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JUSS (Jurnal Sains dan Sistem Informasi)
Published by Universitas Jambi
ISSN : -     EISSN : 26148277     DOI : https://doi.org/10.22437/juss
Core Subject :
JUSS covers a broad range of topics in Information Systems and Computer Science, including but not limited to the following areas: 01. Software Engineering 02. Decision Support Systems 03. Information Systems Security 04. Artificial Intelligence 05. Data Analytics and Visualization 06. Data Science 07. Information Technology Adoption 08. Information Technology Governance
Arjuna Subject : -
Articles 91 Documents
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ANALISIS SENTIMEN ULASAN PELANGGAN APLIKASI LIVIN MANDIRI MENGGUNAKAN METODE ALGORITMA TF-IDF Oktaviani, Hasna; Dina Kalifia, Anna Dina Kalifia
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 7 No. 1 (2024): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v7i1.31214

Abstract

Metode Term Frequency-Inverse Document Frequency (TF-IDF) digunakan dalam penelitian ini untuk melakukan analisis sentimen ulasan pengguna Livin Mandiri. Penelitian ini menggunakan algoritma TF-IDF untuk mendapatkan pemahaman mendalam tentang sentimen positif atau negatif dan memahami respon pengguna terhadap aplikasi. Proses analisis terdiri dari tahap preprocessing data, yang mencakup pembersihan dan transformasi teks ulasan. Selanjutnya, metode TF-IDF digunakan untuk mengekstraksi kata-kata kunci. Visualisasi sentimen dan WordCloud digunakan untuk mengevaluasi hasil analisis sentimen. Penelitian ini dapat memberikan perspektif yang bermanfaat untuk pengambilan keputusan dan pengembangan layanan di masa depan.
Jurnal Analisis Sentimen Tweet COVID-19 Di Indonesia Menggunakan Metode Algoritma TF-IDF Kusuma Jakti, Sekar Arum; Anna Dina Kalifia
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 7 No. 1 (2024): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v7i1.31222

Abstract

Analisis sentimen terhadap ulasan pengguna Twitter tentang COVID-19 di Indonesia telah menjadi topik penelitian yang penting dalam pemrosesan bahasa alami. Dalam penelitian ini, dataset tweet yang mengandung kata kunci #coronavirus dan #COVID-19 diambil dari Kaggle dan diproses menggunakan metode perhitungan TF-IDF untuk melakukan analisis sentimen. Metode ini melibatkan pengumpulan data dari Twitter, preprocessing dataset, dan analisis sentimen menggunakan algoritma TF-IDF. Hasil penelitian ini memberikan wawasan yang lebih jelas tentang sentimen masyarakat terkait COVID-19 di Indonesia berdasarkan data yang ditemukan di Twitter. Dengan menggunakan algoritma RapidMiner, penelitian ini dapat mengidentifikasi sentimen positif, negatif, atau netral dari tweet yang berkaitan dengan COVID-19 di Indonesia. Hasil analisis ini dapat memberikan informasi berharga bagi pemerintah dan masyarakat untuk memahami pandangan dan perasaan masyarakat terkait pandemi COVID-19. Selain itu, visualisasi WordCloud juga digunakan untuk menangkap esensi dari ulasan pengguna dan mengidentifikasi kata-kata kunci yang sering digunakan dalam ulasan tentang COVID-19 di Indonesia. Dengan demikian, penelitian ini memberikan kontribusi penting dalam memahami reaksi masyarakat dan perasaan mereka terhadap COVID-19 di Indonesia melalui platform Twitter.
Analisis Sentimen Tingkat Entitas di Twitter Menggunakan Metode TF-IDF: Analisis Sentimen Menggunakan Metode TF-IDF Sitio, Cecilyani Saragih; Anna Dina Kalifia
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 7 No. 1 (2024): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v7i1.31223

Abstract

Jurnal ini membahas analisis tingkat sentimen entitas di Twitter dengan menggunakan metode TF-IDF. Analisis sentimen adalah proses untuk mengidentifikasi dan mengklasifikasikan opini atau sentimen yang terkandung dalam teks yang ada di Twitter. Fokus pada tingkat entitas memungkinkan pemahaman yang lebih spesifik terhadap sentimen yang terkait dengan entitas tertentu, seperti orang, tempat, organisasi, produk, atau topik lainnya. Metode yang digunakan dalam jurnal ini adalah TF-IDF (Term Frekuensi-Invers Dokumen Frekuensi). Metode ini digunakan untuk menghitung skor sentimen yang berkaitan dengan entitas yang ada di Twitter. TF-IDF menghitung frekuensi kemunculan kata dalam dokumen tersebut serta frekuensi kemunculan kata tersebut di seluruh korpus. Dengan menggunakan metode ini, penulis jurnal berusaha untuk mengidentifikasi kata-kata kunci yang berkontribusi pada sentimen positif atau negatif terhadap entitas yang sedang dianalisis. Penelitian ini bertujuan untuk memberikan wawasan tentang penggunaan metode TF-IDF dalam analisis sentimen pada tingkat entitas di Twitter. Hasil analisis sentimen dapat memberikan pemahaman yang lebih mendalam mengenai opini dan sentimen pengguna Twitter terhadap entitas-entitas yang mereka bahas. Diharapkan penelitian ini dapat memberikan kontribusi dalam pengembangan analisis sentimen lebih lanjut, terutama dalam konteks media sosial seperti Twitter.
Jurnal ANALISIS EFEKTIFITAS SISTEM PEMBAYARAN SEBELUM DAN SAAT ADANYA QRIS PADA KALANGAN MAHASISWA DI KOTA YOGYAKARTA MENGGUNAKAN UJI MC NEMAR Kusuma Jakti, Sekar Arum; Muhammad Ikhwanul Dzikri; Madanadhindra Che Madanararya Saktiyanto
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 7 No. 1 (2024): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v7i1.31282

