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Risky Aswi Ramadhani
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Jl. KH. Achmad Dahlan No. 76 Mojoroto, Kota Kediri 64112.
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INDONESIA
Generation Journal
Published by Universitas Nusantara PGRI Kediri
ISSN : 25804952     EISSN : -     DOI : https://doi.org/10.29407
Core Subject : Science,
Computer Science & IT
Generation (Genius Research Implementation Of Information Technology) Journal diterbitkan oleh Universitas Nusantara PGRI Kediri dan dikelola oleh Prodi Teknik Infomatika Universitas Nusantara PGRI Kediri. Tujuan dari Jurnal ini adalah untuk memfasilitasi publikasi ilmiah dari hasil-hasil penelitian di Indonesia dan berpartisipasi untuk meningkatkan kualitas dan kuantitas penelitian untuk akademisi dan peneliti dalam bidang teknologi informasi. GENERATION Journal diterbitkan setiap bulan Januari dan Juli.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 10 No 1 (2026): Generation Journal" : 5 Documents clear
Implementation of the SAW Method for Mobile Phone Selection Recommendations at Holida Seluler Store Mu'afi, Achmad Faiq; Rohman, M Ghofar; Zamroni, Moh 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.v10i1.26505

Abstract

Public demand for mobile phones continues to increase as mobile phones evolve as tools for communication, work, entertainment, and access to digital information. With so many products with varying specifications to choose from, consumers often find it difficult to determine which mobile phone suits their needs. Holida Seluler, a store that sells various types of mobile phones, still uses a manual approach in providing recommendations to customers, which can potentially result in inaccurate decisions. This study aims to develop a website using the Simple Additive Weighting (SAW) method to assist customers in determining the best mobile phone, as well as to design a system capable of presenting objective calculation results based on predetermined criteria weights that can be directly applied in the recommendation process. The data used consists of 50 mobile phone products available in stores, with seven main criteria, namely: price, RAM, internal memory, camera, battery capacity, screen, and refresh rate. This system was built using the PHP programming language and MySQL database. The implementation results show that the system can objectively rank mobile phones based on user preferences, with the A45 alternative as the best choice, obtaining the highest score of 0.9100. This system is capable of providing fast, accurate, and data-driven recommendations, thereby increasing service effectiveness and enhancing the customer experience in choosing the right product
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
Epistemological and Axiological Analysis of ResNet18-Based Dysgraphia Classification Kirana, Kartika Candra; Handayani, Anik Nur; Patmanthara, Syaad
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.v10i1.27419

Abstract

Based on an ontological perspective, there is a gap in feature representation and in binary dysgraphia classification using ResNet18, an area that has not been explored simultaneously. Thus, our contribution is an analysis of research on dysgraphia classification using ResNet18 that employs epistemological and axiological approaches. ResNet18 was chosen as the backbone of the proposed framework because it has shortcut connections that can degrade residues into useless features. As a representation of new knowledge, ResNet18 was pre-trained on ImageNet. Classification was tested on challenging word assignments, comprising 145 dysgraphia images and 188 non-dysgraphia images. Epoch trials were conducted to find the best architecture. The results showed that ResNet18 at epoch 10 achieved the best performance in binary classification, with a recall of up to 93.55%. This indicates that ResNet18 is sensitive to recognizing dysgraphia classes. Challenges outlined in this study serve as a foundation for further research.
Development of a CNN-Based Knowledge System for Rupiah Currency Authenticity Detection and Nominal Classification Romadhon, Ahmad Sahru; Patmanthara, Syaad; Handayani, Anik Nur
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.v10i1.27464

Abstract

The circulation of counterfeit money in Indonesia inflicts substantial losses on the public and financial institutions. Manual verification of money is inefficient and error-prone, especially during high transaction volumes, because counterfeit bills exhibit physical characteristics nearly identical to genuine currency. To uncover counterfeit notes, an ultraviolet lamp exposes invisible ink. This research employs the Convolutional Neural Network (CNN) to detect authenticity and classify Indonesian rupiah banknotes. The CNN is trained using images of authentic banknotes captured with a camera and ultraviolet light across various denominations. The system stores the images and trains the model to identify authenticity and denomination features. Experimental results demonstrate that the proposed approach achieves high classification accuracy in distinguishing genuine and counterfeit Rupiah banknotes, as well as in recognising their respective denominations. The testing phase introduces real notes exposed to ultraviolet light, producing images that reveal invisible ink patterns. The authenticity detection achieved a 100% success rate, while the denomination recognition rates were 70% for Rp. 5,000 notes, 80% for Rp. 10,000 and Rp. 20,000 notes, and 90% for Rp. 50,000 and Rp. 100,000 notes. The system’s overall success rate is 82%.
Use of API in Data Warehouse Integration for One Data Stunting Presentation Tohir, Arik Sofan; Wiseno, Bambang; Zulvana, Zulvana
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.v10i1.27602

Abstract

The Office of Population Control, Family Planning, Empowerment of Women and Child Protection (DP2KBP3A) of Kediri Regency is one of the key government agencies responsible for stunting management. To monitor the current status of stunting in the region, DP2KBP3A utilizes the 'Aksipenting' application (Stunting Monitoring Integration Application), a platform designed for stunting data entry across Kediri Regency. Beyond stunting monitoring, Aksipenting is also employed to track the health conditions of prospective brides, pregnant women, and postpartum mothers. The system processes data across three hierarchical levels: the cadre level, the district level, and the regency level. While DP2KBP3A manages comprehensive stunting data through this application, data integration across Regional Government Agencies (OPD) continues to face challenges regarding standarization and interoperability. This study aims to design and implement a Data Warehouse-based Application Programming Interface (API) to support the 'One Data Stunting' policy across various agencies. The system development follows a Research and Development (R&D) approach using the Rapid Application Development (RAD) method to produce a reliable, standarized, and accessible data integration solution as a foundation for decision-making in accelerating stunting reduction

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