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All Journal Jurnal Rekayasa Sistem Industri Journal of Engineering and Management in Industrial System JKIE (Journal Knowledge Industrial Engineering) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Journal La Sociale Visioner: Jurnal Pemerintahan Daerah di Indonesia Civil Engineering Scientific Journal CYBER-Techn(Jurnal Informatika dan Industri) Humanist Journal Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Muhammad Hermansyah
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Other

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PEMODELAN DATA RADIOSONDE MENGGUNAKAN STACKING ENSEMBLE UNTUK KLASIFIKASI HUJAN Hermansyah, Muhammad; Saikhu, Ahmad; Amaliah, Bilqis
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.7806

Abstract

Perubahan iklim telah meningkatkan frekuensi dan intensitas kejadian cuaca ekstrem di wilayah tropis seperti Indonesia, sehingga men-imbulkan tantangan dalam pemanfaatan data observasi meteorologi untuk mitigasi bencana hidrometeorologis. Data observasi permukaan sering kali kurang mampu merepresentasikan dinamika vertikal at-mosfer dalam analisis kejadian cuaca ekstrem, seperti hujan sedang hingga lebat. Penelitian ini bertujuan mengembangkan model klasifikasi intensitas hujan berbasis data observasi udara atas dari radiosonde dengan pendekatan stacking ensemble, yang mengintegrasikan algorit-ma Random Forest, XGBoost, LightGBM, dan SVM, serta menggunakan HistGradientBoosting sebagai meta-learner. Untuk mengatasi ketidakseimbangan kelas antara kondisi berawan-hujan ringan dan hujan sedang-lebat, diterapkan teknik Synthetic Minority Over-sampling Technique (SMOTE). Evaluasi performa dilakukan menggunakan metrik precision, recall, F1-score, dan kurva precision-recall. Hasil menunjukkan bahwa model stacking ensemble memberikan performa terbaik dengan nilai precision sebesar 0,9084, F1-score 0,8718, dan average precision untuk kelas hujan sedang-lebat sebesar 0,949, melampaui seluruh model individual. Temuan ini menegaskan keunggulan integrasi data atmosfer vertikal dan pendekatan multi-algorithm machine learning dalam mendeteksi hujan intensitas sedang hingga lebat secara lebih akurat. Model ini memiliki potensi tinggi untuk diimplementasikan dalam sistem peringatan dini cuaca ekstrem, khususnya di wilayah tropis dengan keterbatasan data observasi permukaan.
PENGARUH MARKETING MIX TERHADAP KEPUTUSAN PEMBELIAN PRODUK KASUR PADA PT. RIP Hermansyah, Muhammad
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 2 No. 2 (2022): Juli: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v2i2.572

Abstract

The purpose of this study is to examine the impact of seven elements of marketing mix (product, price, place, promotion, people, process and physical evidence) on customer satisfaction of mattress. Data were collected from 100 customers residing in South Jakarta using self-reporting questionnaires. Factor analysis is used to validate the instrument and regression analysis was used to test the hypotheses. The results of research on the marketing mix strategy applied at PT. RIP Suwayuwo. Research results from consumer responses can it is known that the product aspect with an average of 3.34 is in the very good category. Aspect price with an average of 3.13 in the good category. Aspects of place with an average of 3.21 in good category. The promotion aspect with an average of 2.48 in the poor category. The people aspect with an average of 3.45 is in the very good category. Process aspects with an average of 3.32 in the very good category. Physical evidence aspects with averages 3.13 in good category.
Co-Authors Achmad Misbah Ahmad Saikhu Arif Budi Sulistyo Arif Widiantoro Aryashta, Danurahni Ayik Pusaka Ningwati Bilqis Amaliah Dalih Iskandar Djaya, Subhan Edy Utomo Eko, Andi Gede Yamuna Ceswaraningrat, Ida Bagus Ghozali, M. Wildan Hasan Bashori Hasibuan, Masnilam Imran, Treesje Kahtijah, Siti kasid, Kasid Kusaeri, Ach. M. Imron Mas'ud M. Imron Mas’ud M. Imron Mas’ud Mansyur Djamal Muhammad Afandi Nasir Widha Setyanto Pratikto Pratikto Rini, Detya Nurfajar Rudy Soenoko Siti Nurhayati Situmorang, Marningot Tua Natalis Titin Astuti, Titin