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All Journal SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal PIKOM (Penelitian Komunikasi dan Pembangunan) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) SEIKO : Journal of Management & Business Jiko (Jurnal Informatika dan komputer) Journal of Secretary and Business Administration MIND (Multimedia Artificial Intelligent Networking Database) Journal Progresif: Jurnal Ilmiah Komputer Syntax Idea Jurnal Ilmiah Edunomika (JIE) E-Link: Jurnal Teknik Elektro dan Informatika JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Darma Agung JOINT (Journal of Information Technology Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat Indonesia JURNAL ILMIAH GLOBAL EDUCATION JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence Prosiding Konferensi Nasional PKM-CSR Jurnal Algoritma Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Engineering Continuity
Sulianta, Feri
Universitas Widyatama
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Mechanical Engineering Nursing Public Health Social Sciences Other

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Revealing Consumer Preferences in the Fashion Industry Using K-Means Clustering Sulianta, Feri; Ulfah, Khaerani; Amalia, Endang
International Journal of Engineering Continuity Vol. 3 No. 2 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i2.280

Abstract

The fashion industry, driven by rapidly shifting e-commerce trends and consumer preferences, demands precise data analysis to optimize marketing strategies and enhance customer satisfaction. This study utilizes data mining techniques, specifically K-Means Clustering and the Elbow Method, to reveal consumer preferences within a dataset of 1,000 fashion product sales records, which include attributes such as product ID, name, brand, category, price, rating, color, and size. By grouping data into distinct clusters based on price and rating preferences, the analysis uncovers four key consumer segments. The optimal number of clusters is confirmed using the WCSS (Within-Cluster Sum of Square) method. These insights offer valuable guidance for refining marketing strategies in the fashion industry. Future research should consider additional variables and employ advanced tools for deeper analysis.
ATURAN ASOSIASI MENGGUNAKAN ALGORITMA APRIORI UNTUK MENCIPTAKAN STRATEGI PEMASARAN PADA APOTEK Sulianta, Feri; Prayogo, Eriko
E-Link: Jurnal Teknik Elektro dan Informatika Vol 19 No 1: Mei 2024
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v19i1.5951

Abstract

The sales of pharmaceutical products among the public are increasing, especially with the recent pandemic that has led to an increase in drug sales. This has created significant potential for the pharmaceutical industry or drug sales businesses. However, proper marketing plans are required in the pharmaceutical industry to optimize revenue. Analyzing drug sales trends can provide valuable insights for creating excellent marketing plans. To develop a superior marketing plan, an analysis of sales transaction data is necessary with the help of data mining, which is useful for obtaining important information from the dataset being analyzed. The Apriori algorithm is used in this research to examine association rule patterns of drug sales in pharmacies The sales information used as dataset is consisting of 600,000 transactional data collected over six years (2014–2019). This dataset includes the date and time of sales, pharmaceutical drug brands, and other relevant information.
Edukasi mengenai Mobile Hacking: Pengenalan dan Mitigasi Puspitarani, Yan; Rumaisa, Fitrah; Violina, Sriyani; Sulianta, Feri; Rosita, Ai
SEIKO : Journal of Management & Business Vol 6, No 2.1 (2023)
Publisher : Program Pascasarjana STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/sejaman.v6i2.5890

Abstract

Data merupakan hal yang berharga dan bersifat pribadi bagi perseorangan maupun perusahaan. Akan tetapi, pencurian data seringkali dilakukan terhadap sistem keamanan data yang memiliki celah. Hacking ini sudah marak dilakukan oleh kalangan muda. Jika tidak diarahkan dengan baik, besar kemungkinan banyak generasi muda yang menjadi pelaku cyber crime. Selain itu, untuk melakukan investigasi terhadap cyber crime, diperlukan juga digital forensic terhadap perangkat. Oleh karena itu, kegiatan pengabdian ini, akan memberikan edukasi kepada para anak SMA sebagai generasi muda dengan harapan agar para generasi muda tidak menjadi korban atau pelaku. Kata Kunci: hacking; forensic; cyber crime.
Analisis Klasterisasi Data Peserta Asuransi PT Xyz Menggunakan Metode Denisty-Based Spatial Clustering of Applications with Noise (DBSCAN) Fathur Rizki, Muhamad; Sulianta, Feri
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2417

