Article Per Year (5 Year)
p-Index From 2021 - 2026
9.094
P-Index
This Author published in this journals
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

Published : 82 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 82 Documents
Search

 5   6   7   8   9 
KLASIFIKASI KEMISKINAN DI INDONESIA DENGAN DECISION TREE MENGGUNAKAN RAPIDMINER Andi Setyawan; An-nisa Fitriani; Elkin Rilvani
Jurnal Media Akademik (JMA) Vol. 3 No. 7 (2025): JURNAL MEDIA AKADEMIK Edisi Juli
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/v3i7.2646

Abstract

Kemiskinan merupakan salah satu permasalahan utama yang masih dihadapi dalam proses pembangunan, khususnya di negara-negara berkembang seperti Indonesia. Ketimpangan sosial dan ekonomi yang masih tinggi menuntut adanya kebijakan yang tepat sasaran dan berbasis pada data yang akurat. Oleh karena itu, dibutuhkan metode klasifikasi yang mampu memetakan status kemiskinan masyarakat secara efektif. Penelitian ini bertujuan untuk menganalisis klasifikasi status kemiskinan menggunakan metode Decision Tree yang diimplementasikan melalui aplikasi RapidMiner. Data yang digunakan merupakan data sintetis sebanyak 150 entri yang menggambarkan kondisi sosial ekonomi penduduk Indonesia. Variabel-variabel yang digunakan dalam analisis meliputi umur, tingkat pendidikan, status pekerjaan, pendapatan bulanan, jumlah anggota keluarga, serta tipe lokasi tempat tinggal (perkotaan atau pedesaan). Proses klasifikasi dilakukan menggunakan pendekatan pembelajaran terawasi (supervised learning), yang menghasilkan model pohon keputusan yang mudah dipahami dan diinterpretasikan. Hasil penelitian menunjukkan bahwa metode Decision Tree mampu mengklasifikasikan status kemiskinan dengan tingkat akurasi mencapai 93%. Dari hasil analisis, diketahui bahwa pendapatan bulanan dan status pekerjaan merupakan variabel yang paling berpengaruh dalam menentukan status kemiskinan. Temuan ini diharapkan dapat menjadi landasan dalam perumusan kebijakan intervensi sosial yang lebih tepat sasaran dan efektif.
PREDIKSI JUMLAH UMKM BERDASARKAN KATEGORI USAHA DAN LOKASI KABUPATEN/KOTA DI PROVINSI JAWA BARAT MENGGUNAKAN DECISION TREE Rizki Fahrizal; Muhammad Nur Falah; Elkin Rilvani
Jurnal Media Akademik (JMA) Vol. 3 No. 7 (2025): JURNAL MEDIA AKADEMIK Edisi Juli
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/v3i7.2658

Abstract

Provinsi Jawa Barat merupakan salah satu wilayah dengan jumlah Usaha Mikro, Kecil, dan Menengah (UMKM) terbanyak di Indonesia. UMKM memegang peranan penting dalam mendorong pertumbuhan ekonomi daerah, menciptakan lapangan kerja, serta meningkatkan kesejahteraan masyarakat. Penelitian ini bertujuan untuk memprediksi jumlah UMKM berdasarkan kategori usaha dan wilayah administratif kabupaten atau kota di Jawa Barat. Data yang digunakan dalam penelitian ini merupakan data proyeksi jumlah UMKM dari tahun 2017 hingga 2024 yang telah dikelompokkan berdasarkan jenis usaha seperti kuliner, perdagangan, konveksi, jasa, dan lainnya. Metode yang digunakan adalah algoritma Decision Tree karena memiliki kemampuan untuk menghasilkan model prediksi yang mudah dipahami dan mampu mengidentifikasi atribut paling berpengaruh terhadap fluktuasi jumlah UMKM. Proses analisis dilakukan dengan menggunakan perangkat lunak RapidMiner untuk membangun dan mengevaluasi model prediksi. Hasil penelitian menunjukkan adanya variasi pertumbuhan UMKM di setiap kabupaten atau kota dan dalam masing-masing kategori usaha. Temuan ini diharapkan menjadi acuan bagi pemerintah daerah dalam menyusun strategi pengembangan UMKM yang lebih tepat sasaran dan berbasis potensi lokal.
Prediksi Penjualan Brand di HGVR Store Menggunakan Algoritma C4.5 dan Naïve Bayes Naya, Candra; Rilvani, Elkin
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1242

