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Ardi Susanto
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informatika.ejournal@poltektegal.ac.id
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Gedung B, Politeknik Harapan Bersama, Jl Mataram No 9 Pesurungan Lor Kota Tegal
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INDONESIA
Jurnal Informatika: Jurnal Pengembangan IT
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Articles 414 Documents
Optimaliasi Desain UI/UX Pada Platform E-commece Alat Kesehatan dengan Pendekatan User Centered Design Wardhanie, Ayouvi Poerna; Effendi, Pradita Maulidya
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8816

Abstract

E-commerce is a new type of business in which all business processes—such as ordering, payment, and delivery—can be carried out online through applications, whether on websites or mobile platforms. Today, almost all businesses utilize e-commerce as a platform for selling, including those in the medical equipment industry. PT. Wanbass Timur Persada is a company based in Surabaya that specializes in the sale of medical equipment. The main issue faced by the company is the limited reach of its promotional efforts and the dissemination of information to its target consumers, which has resulted in low product sales. Therefore, an e-commerce platform is needed to facilitate broader information dissemination and to streamline the ordering, payment, and delivery processes. In developing e-commerce, besides ensuring functionality, attention must also be paid to several design elements such as layout, images, colour scheme, typesetting, navigation, and content. The method used in this research is User-Centered Design, as it focuses on an iterative approach, usability, user characteristics, environment, tasks, and workflow. The result of this study is an e-commerce prototype featuring a product catalog, ordering process, payment, and delivery. It also applies a simple layout, varied images, a website colour combination, easy-to-read font styles, and comprehensive information.
Implementasi Algoritma Support Vector Regression untuk Prediksi Harga Emas Berdasarkan Data Historis Hidayatulloh, M Rizqi; Yuwono, Dwi Purbo
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9233

Abstract

Amidst global economic volatility, accurate forecasting of gold prices remains a crucial and challenging task for investors and financial policymakers, as gold functions as a vital safe-haven asset and a hedge against inflation. This study focuses on gold price prediction utilizing the Support Vector Regression (SVR) algorithm, with the main objective of improving forecast accuracy. The relevance of this prediction is underpinned by the dynamic characteristics of gold prices, which is essential for decision-making by various stakeholders. Historical gold price data were obtained from the investing.com platform. The SVR implementation was carried out utilizing the Radial Basis Function (RBF) kernel. The SVR parameter optimization process employing Grid Search successfully identified the optimal values, namely C=1000, ϵ=0.5, and γ=0.01. To ensure model robustness and generalization capability, validation was performed using 5-Fold Cross Validation, which yielded an average Mean Absolute Percentage Error (MAPE) of 0.66%. The very high level of SVR accuracy, alongside its consistency across each fold, stability, and reliability, indicates that the optimized SVR model is a prospective solution for gold price forecasting in the commodity market.
Pengembangan Aplikasi Chatbot Untuk Layanan Penerimaan Mahasiswa Baru Berbasis Natural Language Processing Setiyorini, Agustin
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9406

Abstract

Abstrak – Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan sistem chatbot berbasis Natural Language Processing (NLP) untuk mendukung layanan informasi Penerimaan Mahasiswa Baru (PMB) di Universitas Janabadra. Layanan PMB selama ini masih bergantung pada interaksi manual yang terbatas pada jam kerja. Oleh karena itu, diperlukan solusi digital yang mampu memberikan informasi secara cepat, akurat, dan real-time. Sistem dikembangkan menggunakan framework CodeIgniter 4 dan memanfaatkan algoritma Naive Bayes untuk klasifikasi intent serta Levenshtein Distance untuk pencocokan kemiripan teks. Dataset pelatihan disusun berdasarkan kumpulan pertanyaan umum calon mahasiswa. Hasil evaluasi menunjukkan bahwa chatbot mampu menjawab 70% dari 500 pertanyaan secara otomatis dengan akurasi 92% dan waktu respons rata-rata 0,5 detik. Selain itu, chatbot mampu menurunkan beban kerja staf administrasi hingga 30%. Survei terhadap 100 pengguna menunjukkan bahwa 85% responden merasa puas terhadap kecepatan dan keakuratan respons sistem. Sistem ini juga mendukung penyimpanan konteks percakapan dan integrasi langsung dengan informasi PMB universitas. Penelitian ini menyimpulkan bahwa chatbot berbasis NLP dapat menjadi solusi efektif dalam meningkatkan efisiensi layanan informasi pendidikan tinggi. Pengembangan lanjutan diarahkan pada perluasan dataset, adopsi model NLP berbasis Transformer, serta integrasi lintas platform komunikasi untuk memperluas jangkauan layanan. Kata Kunci: Chatbot, Natural Language Processing, Naive Bayes, Levenshtein Distance, Penerimaan Mahasiswa Baru.
Pengembangan Aplikasi Prediksi Harga Emas Berbasis Web Menggunakan Model Time Series Abdullah, Fikrian Nur; Nurardian, Ridwana Septian; Liya, Amel; Saputra, Ari Setia; Saputra, Atio Wahyudi; Bismi, Waeisul
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9165

Abstract

High gold price volatility due to global economic instability poses challenges in investment decision-making. This research aims to develop a web-based gold price prediction application using a time series model, focusing on the Gated Recurrent Unit (GRU) algorithm. This application is designed to present real-time, accurate, and easily accessible gold price predictions, thereby increasing the efficiency and transparency of information for investment decision making. The development process starts from collecting and preprocessing daily gold price data for the period 2013-2023, then comparing four predictive models: LSTM, GRU, ARIMA, and XGBoost. Evaluation is performed using MAE, RMSE, and R² metrics. Results showed that GRU provided the best performance with an RMSE value of 17.76 and R² of 0.9410. The GRU model is integrated into a web application using the Flask framework, with an interactive HTML-based interface and Chart.js visualization. This application presents real-time gold price predictions and can be accessed by general users and investors. The results of this study show that the time series approach with GRU is effective in projecting gold prices, and can be a relevant tool in supporting data-based investment decisions.