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All Journal Tech-E bit-Tech Journal of Applied Computer Science and Technology (JACOST) Algor
Alexius Hendra Gunawan
Universitas Buddhi Dharma
Computer Science & IT

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Journal : bit-Tech

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Analysis and Design of ERP Information Systems Using User Acceptance Test Method Aditya Kristianto Santoso; Alexius Hendra Gunawan
bit-Tech Vol. 7 No. 3 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i3.1666

Abstract

Information technology that continues to develop supports companies in carrying out their business activities. Computerized company information technology is needed in this modern era. Therefore, Enterprise Resource Planning information systems are needed in carrying out the company's business processes, Enterprise Resource Planning information systems with purchasing, sales, and inventory modules can assist companies in planning business processes. The design of this Enterprise Resource Planning application information system aims to assist companies and employees in carrying out the transaction process. The method used for developing this application is to use the waterfall motede. The waterfall method is a software development method that uses a systematic and sequential approach, so that the quality of the resulting system will be optimal. In addition, the research method in developing this software uses a User Acceptance Test where the results of the proposed system have been verified through interviews filling out questionnaires so as to produce a system that suits user needs. This system was built to meet user needs to produce accurate and systematic inventory, sales and purchase reports. Thus, users do not need to worry about errors in processing company transaction data. The conclusion obtained is that the system built is able to assist users in inputting transactions and make it easier for stakeholders because this information system is made web-based so that it can be accessed anywhere and anytime, and makes work time more effective.
Eksplorasi Algoritma Support Vector Machine untuk Analisis Sentimen Destinasi Wisata di Indonesia Junaedi; Alexius Hendra Gunawan; Verri Kuswanto; Jonathan
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1810

Abstract

Penelitian ini mengeksplorasi penerapan algoritma Support Vector Machine (SVM) dalam Text Mining untuk analisis sentimen sektor pariwisata di Indonesia, menggunakan data dari platform Twitter. Data dikumpulkan melalui API Twitter dan diproses melalui tahapan prapemrosesan teks, termasuk tokenisasi, normalisasi, penghapusan stopword, dan stemming, untuk memastikan kesiapan data dalam analisis. Model SVM diuji dengan tiga kernel berbeda—linear, radial basis function (RBF), dan sigmoid—serta menggunakan rasio data latih-uji 7:3 dan 8:2. Hasil menunjukkan bahwa kernel linear dengan rasio 7:3 menghasilkan kinerja terbaik dengan akurasi 92,89%, precision 92%, recall 74%, dan F1-score 81%. Evaluasi berdasarkan kelas sentimen menunjukkan performa tinggi pada sentimen positif (F1-score 96%) tetapi moderat pada kelas netral (F1-score 67%), mencerminkan pengaruh ketidakseimbangan data. Penelitian ini memberikan kontribusi signifikan dalam mendukung pengambilan keputusan berbasis data untuk pengembangan sektor pariwisata. Temuan ini memungkinkan pengelola destinasi wisata untuk memahami opini wisatawan secara otomatis, menyusun strategi promosi yang lebih efektif, serta meningkatkan kualitas layanan. Dengan menerapkan analisis sentimen berbasis SVM, penelitian ini mendukung pengelolaan pariwisata berbasis data untuk meningkatkan daya saing destinasi wisata di Indonesia. Penelitian lanjutan disarankan untuk mengatasi ketidakseimbangan data melalui teknik resampling atau penerapan algoritma alternatif seperti deep learning, guna meningkatkan akurasi klasifikasi sentimen yang lebih kompleks. Dengan demikian, penelitian ini menjadi langkah strategis dalam memanfaatkan teknologi analitik untuk pengelolaan pariwisata yang lebih inovatif.
Co-Authors Aditya Kristianto Santoso Amat Basri Andri Wijaya Dede Kurniawan Dellih Wijaya Jonathan Junaedi Lily Damayanti Muhammad Reza Ilham Samuel Ryon Elkana Suwitno Suwitno Tugiman Verri Kuswanto