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Vina Ayumi
Fakultas Teknik dan Informatika, Universitas Dian Nusantara, Indonesia
Computer Science & IT

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Transformasi Human Capital pada Penerapan Knowledge Sharing System Berdasarkan Shared Language dan Social Interaction di Perguruan Tinggi Vina Ayumi
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7911

Abstract

Penelitian ini bertujuan untuk menganalisis bagaimana transformasi human capital mahasiswa dapat mendukung penerapan KSS dengan mempertimbangkan shared language dan social interaction sebagai faktor utama dalam knowledge sharing. Metode penelitian yang digunakan adalah survei daring dengan 420 responden mahasiswa dari berbagai perguruan tinggi di Indonesia. Data dianalisis menggunakan pendekatan Partial Least Squares Structural Equation Modeling (PLS-SEM) untuk mengukur hubungan antara variabel penelitian. Hasil penelitian menunjukkan bahwa shared language dan social interaction berpengaruh signifikan terhadap tacit dan explicit knowledge sharing, yang pada akhirnya berdampak pada human capital mahasiswa. Hasil penelitian ini memberikan rekomendasi tentang komponen tacit knowledge sharing memiliki kontribusi lebih besar dalam meningkatkan human capital dibandingkan explicit knowledge sharing. Dari hasil penelitan, faktor shared language dan social interaction memainkan peran penting dalam memperkuat knowledge sharing system di perguruan tinggi. Implikasi dari penelitian ini dapat digunakan sebagai dasar dalam perancangan strategi untuk meningkatkan pengelolaan dan transfer pengetahuan di lingkungan pendidikan tinggi.
Pengembangan Cash Management System (CMS) Berbasis Web Berbasis Cash Processing Center (CPC) di PT. XYZ Andriana Suhendi; Vina Ayumi
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8612

Abstract

This research aims to develop a web-based financial management system to optimize cash management at PT. XYZ. The background of this research is based on the importance of utilizing technology to support the operations of cash management service companies, such as PT. XYZ, which handles Cash In Transit (CIT) and Cash Management. With the rapid advancement of technology, an application is needed that can simplify cash management processes, improve efficiency, and reduce the risk of errors in recording daily transactions. The research methodology used is qualitative, involving active participation, observation, interviews, and documentation. The researcher directly participated in the application development process with the CPC division for 3 months, observing workflows and system requirements, and discussing with employees and company management. Interviews were conducted to understand managerial needs, while observations focused on monitoring existing cash management operations as the basis for developing a new system. The research results show that the development of the web-based financial management system successfully optimized the recording of cash inflows and outflows, facilitated customer data management, and ensured operational efficiency.
Pengembangan Aplikasi Website untuk Manajemen Bahan Pergudangan Berbasis Web Rivky Kurniatama; Vina Ayumi
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8613

Abstract

Efficient warehouse management is a critical factor in maintaining smooth business operations. However, many companies still use manual methods that are prone to errors and time-consuming. This research aims to design and implement a web-based warehouse management system application that simplifies stock management, records transactions of goods entering and leaving the warehouse, and provides real-time reporting. The research adapts the waterfall method, which includes requirements analysis, system design, implementation, deployment, and testing. This study analyzes the warehouse management issues at Sari Rasa Group as a case study. The application is developed using PHP programming language and MySQL database, with a responsive interface for easy access across various devices. Based on the analysis, the use case diagram in this system includes one actor, the admin. The admin can perform activities such as logging in, managing product data, managing request data, managing goods expenditure data, managing goods input data, and creating daily and monthly summaries. The warehouse management website application will be developed with six classes: user, product data, stock input, output data, stock output, and reports. The test results show that the application can assist in the process of recording goods in and out, enabling warehouse management to minimize user errors.
Analisis Sentimen Terhadap Kompetensi Pedagogi Dosen Menggunakan Word Embedding dan Random Forest pada Data Umpan Balik Mahasiswa Vina Ayumi; Mariana Purba; Abd Rahman
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8761

Abstract

Perkembangan teknologi dan media digital telah mendorong cara evaluasi kinerja dosen yang tidak hanya berbasis kuantitatif, tetapi juga didukung oleh analisis data kualitatif. Salah satu pendekatan yang efektif adalah analisis sentimen terhadap umpan balik mahasiswa terkait informasi berharga mengenai persepsi dan pengalaman terkait kompetensi pedagogi dosen. Penelitian ini mengolah dataset sentimen umpan balik mahasiswa di Universitas Sjakhyakirti dengan menggunakan metode word embedding (WE) dan random forest (RF) untuk mengklasifikasikan sentimen positif dan negatif. Dataset yang digunakan berjumlah 6.164 data kuesioner, terdiri dari 3.800 data sentimen positif dan 2.364 data sentimen negatif. Data kemudian dibagi menjadi data pelatihan (70%), validasi (10%), dan pengujian (20%). Evaluasi kinerja model pada data pengujian menunjukkan bahwa model WE-RF mampu mengklasifikasikan sentimen dengan tingkat presisi, recall, dan F1-score masing-masing sebesar 0,805; 0,724; dan 0,762 untuk kelas positif, serta 0,618; 0,719; dan 0,664 untuk kelas negatif. Akurasi pada tahap pengujian yang diperoleh mencapai 72,2% yang menujukkan bahwa model ini cukup efektif untuk menganalisis sentimen dalam konteks kompetensi pedagogi dosen.
Co-Authors Abd Rahman Andriana Suhendi Mariana Purba Rivky Kurniatama