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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 Journal of Social Research 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) Jurnal Cakrawala Ilmiah 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 CommLine Expert Net: Exploration Journal of Technological Education Trends Joong-Ki Jurnal Pengabdian Kepada Masyarakat 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 Public Health Social Sciences Other

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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.
Strategi Teknik Debugging untuk Sistem Operasi Windows Herlan Wibowo; Muhamad Faisal Ilham; Elkin Rilvani
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : 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.v2i4.4558

Abstract

The debugging process is a critical step in software development, especially for the Windows operating system, which offers various tools and techniques to address software issues. This study explores debugging strategies such as logging, memory analysis, real-time debugging, reverse engineering, and compilation-based techniques to identify and resolve problems such as memory leaks and unresponsive applications. Results indicate that selecting the right debugging method depends on the type and complexity of the problem, with a combination of methods often yielding the best outcomes. This study provides practical guidance for Windows users to enhance debugging effectiveness in resolving system and application issues.
Keberhasilan Branding SUKO Fashion di Matahari MUHAMAD BINDARA SAOT; Daud Muzzaki; Dafi Andin Muhamad; Elkin Rilvani
CommLine Vol 11, No 1 (2026)
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/cl.v11i1.5631

Abstract

Penelitian ini bertujuan untuk melakukan analisis mendalam terhadap faktor penentu keberhasilan dan sisa hambatan operasional dalam strategi branding private label SUKO Fashion di PT Matahari Department Store Tbk (LPPF) sepanjang periode longitudinal 2025-2026. SUKO dikembangkan sebagai Exclusive Anchor Brand dengan gaya estetika minimalis Jepang untuk meningkatkan kontribusi margin perusahaan melalui strategi premium positioning. Metode yang digunakan adalah deskriptif kualitatif dengan teknik Netnografi terhadap ribuan interaksi digital di TikTok dan Instagram, serta studi dokumentasi longitudinal pada laporan keuangan korporasi. Hasil penelitian menunjukkan bahwa keberhasilan finansial SUKO divalidasi oleh laba bersih LPPF 2025 sebesar Rp725,4 miliar dan pertumbuhan laba kuartal I-2025 yang mencapai 97%. Keberhasilan ini didorong oleh persepsi positif terhadap kualitas bahan (linen) dan efektivitas peremajaan citra merek korporasi. Namun, ditemukan hambatan kritis berupa ketidaksesuaian harga antar saluran distribusi (kegagalan omnichannel) serta konflik citra dengan budaya diskon massal perusahaan induk yang terekam jelas dalam pola aduan konsumen di ruang siber. 
LITERATUR REVIEW: PELANGGARAN ETIKA TEKNOLOGI INFORMASI KASUS KEBOCORAN DATA PADA MARKETPLACE DI INDONESIA Rizqi Saputri; Asmil Januar; Elkin Rilvani
Jurnal Cakrawala Ilmiah Vol. 5 No. 11 (2026): Juli 2026
Publisher : Bajang Institute