Abstract

HGVR Brand is a creative industry engaged in the production and distribution of ready-to-wear clothing established in 2015, which has a reseller network in several major cities in Java. This study aims to analyze the prediction of HGVR Store product sales levels using data mining methods, specifically the C4.5 and Naïve Bayes algorithms, so that it can assist the company in determining marketing strategies and inventory management. The data used in this study consists of 500 sales data collected in June 2019 through observation, interviews, and internal company documentation. The input variables used include the number of orders (PO), quantity, price, and sales status, while the target variable is the classification of sales into "high" and "low" categories. The analysis process is carried out through the stages of data cleaning, transformation, and validation using the split validation technique (70% training data and 30% testing data). The C4.5 algorithm is used to build a decision tree model, while the Naïve Bayes algorithm is used to calculate the classification probability. The test results show that the C4.5 algorithm has a 100% accuracy rate with an excellent classification category based on the ROC curve (AUC = 1.00). Meanwhile, the Naïve Bayes algorithm also produced good classification results, although its accuracy was lower than that of C4.5. The conclusion of this study is that the C4.5 algorithm is more optimal than Naïve Bayes in predicting sales levels at the HGVR Store. These findings are expected to inform decision-making for the HGVR Brand in formulating business strategies.
Evaluasi Segmentasi VLAN dalam Optimalisasi Kinerja dan Keamanan pada Jaringan LAN di Universitas Pelita Bangsa Nadia tul umah; Faisal Arya Yudanto; Elkin Rilvani
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 8, No 1 (2025): Januari
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v8i1.313

Abstract

Abstrak: Perkembangan teknologi jaringan komputer, khususnya dalam pengelolaan Local Area Network (LAN), telah mendorong pengembangan teknologi Virtual Local Area Network (VLAN) sebagai solusi untuk meningkatkan efisiensi dan fleksibilitas jaringan. Penelitian ini bertujuan untuk menganalisis pengaruh segmentasi VLAN terhadap kinerja dan keamanan jaringan LAN. Metode yang digunakan dalam penelitian ini mencakup observasi, wawancara, serta analisis data menggunakan alat bantu seperti Cisco Packet Tracer, Wireshark, dan Iperf. Hasil penelitian menunjukkan bahwa penerapan VLAN dapat meningkatkan kinerja jaringan LAN secara signifikan, dengan peningkatan throughput sebesar 60%, penurunan delay sebesar 33%, pengurangan packet loss hingga 80%, dan penurunan jitter sebesar 57%. Selain itu, VLAN juga berperan dalam meningkatkan keamanan jaringan dengan memisahkan trafik berdasarkan segmen-segmen tertentu, sehingga mengurangi potensi ancaman dan meningkatkan kontrol terhadap aliran data. Penelitian ini memberikan rekomendasi bagi administrator jaringan untuk mengimplementasikan VLAN dalam pengelolaan jaringan LAN guna memperoleh kinerja yang lebih baik serta meningkatkan aspek keamanan jaringan. Kata kunci: VLAN, LAN, segmentasi jaringan dan keamanan jaringanAbstract: The development of computer network technology, particularly in the management of Local Area Networks (LAN), has driven the advancement of Virtual Local Area Network (VLAN) technology as a solution to enhance network efficiency and flexibility. This research aims to analyze the impact of VLAN segmentation on the performance and security of LAN networks. The methods used in this study include observation, interviews, and data analysis using tools such as Cisco Packet Tracer, Wireshark, and Iperf. The research findings indicate that the implementation of VLAN can significantly improve LAN network performance, with a 60% increase in throughput, a 33% reduction in delay, an 80% decrease in packet loss, and a 57% reduction in jitter. Additionally, VLAN plays a role in improving network security by separating traffic into specific segments, thus reducing potential threats and enhancing control over data flow. This study provides recommendations for network administrators to implement VLAN in managing LAN networks to achieve better performance and enhance network securityKeywords: VLAN, LAN, network segmentation, and network security.
Analisis Pengelompokan Data Nilai Siswa Untuk Menentukan Siswa Berprestasi Menggunakan Metode Clustering K-Means Elkin Rilvani; Monika Pakpahan
Prosiding Sains dan Teknologi Vol. 4 No. 1 (2025): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 4 - Februari 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Today’s education sector is required to remain competitive by maximizing all available resources. High student success rates and low failure rates reflect the quality of education. However, determining student achievement levels—categorized as low, sufficient, or high—often becomes a challenge. To address this issue, data mining can be applied as a method for analyzing data and identifying patterns within large datasets. One important technique in data mining is clustering, which groups data into clusters based on similarity. Data within the same cluster have high similarity, while data between clusters have low similarity. A commonly used clustering method is the K-Means algorithm. K-Means is a non-hierarchical clustering technique that partitions data into one or more clusters based on shared characteristics, grouping similar objects together and separating those with different characteristics. In analyzing student achievement, the attributes used include student names and subject grades. The grouping process applies Euclidean Distance to measure similarity between data points. By implementing clustering with the K-Means algorithm, student achievement levels can be classified into low, sufficient, and high categories, thereby supporting more effective and targeted teaching and learning processes.
Pendampingan Pembuatan Sistem Keamanan Jaringan Menggunakan Firewall Open Source Di SMK Garuda Nusantara Siswandi, Arif; Soejarminto, Yos; Rilvani, Elkin; Muktiali, Saiful
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 3 No. 2 (2025): Desember 2025
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v3i2.166