Abstract

Penelitian ini bertujuan untuk menganalisis klasterisasi data peserta asuransi di PT XYZ menggunakan algoritma Density-Based Spatial Clustering of Applications with Noise (DBSCAN). Atribut utama yang digunakan dalam proses klasterisasi adalah usia, pekerjaan, dan gaji. Aplikasi berbasis web dikembangkan menggunakan Laravel untuk frontend/backend dan Python (Flask) untuk pemrosesan data dan implementasi DBSCAN. Data yang dikumpulkan dari file Excel yang di unggah diproses melalui REST API, dan hasil klasterisasi dievaluasi menggunakan Silhouette Coefficient untuk menilai validitas klaster. Analisis berhasil mengidentifikasi 16 klaster utama dan 1 kategori noise, dengan klaster dominan berisi lebih dari 4.800 peserta. Skor Silhouette Coefficient sebesar 0,74 menunjukkan struktur klasterisasi yang kuat dan valid, menyoroti efektivitas DBSCAN dalam mengidentifikasi pengelompokan yang padat dan mendeteksi outlier. Hasil ini dapat digunakan untuk lebih memahami profil peserta dan mendukung pengambilan keputusan di masa mendatang dalam perencanaan program asuransi dan strategi pemasaran.
Implementasi dan Analisis Algoritma Content-Based Filtering Pada Sistem Rekomendasi Produk Tas pada Basis Data MySQL Pranata, Aryoga; Sulianta, Feri
Jurnal Ilmiah Global Education Vol. 6 No. 3 (2025): JURNAL ILMIAH GLOBAL EDUCATION
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i3.4017

Abstract

Recommendation systems have become a crucial component in various digital platforms to enhance user experience by providing relevant product suggestions. This research aims to implement and analyze the Content-Based Filtering (CBF) algorithm in a product recommendation system using the MySQL database. The CBF algorithm works by recommending products similar to those already liked or purchased by the user based on the features of those products. In this context, features such as product category, brand, and text description are used to generate relevant recommendations. The implementation of this algorithm involves using Natural Language Processing (NLP) techniques to extract features from product descriptions stored in the database. The first phase of this research involves collecting and processing product data to ensure consistency and readiness for further analysis. Key features of each product are then extracted and their similarities calculated using the CBF algorithm. Subsequently, the recommendation results are tested and evaluated using performance metrics such as Precision and Recall to determine the system's effectiveness in providing relevant and beneficial recommendations to users. The research findings indicate that the CBF algorithm can provide fairly accurate and relevant product recommendations, enhancing user satisfaction by offering product choices that match their preferences. Performance evaluation also demonstrates that the system is effective in recognizing user preference patterns and providing useful suggestions. Additionally, the use of the MySQL database offers advantages in efficient data management and processing. With this recommendation system, it is expected to improve user satisfaction and engagement in the e-commerce platform. The use of CBF techniques enables the system to continually learn and adapt to user preferences, providing increasingly relevant recommendations over time.
Implementasi Algoritma Naïve Bayes untuk Mengevaluasi Reputasi Merek (Studi Kasus: Toko XYZ) Suryaresmana, Rizka Putera; Sulianta, Feri
Jurnal Ilmiah Global Education Vol. 6 No. 3 (2025): JURNAL ILMIAH GLOBAL EDUCATION
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i3.4016