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

Abstract

Di tengah pesatnya transformasi digital, data telah menjadi sumber daya utama yang menopang berbagai sektor, mulai dari bisnis, layanan publik, hingga pemerintahan. Marketplace menjadi salah satu bentuk nyata dari transformasi digital ini, di mana interaksi antara penjual dan pembeli dilakukan sepenuhnya secara daring. Namun, kemudahan yang ditawarkan oleh marketplace sering kali diiringi dengan permasalahan hukum, terutama terkait dengan keamanan data pribadi pengguna (Aryanti, 2023). Kebocoran data pribadi yang melibatkan jutaan pengguna marketplace di Indonesia menunjukkan masih lemahnya perlindungan hukum terhadap privasi digital. Kasus kebocoran data Tokopedia pada tahun 2020, kebocoran sekitar 91 juta data pengguna Tokopedia pada tahun 2020. Informasi penting seperti nama lengkap, alamat email, nomor telepon, hingga password hash diretas dan dijual melalui dark web. Peretasan ini diperkirakan terjadi pada Maret 2020 dan baru terungkap beberapa bulan kemudian setelah data tersebut diperdagangkan di forum daring. Profesional TI berkewajiban untuk menjaga kerahasiaan informasi, memastikan integritas sistem, dan meminimalkan risiko yang dapat merugikan masyarakat. Prinsip-prinsip tersebut menekankan pentingnya tanggung jawab moral dan profesional dalam menangani data sensitif. Pelanggaran terhadap prinsip ini dapat menyebabkan kerugian besar, baik bagi individu maupun organisasi, serta merusak kepercayaan publik terhadap layanan digital.
Systematic Literature Review: Profiling Mahasiswa Menggunakan Metode Decision Tree Aries Widyantoro; Fiqhy Faradisa Al Bina; Elkin Rilvani
Journal Of Informatics And Busisnes Vol. 3 No. 1 (2025): April - Juni
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i1.2819

Abstract

Abstract This study aims to systematically review the application of the Decision Tree method in student profiling activities using the Systematic Literature Review (SLR) approach. By analyzing 15 relevant scholarly articles, this research evaluates the techniques employed, the effectiveness of the Decision Tree method, and the most commonly used algorithms. The findings reveal that Decision Tree is one of the most widely used classification methods in education due to its ability to simplify decision-making processes and produce interpretable models. Algorithms such as ID3, C4.5, CART, and Random Forest are frequently applied in various studies, especially for academic performance prediction, dropout risk assessment, and student potential mapping. This study concludes that Decision Tree is an effective, efficient, and relevant method for supporting educational data analysis and evidence-based decision-making.
Implementasi Data Mining dengan Metode K-Means dan FCM untuk Analisis Pola Pembelian Konsumen Online Rio Rinto Saki; Rizky Juniarko Taruna Putra; Elkin Rilvani
Journal Of Informatics And Busisnes Vol. 3 No. 2 (2025): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i2.3106

Abstract

This study explores the implementation of data mining techniques using K-Means and Fuzzy C-Means (FCM) clustering methods to analyze online customer purchasing patterns. The focus of the analysis lies in identifying similarities and segmenting customers based on their transaction behaviors. By using datasets collected from e-commerce platforms during the 2022–2023 period, the study evaluates the effectiveness of each algorithm in discovering meaningful clusters. The results indicate that both methods can group consumers based on purchasing trends, with FCM offering better flexibility due to its fuzzy membership assignment. This clustering approach can support decision-making in targeted marketing, product recommendations, and customer relationship management.
Sentiment Analysis of TikTok User Reviews on Google Playstore Using Naïve Bayes Methods Indra Prakoso; Andhika Aziz Bachtiar; Elkin Rilvani
Journal Of Informatics And Busisnes Vol. 3 No. 2 (2025): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i2.3297

Abstract

interactions, one of which is TikTok. The TikTok platform has become a global phenomenon favored by many, especially the younger generation. As the number of users increases, reviews on digital platforms such as the Google Play Store become an important source for understanding users' perceptions of the application. Therefore, a deep understanding of user sentiment toward TikTok is essential for better app development and effective marketing strategies. To analyze TikTok user sentiment, this study employs two well-established computational methods: Support Vector Machine (SVM) and Naïve Bayes. These methods are used to classify user reviews into positive or negative sentiment categories. The approach involves several stages, including data collection, data preprocessing, data splitting, sentiment classification, and model evaluation. The study shows that the SVM model achieved an accuracy of 88.76% with an AUC of 92.61%, outperforming Naïve Bayes, which achieved an accuracy of 84.27% and an AUC of 92.57%. In the positive sentiment category, SVM recorded a precision of 90.74% and a recall of 95.15%, while Naïve Bayes yielded a precision of 83.61% and an almost perfect recall of 99.03%. For negative sentiment, SVM showed a precision of 80.39% and recall of 67.21%, whereas Naïve Bayes had a higher precision of 91.30% but a lower recall of 34.43%, with a lower F1-score of 50%.
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.
KLASIFIKASI VOLATILITAS HARGA DAGING AYAM DAN CABE RAWIT MERAH DENGAN DECISION TREE Mohamad Hegar Sukmana Wibowo; Muhammad Din Al Ayubi; Elkin Rilvani
Jurnal Komputer dan Teknologi Vol 4 No 2 (2025): JUKOMTEK JULI 2025
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v4i2.455