Abstract

Penelitian ini membahas tentang penelitian yang dilakukan untuk menyelidiki dampak penggunaan QRIS terhadap kepuasan konsumen, khususnya di kalangan mahasiswa di Kota Yogyakarta. Penelitian ini bertujuan untuk menganalisis efektivitas sistem pembayaran sebelum dan setelah adanya QRIS menggunakan metode uji MC Nemar. Melalui analisis mendalam terhadap faktor-faktor seperti keefektivitasan dan kenyamanan. Penelitian ini bertujuan untuk mengevaluasi efektivitas penggunaan QRIS sebagai sistem pembayaran di kalangan mahasiswa di Kota Yogyakarta. Metode penelitian yang digunakan adalah deskriptif kuantitatif dengan pengumpulan data melalui survei menggunakan kuesioner. Hasil survei menunjukkan bahwa sebagian besar responden merasa nyaman dan efektif menggunakan QRIS sebagai metode pembayaran. Analisis data dilakukan menggunakan uji MC Nemar. Hasil uji statistik McNemar menunjukkan adanya perbedaan yang signifikan dalam efektivitas sistem pembayaran QRIS sebelum dan setelah diterapkannya sistem tersebut. Hal ini menunjukkan bahwa adanya sistem pembayaran QRIS memiliki dampak yang signifikan terhadap efektivitas transaksi pembayaran.
The Evaluasi Usability Aplikasi Goapotik Menggunakan Metode System Usability Scale (SUS) SUBEKTI, REGI MUKLIS; Khaira, Ulfa; Noverina, Yolla
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58813

Abstract

Digital transformation in the healthcare sector has driven the emergence of mobile-based health service applications such as GoApotik, which facilitates the online purchase of medicines and health products. Although it holds a 4.6 rating on the Play Store, several user complaints regarding application responsiveness, order processing by partner stores, lengthy refund times, and address feature errors indicate the need for an in-depth usability evaluation. This study aims to measure the usability level of the GoApotik application and provide a comprehensive overview of the evaluation results using the System Usability Scale (SUS) method. The research employed a quantitative method involving 100 active GoApotik user respondents in Muaro Jambi Regency and Jambi City, selected through nonprobability sampling with a quota sampling approach, using a ten-item SUS questionnaire distributed via Google Form. The results show an average SUS score of 81.875, with a maximum score of 90 and a minimum of 45, categorized as Excellent, grade B+, 83rd percentile, Acceptable, and Promoter on the Net Promoter Score. Among the five usability dimensions, Efficiency, Memorability, and Satisfaction scored high, while Learnability and Errors remained relatively low, particularly among digital immigrant users. It is concluded that GoApotik demonstrates a good level of usability; however, adding interactive tutorial features and expanding respondent coverage in future research are recommended.
Perbandingan Metode Recurrent Neural Network Dan Long Short-Term Memory Dalam Prediksi Indeks Harga Saham Gabungan Riyadi, Marsel Fajriantama; Utomo, Pradita Eko Prastyo; Arsa, Daniel
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58814

Abstract

The movement of the Indeks Harga Saham Gabungan (IHSG) exhibits high volatility influenced by macroeconomic dynamics. This study aims to compare the performance of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) architectures in predicting IHSG closing prices using a multivariate approach integrating the USD to IDR exchange rate and Bank Indonesia (BI) interest rate. Daily historical data from January 2, 2020, to December 31, 2024, were processed through normalization and sequential sliding window formation. Evaluation results indicate that the LSTM model outperformed the RNN. The LSTM model achieved a Mean Absolute Percentage Error (MAPE) of 0.8158% (99.18% accuracy), while the RNN model yielded a MAPE of 0.9314% (99.06% accuracy). Furthermore, the forecasted prices were successfully implemented into a Moving Average Crossover strategy simulation (MA-5 and MA-20) to detect Golden Cross and Death Cross momentums as automated trading signals. In conclusion, the LSTM architecture proved to be more optimal and effective in capturing financial data volatility for IHSG forecasting compared to RNN.
Evaluasi Kepuasan Pengguna Aplikasi Mobile MASTRIS UNJA Menggunakan System Usability Scale (SUS) Fadillah, Muhammad Reno; Aryani, Reni; Muhammad Razi A.
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58823

