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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Indonesian Journal of Multidisciplinary on Social and Technology
Dwi Ismiyana Putri
Universitas Bina Insani
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Social Sciences

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Comparison of Latent Semantic Analysis (LSA) and Doc2Vec Algorithms of Thesis Similarity Detection Rita Wahyuni Arifin; Mardi Yudhi Putra; Dwi Ismiyana Putri
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9954

Abstract

This study aims to develop a system for detecting similarities in thesis titles and content to prevent plagiarism and support student originality. The high level of similarity in final projects is a significant concern in academic environments. Two text vectorization methods, Latent Semantic Analysis (LSA) and Doc2Vec, were compared to measure document similarity. Results showed that LSA achieved a very high cosine similarity (99.94%) due to dimensionality reduction that preserved semantic correlations. In contrast, Doc2Vec produced lower similarity scores, with 7.17% for PV-DM and 39.07% for PV-DBOW, indicating richer text representations. This study adopted the CRISP-DM model, which includes Business Understanding, Data Understanding, Data Preparation, Modelling, and Evaluation. The model is expected to strengthen academic integrity and encourage valuable scientific contributions.
Analysis of Information Systems Acceptance and Success Models in Higher Education Reni Haerani; Titik Khawa Abdul Rahman; Dwi Ismiyana Putri; Rika Apriani; Mardi Yudhi Putra
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 10 No 1 (2026)
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v10i1.24969

Abstract

Background: The integration of Information Systems (IS) in higher education has transformed interactions among students, lecturers, and administrative staff, making system acceptance and success essential for effective academic processes. Various evaluation frameworks have been developed, with the DeLone and McLean Information System Success Model being one of the most widely applied. Objective: This study aims to analyze factors influencing the adoption of academic information systems in higher education using the DeLone and McLean model and to evaluate system success from the perspectives of lecturers, students, and administrative personnel. Methods: A quantitative research approach was employed using questionnaire-based data collection. Data analysis was conducted using SmartPLS 3.0 to assess validity, reliability, and structural relationships among variables. A total of 252 respondents were selected using the Slovin formula and proportional stratified random sampling. The evaluated constructs included system quality, information quality, service quality, system use, user satisfaction, and benefits. Results: The results show that system quality, information quality, and service quality have a positive and significant effect on system use and user satisfaction. Furthermore, system use and user satisfaction contribute to perceived net benefits, such as improved learning outcomes, increased management efficiency, and academic productivity. High service quality also supports continued system usage. All measurement constructs met validity and reliability criteria, with loading factors above 0.7 and Average Variance Extracted (AVE) values exceeding 0.50. Conclusion: In conclusion, the DeLone and McLean model effectively explains academic information system success in higher education, highlighting the importance of system quality, user satisfaction, and generated benefits.
Sistem Pakar Diagnosis Hama dan Penyakit Tanaman Padi Menggunakan Metode Teorema Bayes Dwi Ismiyana Putri; Rini Sukma Ayu
Indonesian Journal of Multidisciplinary on Social and Technology Vol. 4 No. 3 (2026): Juli - Oktober
Publisher : PT Ilmu Data Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/ijmst.v4i3.12300

Abstract

Tanaman padi merupakan komoditas pangan utama di Indonesia, namun produksi padi dipengaruhi oleh serangan Organisme Pengganggu Tumbuhan (OPT) atau disebut juga Hama dan Penyakit Tanaman (HPT) padi. Di BPP Kecamatan Cibarusah, keterbatasan jumlah Pengendali Organisme Pengganggu Tumbuhan (POPT) serta kesulitan petani dalam mengenali gejala awal serangan OPT menyebabkan proses diagnosis belum dapat dilakukan secara cepat, penelitian ini bertujuan mengembangkan sistem pakar diagnosis hama dan penyakit tanaman padi berbasis website menggunakan metode teorema bayes untuk membantu diagnosis awal berdasarkan gejala yang dipilih, pengembangan sistem dilakukan menggunakan metode Rapid Application Development (RAD), sedangkan basis pengetahuan diperoleh melalui Observasi, Wawancara dengan POPT Kecamatan Cibarusah dan POPT Penyelia BBPOPT, serta studi literatur. Sistem mengimplementasikan metode teorema bayes dengan nilai bobot yang ditentukan berdasarkan expert judgement untuk menghitung probabilitas setiap jenis OPT. Hasil penelitian menghasilkan sistem pakar yang mampu mendiagnosis lima jenis OPT berdasarkan 22 gejala serta memberikan rekomendasi penanganan sesuai hasil diagnosis. Validasi dilakukan dengan membandingkan hasil diagnosis sistem terhadap diagnosis pakar menggunakan 30 kasus oleh POPT Kecamatan Cibarusah dan 31 kasus oleh POPT Penyelia BBPOPT. Seluruh hasil diagnosis sistem sesuai dengan hasil diagnosis pakar sehingga diperoleh tingkat kesesuian sebesar 100%. Hasil tersebut menunjukan bahwa sistem pakar yang dikembangkan mampu memberikan diagnosis yang konsisten dengan pengetahuan pakar dan layak digunakan sebagai alat bantu konsultasi OPT tanaman padi untuk memperoleh diagnosis awal.
Co-Authors Reni Haerani Rika Apriani Rini Sukma Ayu Rita Wahyuni Arifin Titik Khawa Abdul Rahman