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All Journal INTECOMS: Journal of Information Technology and Computer Science Jurnal Manuhara: Pusat Penelitian Ilmu Manajemen Dan Bisnis
Azzumardi Mubarok Romadhoni
Universitas Muhammadiyah Gresik
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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PENERAPAN ALGORITMA RANDOM FOREST SEBAGAI EARLY WARNING SYSTEM PREDIKSI KELULUSAN MAHASISWA TEPAT WAKTU Azzumardi Mubarok Romadhoni; Widyasari Puspa Permata Witra; Indra Gita Anugrah
INTECOMS: Journal of Information Technology and Computer Science Vol. 9 No. 3 (2026): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/kqm1n834

Abstract

Ketepatan waktu kelulusan merupakan indikator penting dalam evaluasi kinerja perguruan tinggi. Rendahnya tingkat kelulusan tepat waktu pada Fakultas Teknik di salah satu universitas di Gresik mendorong pengembangan mekanisme prediksi dini untuk mengidentifikasi mahasiswa berisiko terlambat lulus. Penelitian ini membangun model Early Warning System (EWS) menggunakan algoritma Random Forest berdasarkan data akademik 1.558 mahasiswa angkatan 2018 - 2021. Variabel yang digunakan meliputi IPS semester 1 - 4, IPK semester 4, dan status pekerjaan. Pengujian dilakukan dengan kombinasi K-Fold Cross Validation (5 dan 10) serta pembagian data 70:30, 80:20, dan 90:10. Model terbaik diperoleh pada skenario cv5_split70 dengan parameter n_estimators=50 dan max_depth=5, menghasilkan akurasi 77,56% dan F1-Score 0,7764. IPS semester 4 menjadi prediktor paling dominan. Hasil penelitian menunjukkan Random Forest efektif digunakan sebagai dasar pengembangan EWS untuk mendukung intervensi akademik yang lebih tepat sasaran. Kata Kunci: Early Warning System, Random Forest, Prediksi Kelulusan, Kinerja pendidikan tinggi,
Pemanfaatan Visualisasi Data dalam Business Intelligence untuk Strategi Bisnis Perusahaan Retail Sasha Safira Nuraini; Azzumardi Mubarok Romadhoni; Muhammad Akmal Faris Taqiyuddin; Ma’had Wicaksono
Jurnal Manuhara : Pusat Penelitian Ilmu Manajemen dan Bisnis Vol. 3 No. 3 (2025): Juli : Jurnal Manuhara : Pusat Penelitian Ilmu Manajemen dan Bisnis
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/manuhara.v3i3.1992

Abstract

This study investigates how data visualization helps retail companies make Business Intelligence (BI)-based decisions. The study processed one year of sales data with a quantitative descriptive approach to find seasonal patterns, performance by region, and customer consumption tendencies. The analysis results show that BI software such as Microsoft Power BI can visualize data more easily and accelerate understanding of business performance. Strategic decisions such as promotional planning and product inventory management are more effective with interactive visualization, which allows decision makers to see data in a more understandable way. The study found that data visualization in BI systems can help retail businesses make better decisions. These results show the importance of incorporating BI into a company's operational processes and using interactive visualization to improve overall business performance.
Co-Authors Indra Gita Anugrah Ma’had Wicaksono Muhammad Akmal Faris Taqiyuddin Sasha Safira Nuraini Widyasari Puspa Permata Witra