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Pengoptimalan Teknik White Hat SEO Pada Website Startupreneur Menggunakan Metode IMF Irwansya, Irwansya; Nurninawati, Euis; Imammuddin, Muh. Rukhi
Jurnal Ilmiah Komputasi Vol. 24 No. 1 (2025): Jurnal Ilmiah Komputasi : Vol. 24 No 1, Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.24.1.3771

Abstract

Di era digitalisasi, penggunaan mesin pencari untuk mencari informasi di internet meningkat pesat. Hal ini disebabkan oleh berbagai mesin pencari yang tersedia untuk pengguna internet di seluruh dunia. Apabila website Startupreneur tidak menerapkan SEO (Search Engine Optimization), mesin pencari kesulitan untuk mengenali dan menemukannya di internet. Penelitian bertujuan untuk meningkatkan posisi website Startupreneur dalam hasil pencarian Google dan jumlah pengunjung melalui mesin pencari Google dengan menerapkan strategi SEO secara sistematis dan sesuai syarat dan ketentuan mesin pencari. Metode SEO White Hat digunakan meningkatkan hasil pencarian dan posisi situs web Startupreneur. Hasil penelitian menunjukkan bahwa penerapan teknik SEO pada website Startupreneur berhasil mendapatkan posisi pertama dalam hasil pencarian dan meningkatkan trafik pengunjung secara konsisten. Selain itu, penelitian juga melibatkan Tingkat Kesiapan Teknologi (TKT) dalam dua skala, yaitu tahun 1 dan tahun 2. Output Tahun 1 meliputi Jurnal Internasional terindeks bereputasi sebagai output wajib dan Publikasi Ilmiah Jurnal Nasional sebagai output tambahan.
Development of Artificial Intelligence (AI)-Based Digital Evaluation Applications to Improve Quality of Feedback for PGSD Students’ Formative Juryatina, Juryatina; Imammuddin, Muh. Rukhi; Nasir, Muh.; Azmin, Nikman; Ekahidayatullah, M.; Agustiarrahman, Agustiarrahman
JISIP: Jurnal Ilmu Sosial dan Pendidikan Vol 9, No 4 (2025): JISIP (Jurnal Ilmu Sosial dan Pendidikan) (November)
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/jisip.v9i4.9526

Abstract

The objective of this study was the development and implementation of an artificial intelligence (AI)–based digital assessment application to improve the quality of formative feedback for students of the Primary School Teacher Education (PGSD) Program at Nggusuwaru University. The study employed a Research and Development (R&D) approach using the ADDIE model, which included needs analysis, design, development, limited implementation, and evaluation. Expert validation placed the application in the “valid” category (mean score 3.31), while practicality testing by lecturers and students produced a mean score of 3.20 (“practical”). Pretest–posttest effectiveness testing in two classes (n = 40) showed a significant improvement in learning outcomes (increase of 6–7 points; p < 0.05). The quality of formative feedback was also rated positively by students, with an average response time of 4–5 seconds and perception scores above 3.2. System log analysis during two weeks of implementation recorded an average session duration of 9–10 minutes, page load times of under 3 seconds, an error rate reduction from 4.5% to 3.8%, and uptime over 98%, indicating good system stability. Qualitative findings supported the quantitative results, showing that the application accelerated formative feedback but still required refinement of feedback language and performance optimization under low-network conditions. These findings indicate that the AI-based digital assessment application is feasible for supporting formative evaluation of PGSD students and has the potential for wider implementation in higher education.