Abstract

Price fluctuations of key food commodities such as chicken meat and red bird’s eye chili exhibit significant volatility patterns in Bekasi Regency, impacting consumers, producers, and local government authorities. This study aims to classify the level of price volatility for these two commodities using the Decision Tree C4.5 algorithm. Daily price data for the year 2024 were obtained from the Department of Communication, Informatics, Cryptography, and Statistics of Bekasi Regency, then processed and analyzed using RapidMiner with an 80:20 training-to-testing data ratio. The classification results show that the C4.5 algorithm achieved an accuracy of 93.84% for chicken meat prices and 80.56% for red chili prices. These findings demonstrate the effectiveness of the C4.5 algorithm in recognizing price volatility patterns and its potential in supporting decision-making for regional price monitoring systems and early warning mechanisms for market shocks. This research offers practical contributions to government efforts in price stabilization.
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 Siswandi ARIF SUSILO Arif Susilo Arif Tri Widiyatmoko Ariza, Rini Arya Saepul Hakim Asep Muhidin Asep Muhidin Asep Saepuloh Asmil Januar Bagoes Ramadhan Baihaqi Asa’ari Lubis Bayu Nugroho Butsianto, Sufajar Candra Naya Catur Pranomo Dafi Andin Muhamad Daud Muzzaki 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 Ikhsan Romli Indra Permana Indra Prakoso Indry Widiyani Iwan Mulyana Johan Mohammad Palah Khaerunnisa Isnaeni Lestari Khairunnisa Nasution Kristiyanto, Yogi Lili Fadli Muhamad Listian Indriyani Achmad Ma'ruf Setiadi2 Maharani , Tyanshi Firli Mikael Rivaldo Mochammad Rahmat Faisal Mohamad Hegar Sukmana Wibowo Monika Pakpahan MUHAMAD BINDARA SAOT Muhamad Daffa Maulana Arrasyid Muhamad Faisal Ilham Muhamad Fatchan Muhammad Akmal Ar Rasid Muhammad Albedri MUHAMMAD ARIFIN Muhammad Din Al Ayubi Muhammad Farhan Fahreza Muhammad Hegar Sukmana Muhammad Nur Falah Muhammad Rifki Febrianto Muhammad Rizal Mantofani Muhammad Rizky Raka muhidin, asep Muhtajuddin Danny Nabilla Kusuma Wijaya Nadia tul umah Nawangsih, Ismasari Naya, Candra Naza Sefti Prianita Novant Nanda Pradana Novi Wulandari Novianto Andi Hardiansyah Nur Hasim Nur Hidayati Nurhadi Surojudin Nurkholik Safrudin Ovi Marzuki Panji Anwar Sanusi Pardede, Debora Hizkhia Prasetyo, Fabian Eka Priasnyomo Prima Santoso Putra, Aan Fadillah Rafi Maulana Firdaus Rafli Maulana Ramadhan Ardi Iman Prakoso Reza Maulana, Muhammad Rio Rinto Saki Rizki Fahrizal Rizki Muhammad Rizky Juniarko Taruna Putra Rizqi Saputri 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 Trisnawan, Ahmad Budi Weni Purnomo1 Widodo , Edy Wisnu Ikhwansyah Saputra Wisnu Setyawan Yoga Pratama, Evan Yos Soejarminto Yudha Purnama Putra Yudi Fermana Zacky Rafian Fawwauzy Zalfa Dewi Zahrani