Abstract

Brand reputation assessment is a crucial aspect for companies in maintaining consumer trust and satisfaction. However, evaluating brand reputation is often challenging, especially for companies that lack the resources to perform it manually. This study aims to implement the Naïve Bayes algorithm in evaluating brand reputation, using a case study of Toko XYZ. The Naïve Bayes algorithm is utilized to perform sentiment analysis on text data related to the brand, such as customer reviews, which are then classified into positive, negative, or neutral sentiments. The results of this analysis are expected to provide the company with a deeper insight into consumer perceptions of their brand. This research also aims to support companies in making strategic decisions related to brand reputation management. Based on the findings, the Naïve Bayes algorithm proves to be effective in analyzing customer sentiment, providing companies with a clearer understanding of how their brand is perceived in the market, and enabling them to better respond to consumer needs.
Membangun Learning Management System di SDN 162 Warung Jambu sebagai Media Belajar di Era Digital berbasis Moodle Sulianta, Feri; Rumaisa, Fitrah; Puspitarani, Yan; Violina, Sriyani; Rosita, Ai
Abdimas Galuh Vol 7, No 2 (2025): September 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v7i2.21000

Abstract

Pada era digital, sekolah dituntut untuk meningkatkan kualitas pembelajaran sekaligus memperkuat visibilitas daring sebagai media komunikasi, informasi, dan sarana belajar. Namun, SDN 162 Warung Jambu, Kota Bandung, masih menghadapi kendala karena pembelajaran didominasi metode konvensional dan informasi sekolah belum terintegrasi secara online. Untuk menjawab permasalahan tersebut, kegiatan pengabdian ini mengembangkan platform Learning Management System berbasis Moodle versi 4.3 dengan metode Research and Development menggunakan model Waterfall. Proses pengembangan meliputi analisis kebutuhan, desain sistem, implementasi, pengujian menggunakan metode Black Box, serta pemeliharaan. Hasil pengembangan menghasilkan website e-learning dengan domain https://elearning.sdn162bandung.sch.id/ yang memfasilitasi pembelajaran daring, mulai dari akses materi, pengumpulan tugas, kuis, forum diskusi, hingga pemantauan nilai secara transparan. Pengujian menunjukkan bahwa seluruh fitur pada peran admin, guru, dan siswa berfungsi sesuai kebutuhan tanpa kendala signifikan. Implementasi platform ini meningkatkan efisiensi pembelajaran, memperluas akses informasi akademik, serta memperkuat citra digital sekolah. Dengan demikian, pengembangan e-learning berbasis Moodle terbukti menjadi solusi efektif untuk mendukung transformasi digital sekolah dasar sekaligus mendorong terciptanya ekosistem pendidikan yang modern, adaptif, dan transparan.
Implementation of Kanban Method in Transactional System Design in the “Mr. Sneakers” Shoe Laundry Business Puspitarani, Yan; Violina, Sriyani; Rumaisa, Fitrah; Sulianta, Feri
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.v4i1.3859

Abstract

Laundry information system design using Kanban method is a strategic step to improve operational efficiency and responsiveness to customer needs in the laundry business. The study aims to design an information system that is integrated with the Kanban method to optimize the transaction process from receiving orders to returning to customers. The study outlines the process of designing a laundry information system using Kanban principles, including workflow mapping, suitable Kanban board design and integration with existing information systems. The results of this information system design show that the application of Kanban can provide a clear visualization of the workflow in the process, improve operational efficiency by speeding up the order cycle time, reducing waiting times, and minimizing errors in the transactions process. Good integration between the information system and the Kanban board allows managers to monitor order status in real time and respond quickly to changing customer requests. In conclusion, designing a laundry information system using the Kanban method can improve business performance, strengthen customer relationships, and create significant added value.
Rancang Bangun Website Edukatif di Sekolah SDN 162 Warung Jambu Kiaracondong berbasis Laravel Sulianta, Feri; Rumaisa, Fitrah; Puspitarani, Yan; Violina, Sriyani; Rosita, Ai
Jurnal Pengabdian Masyarakat Indonesia Vol 5 No 4 (2025): JPMI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpmi.3623

