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All Journal Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Data : Journal of Information Systems and Management
Hamidan, Rusdi
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Computer Science & IT Decision Sciences, Operations Research & Management

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UX Analysis of the Virtual Tour 360 Application at Universitas Dr. Soetomo Campus Choiron, Achmad; Hamidan, Rusdi
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8813

Abstract

This research investigates the effectiveness of the Virtual Tour 360 application implemented at Universitas Dr. Soetomo Campus, Surabaya, as a tool for enhancing prospective students' understanding and familiarity with campus facilities. Focusing on user experience (UX), this study evaluates key aspects such as the flow of the virtual tour, camera height for indoor and outdoor captures, image resolution and file size, and overall application size for online accessibility. User feedback highlights a high level of satisfaction, with 85.1% finding the application beneficial, especially on mobile devices, the preferred access method. The immersive 360-degree campus visualizations and user-friendly navigation have received positive responses, effectively providing a favorable first impression of the university. To further enrich user experience, optimizing mobile display quality and enhancing navigation features are recommended to offer a more comprehensive and interactive campus introduction.
SISTEM INFORMASI EVALUASI DOSEN OLEH MAHASISWA (EDOM) BERBASIS WEB UNTUK MENINGKATKAN TRANSPARANSI PENILAIAN DOSEN DI PERGURUAN TINGGI Fauzi, Chamda; Hamidan, Rusdi; Kacung, Slamet
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.12985

Abstract

Salah satu cara penting untuk menilai kualitas pengajaran di perguruan tinggi adalah evaluasi dosen oleh mahasiswa (EDOM). Namun, banyak perguruan tinggi masih menggunakan metode manual untuk melakukan evaluasi ini, yang dapat mengurangi transparansi dan akuntabilitas penilaian dosen. Akibatnya, pengembangan sistem informasi berbasis web untuk EDOM dapat membantu mahasiswa menilai dosen dengan lebih efektif, lebih transparan, dan lebih valid. Tujuan dari penelitian ini untuk menerapkan sistem informasi EDOM berbasis web yang dapat membuat penilaian dosen lebih jelas. Dalam studi ini, metode pengembangan sistem menggunakan pendekatan berbasis waterfall. Antarmuka pengguna yang dirancang dengan baik membuatnya mudah dipahami dan mudah digunakan. Metode deskriptif kuantitatif digunakan untuk menganalisis data untuk mengetahui tingkat kepuasan dan transparansi penilaian. Hasil penelitian menunjukkan bahwa fitur sistem evaluasi EDOM berbasis web berhasil meningkatkan transparansi penilaian dosen, rata-rata mahasiswa menyatakan bahwa mereka puas dengan feedback yang baik terhadap dosen. Selain itu, umpan balik yang lebih jelas dan terstruktur tentang kualitas pengajaran yang diberikan oleh dosen dapat digunakan untuk perbaikan di masa depan. Dengan penerapan sistem EDOM berbasis web, proses evaluasi menjadi lebih transparan dan tidak bias. Sistem ini memberi perguruan tinggi kemampuan untuk memantau dan memastikan bahwa penilaian dosen dilakukan dengan adil dan sesuai dengan peraturan. Studi ini merekomendasikan pengembangan lebih lanjut tentang elemen keamanan data dan integrasi sistem dengan platform akademik lainnya.
SISTEM INFORMASI PERSEDIAAN STOK BERDASARKAN TURNOVER RATIO Muzaki, Mochammad Rizki; Vitianingsih, Anik Vega; Hamidan, Rusdi; Maukar, Anastasia Lidya; Wati, Seftin Fitri Ana
Journal of Information System Management (JOISM) Vol. 7 No. 1 (2025): Juni
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2025v7i1.2120

Abstract

Penelitian ini mengembangkan sistem informasi persediaan stok berdasarkan rasio perputaran (turnover ratio) untuk mengatasi pencatatan manual dan analisis intuitif yang tidak valid. Sistem dibangun menggunakan metode SDLC dan diuji dengan pendekatan black box testing dan uji penerimaan menggunakan system usability scale (SUS). Hasil pengujian menunjukkan bahwa 87% pengguna menyatakan proses input data berjalan lancar dan sesuai alur kerja. Fitur klasifikasi berdasarkan turnover ratio yaitu non-moving, slow-moving dan fast-moving sangat membantu dalam pengambilan keputusan logistik. Hasil penelitian menunjukkan nilai rata-rata skor SUS yaitu 75,33 dengan kategori “Good”. Sistem yang dibangun dalam penelitian ini mampu mendukung operasional gudang secara efektif dalam meningkatkan efisiensi pengelolaan stok, integrasi pemesanan dengan supplier, serta transparansi aktivitas melalui log sistem otomatis yang mengacu pada visualisasi dashboard dan fitur CRUD yang lengkap.
Comparative Analysis of Deep Learning Methods for Predicting the Value of the Standard & Poor's Global Supply Chain Intelligence (S&P GSCI) Nickel Stock Index Rahmansyah, Ragada; Vitianingsih, Anik Vega; Hamidan, Rusdi; Lidya Maukar, Anastasia; Budi Suprio, Yoyon Arie
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.36129

