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All Journal TEKNIK INFORMATIKA Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik JURNAL ILMIAH INFORMATIKA Generation Journal Jurnal Mnemonic Jurnal Teknik Informatika (JUTIF) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Abdimas Terapan Dedication : Jurnal Pengabdian Masyarakat
M. Rosidi Zamroni
Program Studi Teknik Informatika, Fakultas Teknik, Universitas Islam Lamongan
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Engineering Immunology & microbiology Social Sciences Other

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Decision Support System For Determining The Major Of New Students At SMKS Sunan Drajat Sugio Using The Method SAW (Simple Additive Weighting) Rohma, Riska Dwi Elida Yahyatul; Rohman, M. Ghofar; Zamroni, M. Rosidi
Generation Journal Vol 10 No 1 (2026): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v10i1.26553

Abstract

Determining majors for new students at vocational schools is an important process that can affect student achievement and future prospects. However, this process is often still carried out manually and is not very objective, which can potentially lead to a mismatch between the chosen major and the potential and interests of the students. Therefore, a system is needed that can help schools determine majors more accurately, efficiently, and based on data. This study aims to design a Decision Support System (DSS) for determining the majors of new students at SMKS Sunan Drajat Sugio using the Simple Additive Weighting (SAW) method. The SAW method was chosen because of the ease of calculation and its ability to process multi-criteria data to produce systematic decisions. The criteria used in this system include report card averages, basic competency test results, and student interests. This system is web-based with a user-friendly interface. Testing was conducted using 65 new student data for the 2024/2025 academic year by comparing the system's calculation results with manual calculations using the SAW method that had been validated by the school. The test results showed a 100.0% match between the system results and manual calculations, indicating that the system is capable of implementing the SAW method accurately and consistently. Thus, the developed system can be used as a tool to assist
Implementation of the Content-Based Filtering Method in Menu Recommendations at Pandawa Pondok Kopi Saputra, Muhammad Hanes Eka; Rohman, M.Ghofar; Zamroni, M.Rosidi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1838

Abstract

The rapid growth of the coffee shop industry and the wide variety of menu offerings at Pandawa Pondok Kopi demand a system capable of delivering accurate and personalized menu recommendations. This study aimed to develop a web based menu recommendation application using Content Based Filtering (CBF), leveraging TF-IDF for document vectorization and Cosine Similarity to measure product description similarity.The system was implemented with PHP and MySQL, featuring a responsive interface across three main modules: the homepage (displaying the menu list), the menu detail page (providing full information and similar recommendations), and the admin dashboard (for menu data management). Menu descriptions were preprocessed (tokenization, stop word removal, and stemming) before computing TF-IDF weights. Given a user’s selected menu item, the system calculated Cosine Similarity between its description vector and those of all other menu items, then presents the top three matches. Functionality was verified via Black Box Testing to ensure that admin login, menu addition/editing, recommendation displays, and interface navigation conform to specifications. Test results showed an average Cosine Similarity score ranging from 0.62 to 0.78, indicating satisfactory accuracy in matching user preferences. The system also achieved an average response time of under one second under standard load, meeting efficiency criteria.In conclusion, the Content Based Filtering implementation successfully enhances the relevance of menu recommendations and user experience, thereby supporting increased customer satisfaction and operational effectiveness at Pandawa Pondok Kopi.
Co-Authors Abdul Kholiq Agung Wahyudi Ahmad Fauzi Hendratmoko Alfarisi, Muhammad Nur Fikri AlMuhibbi, Muhammad Rayendra Anam, M. Khairul Azizah, Luluk Nur Azza Abidatin Bettaliyah AZZA ABIDATIN BETTALIYAH Dinar Mahdalena Leksana 1 Erna Hayati, Erna Erry Anggraini ERRY ANGGRAINI Farizki, Achmad Nurasel FATHARANI, ATIKA Fatkhul U, M. Miftah Firdaus, Muhammad Alvin Fudzee, Mohd Farhan Md Hamid, Rahayu A Ismail, Mohd Norasri KIKI SEPTARIA Lilik Anifah M. Ghofar Rohman M. ZAKI QOMARUDDIN Miftahus Sholihin Mufrody, Moh Adam Nurroziqin, M Chabib Nurul Aswa Omar Prastowo, Diko Prsatama, Febrian Abie Qabilah Cita K. N. S Rahayu A Hamid Retno Wardhani Rohma, Riska Dwi Elida Yahyatul Saputra, Muhammad Hanes Eka Siti Mujilahwati Sulaiman, Akhmad Nurali Umam, Moch. Zuhrul Zirby, Qonit