Abstract

Dalam era digital, sistem informasi berbasis web menjadi kebutuhan mendesak bagi institusi pendidikan untuk meningkatkan pendistribusikan informasi akademik, dan keterlibatan pendidik, peserta didik serta orang tua siswa. SDN 162 Warung Jambu Kiaracondong menghadapi kendala dalam peningkatan visibilitas dan pendistribusian informasi sekolah yang masih dilakukan secara manual. Oleh karena itu, dilakukan perancang dan pengembangkan situs web sekolah berbasis Laravel menggunakan metode Waterfall sebagai aspek dari digitalisasi pendidikan. Proses pengembangan mencakup analisis kebutuhan, desain, implementasi, pengujian Black Box, serta evaluasi menggunakan alat ukur kualitatif dan deskriptif. Perancangan Antar muka menggunakan metode Design Thinking yang mengakomodasi aspek Interface dan User Experience.  Hasil menunjukkan bahwa situs web ini mampu meningkatkan efisiensi yaitu: mempercepat akses informasi sekolah, serta memperkuat interaksi antara siswa, guru, dan orang tua. Pengujian sistem membuktikan bahwa seluruh fitur berfungsi sesuai dengan spesifikasi yang ditetapkan. Implementasi situs web sekolah ini menjadi solusi yang efektif dalam mendukung digitalisasi pendidikan dan meningkatkan distribusi informasi akademik bagi seluruh pemangku kepentingan di kalangan eduskatif SDN 162 Warung Jambu Kiaracondong.
DEVELOPING AN IT INFRASTRUCTURE MODEL FOR ENHANCING DIGITAL LITERACY THROUGH WEB-BASED LEARNING: A COMPREHENSIVE FRAMEWORK Sulianta, Feri; Rumaisa, Fitrah; Puspitarani, Yan; Violina, Sriyani; Rosita, Ai
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 3 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.8761

Abstract

In today's rapidly evolving educational landscape, there is a growing need to develop an IT infrastructure model that can effectively support web-based learning environments to enhance digital literacy. The proposed model offers a comprehensive framework for educational institutions to integrate digital technologies into their curricula seamlessly. Key elements of the model include essential hardware, user-friendly software, and advanced security measures, each playing a vital role in creating a seamless, secure, and efficient digital learning experience. This study explores the dynamic interactions among these components and their collective influence on fostering a conducive and productive web-based learning environment. By addressing the need for reliable infrastructure, scalable solutions, and robust security protocols, the model provides a holistic approach to improving digital literacy in educational contexts. The research underscores the critical role of a well-structured IT infrastructure in supporting digital education, offering actionable insights and recommendations for implementation. Moreover, it emphasizes that a well-developed IT infrastructure is foundational for the long-term success of web-based learning programs, enabling institutions to meet diverse learner needs, adapt to technological advances, and ensure sustainability in the digital education landscape.
Co-Authors Ahmad Arif Ahmad Zaeni, Ahmad Ai Rosita Amalia, Endang Ari Purno Wahyu Wibowo Aswari Aswari Daud Rifki Gunawan Deden Farhan Dzikriyana Zuhdia Aziz Esa Fauzi Fadllur Rohman, Muhammad Naufal Fathur Rizki, Muhamad Faturrohman, Adit Fitrah Rumaisa Galang Raka Siwi Kautsar Baihaqi Supriyadi Mendonca, Fernando Muharam, Rahman Mutaqin, Safira Mardiyah Philothra Clarissa Raina Pranata, Aryoga Prayogo, Eriko Putri, Vianty Julia Suryana Rachmat, Alam Maulana Rah Utami Nugrahani Rahman Muharam Raina, Philothra Clarissa Reza Syafrian Setiadi Rizky Muhammad Fauzi Rosita, Ai Saputra, Rinaldy Buana Sriyani Violina Suryaresmana, Rizka Putera SY Yuliani Ulfah, Khaerani yakub, sy yuliani yuliani Yan Puspitarani Yenie Syukriyah