Abstract

The development of information technology has opened up new opportunities in stock market forecasting, especially in nickel commodities, which are increasingly strategic in the global energy transition. This study uses a Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and a Gated Recurrent Unit (GRU) to forecast the movement of the S&P GSCI Nickel stock index value. Yahoo Finance time series data for the years 2018–2024 are used in the dataset. The study's findings are used to evaluate each model's capacity to forecast changes in nickel stock prices. The RNN model is used in this study because it can work with sequential information, while LSTM works with three memory gates (input, forget, output), and GRU works with 2 gates, namely update and reset. Mean Absolute Percentage Error (MAPE) presents the results of open and closed variable forecasting errors with the lowest average for the RNN model of 2.08%, the LSTM model of 2.505%, and the GRU model of 1.505%. This study is expected to contribute to investor decision-making and the identification of the most accurate forecasting model for the nickel stock index
Sentiment Analysis of BCA Mobile App Reviews Using K-Nearest Neighbour and Support Vector Machine Algorithm Zandroto, Yosefin Yuniati; Vitianingsih, Anik Vega; Maukar, Anastasia Lidya; Hikmawati, Nina Kurnia; Hamidan, Rusdi
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.37773

Abstract

The rapid evolution of digital technology has significantly transformed the financial services landscape, especially in the realm of mobile banking. BCA Mobile stands among the most popular apps for digital banking in Indonesia. Despite its widespread adoption, user reviews reflect diverse viewpoints and sentiments about the app. The objective of this research is to examine the user sentiments regarding the BCA Mobile app, based on reviews sourced from the Google Play Store and App Store. Two classification models, namely Support Vector Machine (SVM) and K-Nearest Neighbour (K-NN), are used in the analysis process. The collected review data undergoes several pre-processing stages and is labeled automatically using a Lexicon-Based technique. For feature weighting, the TF-IDF (Term Frequency-Inverse Document Frequency) approach is used.. Sentiment classification is then carried out using both K-NN and SVM, with performance evaluated through a matrix of confusion based on measurements like F1-score, recall, accuracy, and precision.  The findings show that the SVM algorithm outperforms K-NN in terms of performance, with an accuracy of 94%, while K-NN achieves an accuracy of 82%. This study offers valuable insights for BCA management in understanding user sentiment and enhancing service quality through the application of artificial intelligence
Digital Capabilities and IT Governance as Drivers of Firm Performance: A Multilevel Study in Emerging Markets Hamidan, Rusdi; Sitorus, Anwar T; Sucipto, Purwo Agus
Data : Journal of Information Systems and Management Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i2.1088

Abstract

This study explores the role of Strategic IT Planning (SITP) in fostering Sustainable Competitive Advantage (SCA) among firms operating in emerging economies. With the rapid pace of digital transformation reshaping global competition, aligning IT strategy with business goals has become critical. Drawing on a combination of primary and secondary datasets, the research examines the impact of SITP maturity on firm performance, the mediating influence of digital capabilities, and the moderating role of national digital readiness. The methodology includes firm level survey data integrated with national indicators across multiple emerging markets. Hierarchical Linear Modeling (HLM) is employed to analyze multi level panel data, capturing the nested relationships between organizational practices and country level digital infrastructure. The study applies Structural Equation Modeling (SEM) to validate the effects of SITP on SCA through digital capabilities. Results indicate that higher levels of SITP maturity significantly correlate with improved firm performance and long term competitive positioning. Digital capabilities such as ERP, CRM, and analytics mediate this relationship by enhancing business alignment and operational coherence. Furthermore, the National Readiness Index (NRI) and digital infrastructure metrics moderate the effectiveness of SITP, with distinct cutoff points observed across countries. The findings underscore the importance of aligning internal IT governance structures with external digital environments. Policymakers are encouraged to support firms through investments in infrastructure, cybersecurity, and workforce development. Meanwhile, firms are advised to adopt flexible, data driven strategic planning practices.
Co-Authors Achmad Choiron Anastasia Lidya Maukar Anik Vega Vitianingsih Budi Suprio, Yoyon Arie Fauzi, Chamda Hikmawati, Nina Kurnia Lidya Maukar, Anastasia Muzaki, Mochammad Rizki Rahmansyah, Ragada Sitorus, Anwar T Slamet . Sucipto, Purwo Agus Wati, Seftin Fitri Ana Zandroto, Yosefin Yuniati