Tatia Deswita Anggraeni; Elkin Rilvani
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 1 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i1.634

Abstract

Pengembangan sistem operasi pada platform terdistribusi, terutama dalam konteks Cloud Computing, memainkan peran penting dalam mengelola sumber daya komputasi secara efisien. Manajemen terdistribusi mengacu pada penggunaan terintegrasi dari berbagai komponen di berbagai lokasi, menghadirkan tantangan yang signifikan dalam mengelola dan memantau sumber daya yang tersebar. Komputasi awan menawarkan solusi infrastruktur fleksibel yang memungkinkan pengguna mengakses sumber daya komputasi tanpa memerlukan manajemen infrastruktur fisik. Penelitian ini bertujuan untuk mengoptimalkan manajemen terdistribusi dalam sistem operasi komputasi awan dengan memanfaatkan algoritma pembelajaran mesin untuk meningkatkan efisiensi alokasi sumber daya dan meningkatkan keamanan data. Pengumpulan data dilakukan melalui metode observasi sistematis dan tinjauan pustaka. Temuan menunjukkan bahwa penerapan algoritme prediktif di lingkungan cloud secara signifikan mengurangi waktu respons dibandingkan dengan metode manual dan memperkuat perlindungan data melalui deteksi intrusi yang ditingkatkan. Selain itu, sistem berbasis pembelajaran mesin memungkinkan skalabilitas yang lebih baik dan adaptasi yang lebih cepat terhadap permintaan sumber daya dinamis tanpa waktu henti sistem. Makalah ini menyumbangkan wawasan berharga dalam mengoptimalkan kinerja komputasi awan melalui manajemen sumber daya terdistribusi yang ditingkatkan.
Co-Authors Abdul Rokim Abid Lu’ay Raihan Taufik Agung Nugroho Ahmad Budi Trisnawan Ahmad Turmudi Zy Al Ayubi, Muhammad Din Aldi Patria Nugraha Alfian Saputra, Ricky Alfiana Erlangga, Dafa Alif Nur Fathlii Amarta Amar Agung Subekti An-nisa Fitriani Andhika Aziz Bachtiar Andi Setyawan Anindha Latiefa Zahra Apik Aminah Aries Widyantoro Arif Susilo ARIF SUSILO Ariza, Rini Arya Saepul Hakim Asep Muhidin Asep Saepuloh Baehaqi Bagoes Ramadhan Baihaqi Asa’ari Lubis Bayu Nugroho Butsianto, Sufajar Candra Naya Catur Pranomo Dimas Adi Nugraha Dina Amalia Putri Diska Kurnia Azzahra Putra Dito Ridwansyah, Rizjky Dzaky Alaudin Malik Edi Tri Wibowo Edora Erikasari, Vivie Zuliani Ermanto Ermanto Ermanto Fachrial Banyu Asmoro Fadhlurohman Fatikh Navintino Faisal Arya Yudanto Faiza Muhammad Julianto Faqih Irianto Fazri Albadawi Fikr, Muhammad Fiqhy Faradisa Al Bina Fitakwim Fitakwim Galih Pangestu Gilar Sumilar Hadi Putra Hardiansyah, Andi Hendra Parsaulian Henri Caesar Bimantara Herlan Wibowo Hidayat, Chaerul Hilman Ihza Amrullah Hizkia Vincent Hrenysa Ikhsan Romli Indry Widiyani Khaerunnisa Isnaeni Lestari Khairunnisa Nasution Lili Fadli Muhamad Ma'ruf Setiadi2 Maharani , Tyanshi Firli Mikael Rivaldo Mochammad Rahmat Faisal Monika Pakpahan Muhamad Daffa Maulana Arrasyid Muhamad Faisal Ilham Muhamad Fatchan Muhammad Akmal Ar Rasid Muhammad Albedri MUHAMMAD ARIFIN Muhammad Farhan Fahreza Muhammad Nur Falah Muhammad Rifki Febrianto Muhammad Rizal Mantofani Muhammad Rizky Raka muhidin, asep Muhtajuddin Danny Nabilla Kusuma Wijaya Nadia tul umah Naya, Candra Naza Sefti Prianita Novant Nanda Pradana Novianto Andi Hardiansyah Nugroho, Agung Nur Hasim Nur Hidayati Nurkholik Safrudin Ovi Marzuki Panji Anwar Sanusi Pardede, Debora Hizkhia Prakoso, Indra Prasetyo, Fabian Eka Priasnyomo Prima Santoso Putra, Aan Fadillah Rafi Maulana Firdaus Ramadhan Ardi Iman Prakoso Reza Maulana, Muhammad Rio Rinto Saki Rizki Fahrizal Rizky Juniarko Taruna Putra Roana, Roana Saiful Muktiali Sela, Mosses Ara’al De Setyawan, Wisnu Shanti Cahyaningtyas Sifa Setiyani Silvi Fara Dita Siswandi, Arif Siti Yasmin Nurcholifah Soejarminto, Yos Sukmana Wibowo, Mohamad Hegar Surojudin, Nurhadi Suryadi Putra Suryadi, Dikky Suryana, Syahro Tatia Deswita Anggraeni Taufik Eka Albani Tia Mulyani Tri Ngudi Wiyatno Weni Purnomo1 Widodo , Edy Wisnu Ikhwansyah Saputra Wisnu Setyawan Yoga Pratama, Evan Yudha Purnama Putra Yudi Fermana Zacky Rafian Fawwauzy Zalfa Dewi Zahrani