Abstract

The rapid development of information and network technology requires vocational schools to implement reliable network security systems to protect digital infrastructure and data. SMK Garuda Nusantara has adequate network facilities; however, network security implementation has not been optimally configured. This community service program aims to provide assistance in developing and implementing an open-source firewall-based network security system. The implementation method includes preparation, socialization, theoretical training, firewall configuration practice, mentoring, and evaluation. Open-source firewall solutions are utilized as cost-effective and educational tools for network security learning. The results indicate improved participants’ understanding and skills in network security concepts, traffic management, and access control using firewalls. This program supports project-based learning, enhances cybersecurity awareness, and strengthens collaboration between higher education institutions and vocational schools. Keywords: Network Security, Open Source Firewall, Community Service, Vocational Education
Implementasi Algoritma K-Means Clustering Meggunakan Rapid Miner Untuk Mengelompokan Penjualan Produk Pada Toko Sanjaya Sport Rilvani, Elkin; Fikr, Muhammad
Jurnal Pelita Teknologi Vol 19 No 2 (2024): September 2024
Publisher : Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/pelitatekno.v19i2.7300

Abstract

This study examines the implementation of the K-means clustering algorithm using RapidMiner to classify sports product sales data at Toko Sanjaya Sport. The research addresses the lack of a sales analysis system capable of grouping products based on sales performance, which has hindered effective stock and promotional decision-making. The dataset includes 150 sales records from January to December 2024, with attributes such as product name, category, and price. The research follows the Knowledge Discovery in Database (KDD) stages: data selection, preprocessing, transformation, clustering using K-means, and evaluation with the Davies-Bouldin Index (DBI). The results generated three clusters: highly demanded products (15 items), moderately demanded products (41 items), and less demanded products (69 items). The DBI score of 0.667 indicates good clustering quality. Overall, the findings provide valuable insights to support better inventory management and sales strategy planning at Toko Sanjaya Sport.
Perbandingan Manajemen Memori pada Sistem Operasi Windows dan Linux Ariza, Rini; Reza Maulana, Muhammad; Rilvani, Elkin
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4471

Abstract

This research compares memory management between Windows 10 and Linux Ubuntu operating systems, focusing on the issues of memory fragmentation and memory leaks. Windows 10 applies paging and segmentation methods, which provide a high degree of flexibility, but on the other hand carry considerable system overhead. On the other hand, Linux Ubuntu uses the Buddies system which is more efficient in dealing with fragmentation issues. In handling memory leaks, Windows 10 relies on Garbage Collection, while Linux Ubuntu utilizes the Permchecker tool. This research provides knowledge related to the differences between Windows 10 and Linux Ubuntu operating systems in the context of handling memory management problems, especially on memory fragmentation and memory leak problems.
Perbandingan Kinerja iOS dan HarmonyOS dalam Performances Hidayat, Chaerul; Prasetyo, Fabian Eka; Rilvani, Elkin
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4497

Abstract

This study compares the performance of two leading mobile operating systems, iOS and HarmonyOS, focusing on technical aspects such as power efficiency, application response speed, background application management, and graphics rendering performance. Using a literature review method, data was collected from scientific sources, comparative reports, and official documents. The analysis results show that iOS excels in hardware-software integration, providing high energy efficiency and stable performance, especially on mobile devices. In contrast, HarmonyOS stands out for its flexibility and multi-device integration, making it ideal for the IoT ecosystem. However, this flexibility has limitations on energy efficiency and performance of some devices. The study concludes that iOS is suitable for users who prioritize a stable and exclusive experience, while HarmonyOS is more ideal for those who need the flexibility of an open ecosystem.    
Analisis Komprehensif Metode Manajemen Penyimpanan dalam Sistem Operasi Cloud Hendra Parsaulian; Yudi Fermana; Elkin Rilvani
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4540

Abstract

The main focus of this research is to examine data storage efficiency methods, algorithm scheduling, and resource usage optimization techniques. This research uses literature study methods and simulation experiments to analyze system performance. The research results show that storage management methods based on deduplication and data compression have significant efficiency in reducing storage space requirements. The implications of this research include improving cloud system performance and reducing operational costs.
Co-Authors Abdul Rokim Abid Lu’ay Raihan Taufik Agung Nugroho 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 Trisnawan, Ahmad Budi Weni Purnomo1 Widodo , Edy Wisnu Ikhwansyah Saputra Wisnu Setyawan Yoga Pratama, Evan Yudha Purnama Putra Yudi Fermana Zacky Rafian Fawwauzy Zalfa Dewi Zahrani