Abstract

Universitas Jambi (UNJA) launched MASTRIS UNJA, a mobile application that integrates SIAKAD, ELISTA, geolocation-based attendance, and electronic mail services. Following the 2.0.2 update released on 6 May 2026, an evaluation was required to determine whether the update improved user satisfaction, particularly for the SIAKAD and ELISTA features. This study measured usability using the System Usability Scale (SUS) with a sample of 97-100 active students of the Faculty of Science and Technology, determined using the Slovin formula. Data were collected through online and offline questionnaires and analyzed with Microsoft Excel following standard SUS scoring rules. The results show an average SUS score of 75.82, placing the application in Grade B, the “Good” adjective category, the “Acceptable” range, and the “Passive” Net Promoter Score category, with a percentile rank of approximately 74%. Per-indicator analysis shows the highest score on user confidence (item 9, mean 3.32) and the lowest on the need to become familiar with the system before use (item 10, mean 2.74). These findings indicate that the MASTRIS UNJA update has improved usability and is well accepted by users, although the learnability aspect still requires improvement.
Implementation of a Website-Based Student Association Activity Management Information System Using the Prototype Method Hendra, Johanda Putra; aryani, reni; A., muhammad razi
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58860

Abstract

The management of Student Association (HIMA) activity administration at the Faculty of Science and Technology, Universitas Jambi, is still carried out manually, from activity proposal submission, proposal and budget plan (RAB) preparation, to accountability reporting (LPJ), making the process slow, difficult to monitor, and prone to document loss. This study aims to implement the prototype model in building a web-based Student Activity Management Information System (SIPEKMA) and to determine the functional test results of the system using black box testing. The development followed the prototype stages of communication, quick plan, modeling quick design, construction of prototype, and delivery and feedback, with system modeling using Unified Modeling Language (UML) in the form of activity diagrams, class diagrams, and sequence diagrams. The system was built with the Laravel framework and MySQL database and was developed through two iterations based on user feedback. Black box testing of 135 functions across four user roles (48 HIMA functions, 26 Advisor functions, 25 Head of Study Program functions, and 36 Vice Dean III functions) produced X = 100% of functions running well and Y = 0% of functions failing, so the system is considered good in terms of functionality and ready to simplify student activity administration.
Perbandingan Efficientnetv2 Dan Mobilenetv3 Pada Cnn Untuk Klasifikasi Gambar Asli Dan Gambar Ai Sandi, Danish Wiedi Marchello; Utomo, Pradita Eko Prasetyo; Khaira, Ulfa
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58864

Abstract

The rapid advancement of generative artificial intelligence, particularly Generative Adversarial Networks and Diffusion Models, has enabled the creation of synthetic images with a visual quality that is increasingly difficult to distinguish from authentic photographs, raising concerns over misinformation, media manipulation, and digital identity misuse. This study implements a Convolutional Neural Network (CNN) to classify real and AI-generated images and compares the performance of two transfer learning architectures, EfficientNetV2-B0 and MobileNetV3-Large, against a CNN trained from scratch. The dataset consists of 10,930 images collected from two Kaggle repositories, comprising 5,508 AI-generated images and 5,422 real images, which were split into 80% training, 10% validation, and 10% testing data, resized to 224x224 pixels, and augmented prior to training using a batch size of 32, a maximum of 20 epochs, a learning rate of 0.001, and the Adam optimizer. The experimental results show that MobileNetV3-Large achieved the best performance with a training accuracy of 96.84%, a validation accuracy of 96.25%, a testing accuracy of 96.71%, and a testing loss of 0.1031, outperforming EfficientNetV2-B0 (94.41% testing accuracy) and the CNN trained from scratch (91.58% testing accuracy). Hyperparameter experiments further confirm that a batch size of 32 combined with 20 training epochs produces the most stable convergence across all three architectures. The best-performing model was subsequently deployed as a REST API using the Flask framework to support real-time image classification. These findings indicate that transfer learning, particularly with the MobileNetV3-Large architecture, provides an effective and computationally efficient approach for detecting AI-generated images
Evaluasi Usability Website Program Studi Sistem Informasi Universitas Jambi Menggunakan System Usability Scale (Sus) Andreansyah, M. Arif; Suratno, Tri; Willy Bima Alfajri
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58893

Abstract

A study program website is the main channel for delivering academic information and serves as the institution's digital representation, so its usability is essential to ensure effective service delivery. This study aims to evaluate the usability of the Information Systems Study Program website at Universitas Jambi using the System Usability Scale (SUS) method. Data were collected through an online questionnaire distributed to website users, namely students and lecturers, using a purposive sampling technique. Of the 34 questionnaires collected, 32 were declared valid after a data-validity verification process and were used for analysis. The results show that the website obtained an average SUS score of 64.92, placing it in Grade C with an "OK" adjective rating and a Marginal acceptability level. This value is below the commonly cited SUS benchmark of 68, indicating that the website's usability is fair but has not yet reached the acceptable category. Item-level analysis shows that the weakest aspects are learnability, interface consistency, and user independence, while overall ease of use and functional integration were rated favorably. Based on these findings, improvements to the navigation structure, design consistency, and feature accessibility are recommended to enhance the website's usability quality.

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