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All Journal Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Jejak digital: Jurnal Ilmiah Multidisiplin
Sriyanti, Rini
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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PENALARAN DEDUKTIF, INDUKTIF DAN BAHASA DALAM PENULISAN ILMIAH Sriyanti, Rini; Hidayat, Nandang; Marlia, Rina
Jurnal Review Pendidikan dan Pengajaran Vol. 7 No. 4 (2024): Special Issue Vol. 7 No. 4 Tahun 2024
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v7i4.38312

Abstract

Penulisan ilmiah membutuhkan kerangka berpikir logis dan sistematis untuk menghasilkan karya yang berkualitas. Penalaran deduktif dan induktif merupakan metode utama yang mendasari pengembangan argumen dalam penulisan ilmiah. Penalaran deduktif digunakan untuk menarik kesimpulan spesifik dari prinsip umum, sedangkan penalaran induktif memungkinkan penulis membangun generalisasi berdasarkan pengamatan atau data spesifik. Selain itu, bahasa memainkan peran strategis dalam menyampaikan argumen agar dapat dipahami oleh pembaca dengan latar belakang yang beragam. Penelitian ini menggunakan metode library research untuk menganalisis teori-teori terkait hubungan antara penalaran deduktif, induktif, dan peran bahasa dalam penulisan ilmiah. Hasil penelitian menunjukkan bahwa sinergi antara ketiga elemen tersebut dapat memperkuat validitas logis, keberterimaan ilmiah, dan efektivitas komunikasi dalam tulisan ilmiah.
Sinergi Kebijakan Hybrid Learning dan Artificial Intelligence dalam Membangun Ekosistem Literasi Digital Mariko, Selli; Sriyanti, Rini; Suhendra, Suhendra
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 10, No 1 (2026): SEMNAS RISTEK 2026
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v10i1.8866

Abstract

Systematic Literature Review Penerapan Algoritma Apriori dalam Data Mining untuk Optimasi Stok Barang Haqi, Bay; Sriyanti, Rini
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 2 (2026): MARET 2026
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/kme6bq63

Abstract

This study aims to examine the application of the Apriori algorithm in data mining for inventory stock optimization using a systematic literature review approach. Effective inventory management is essential for improving operational efficiency and service quality within organizations. The research method involves collecting and analyzing relevant academic articles from scientific databases, which are selected based on predefined inclusion and exclusion criteria. The results indicate that the Apriori algorithm is effective in identifying association patterns among products using transaction data. The generated information supports inventory planning, reduces the risk of overstock and stockouts, and improves overall inventory efficiency. However, several studies highlight the computational complexity of the Apriori algorithm when applied to large datasets. Therefore, future research is recommended to develop hybrid approaches and integrate big data technologies. Overall, this literature review provides a comprehensive overview of research trends and the potential application of the Apriori algorithm in data mining-based inventory management.
Co-Authors Ariwibowo, M Lukman Arrafi, Fulki Butar-Butar, Forkas Tiroy Santos Haqi, Bay Harun Al Rasyid Hidayat, Nandang marlia, rina Purba, Samuel Martohap Putri Dina Mardika Rahman, Muhammad Ichsan Rahnita Nuzulah RAIS HIDAYAT, RAIS Renaldy, Alvian Rismawati, Nofita Selli Mariko Suhendra Suhendra Taliak, Hendrik Wellem Vivi Oktaviani