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All Journal Competitive Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Kimi Thora Refolino
Universitas Logistik dan Bisnis Internasional
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Transportation

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ANALISIS KLASTER RASIO KEUANGAN PT PEGADAIAN DENGAN METODE K-MEANS DAN RANDOM FOREST Kimi Thora Refolino; Woro Istirahayu
Competitive Vol. 21 No. 1 (2026): Jurnal Competitive
Publisher : PPM Universitas Logistik dan Bisnis Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36618/competitive.v21i1.4646

Abstract

Analisis rasio keuangan banyak digunakan untuk menilai kinerja perusahaan, khususnya dari sisi leverage dan profitabilitas. Namun, perubahan pola rasio keuangan dalam jangka panjang sering sulit dilihat secara jelas tanpa bantuan analisis berbasis data. Penelitian ini bertujuan untuk mengelompokkan kinerja keuangan PT Pegadaian periode 2010–2024 dengan menggabungkan metode unsupervised learning dan supervised learning. Analisis dilakukan menggunakan rasio Debt to Asset Ratio (DAR) dan Return on Assets (ROA), yang distandardisasi dengan Z-score, kemudian dikelompokkan menggunakan algoritma K-Means dan diuji kembali menggunakan model Random Forest. Hasil penelitian menunjukkan terbentuknya tiga kelompok kinerja keuangan yang menggambarkan perbedaan kondisi leverage dan profitabilitas antarperiode, dengan nilai silhouette score sebesar 0,5976. Model Random Forest menghasilkan tingkat akurasi sebesar 80 persen, meskipun kinerjanya lebih rendah pada kelompok dengan jumlah data yang terbatas. Penelitian ini menunjukkan bahwa kombinasi DAR dan ROA dapat digunakan tidak hanya untuk menilai kinerja keuangan, tetapi juga untuk mengelompokkan dan memahami pola perubahan kinerja perusahaan dalam jangka panjang dengan bantuan metode pembelajaran mesin.
Analisis dan Perbandingan Sentimen Lirik Lagu pada Album Logic Mess dan Life Update Karya Arash Buana Menggunakan NRC Emotion Lexicon Kimi Thora Refolino; James Aldo Parlindungan; Woro Isti Rahayu
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 3 (2026): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i3.1908

Abstract

Song lyrics are a form of textual data that can be analyzed using Natural Language Processing (NLP) to identify the emotional patterns contained within them. This study aims to analyze and compare the emotional distribution in the lyrics of Arash Buana’s albums Logic Mess and Life Update using the NRC Emotion Lexicon. The dataset consists of lyrics from 20 songs, including 10 songs from Logic Mess and 10 songs from Life Update. Data were collected through a web scraping technique and processed using several preprocessing stages, including case folding, tokenization, and stopword removal. Emotion analysis was conducted by matching the resulting tokens with emotion categories in the NRC Emotion Lexicon. The results indicate that Logic Mess is dominated by negative emotion (18.49%), followed by sadness (12.22%), anger (10.77%), and fear (10.61%), reflecting a more reflective and melancholic emotional character. In contrast, Life Update is dominated by positive emotion (17.91%), followed by joy (11.23%), sadness (11.23%), and anticipation (11.08%), indicating a more optimistic emotional tendency. Comparative analysis reveals an increase in positive emotions and a decrease in negative emotions in Life Update. These findings demonstrate that the NRC Emotion Lexicon-based NLP approach can systematically and effectively identify and compare emotional characteristics in song lyrics. Despite limitations in interpreting contextual nuances, metaphors, and irony, the NRC Emotion Lexicon enables systematic emotion mapping and contributes to computational musicology and psychological studies of creative works.
Co-Authors James Aldo Parlindungan Rahayu, Woro Isti Woro Istirahayu