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INDONESIA
Indonesian Journal of Business Intelligence (IJUBI)
Published by Universitas Alma Ata Yogyakarta
ISSN : 26213915     EISSN : 26213923     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Fokus jurnal adalah karya inovatif pada analisis, desain, pengembangan, implementasi, evaluasi program, proyek, dan produk sistem informasi dalam manajemen strategis dan intelijen bisnis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 209 Documents
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PREDIKSI KEBERHASILAN TRANSFORMASI DIGITAL PADA UKM Atika Mutiarachim
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 1 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i1.5679

Abstract

Industri 4.0 menuntut pelaku industri skala besar sampai kecil untuk mampu beradaptasi dengan percepatan teknologi. Transformasi digital terbukti berdampak signifikan terhadap kinerja industri, termasuk mempertahankan eksistensi UKM. Keberhasilan UKM dalam memanfaatkan teknologi terbukti mampu meningkatkan keuntungan dan efisiensi operasional. Pelaku UKM harus memastikan transformasi digital berhasil diterapkan. Prediksi transformasi digital memudahkan pelaku UKM untuk mengetahui tingkat keberhasilan usahanya dalam menerapkan transformasi digital, sehingga UKM dapat mengembangkan strategi inovasi mengoptimalkan teknologi digital untuk menjaga eksistensi, memperoleh keuntungan optimal, meningkatkan daya saing serta efisiensi operasional. Prediksi dilakukan dengan membandingkan ID3, C4.5 dan CART untuk menemukan rule dengan performance terbaik, yang paling efektif untuk memprediksi keberhasilan suatu UKM dalam menerapkan transformasi digital. Hasil menunjukkan ID3 memperoleh performance terbaik dengan akurasi 89.19% dan AUC 0.959. Atribut ATP menjadi root node pada seluruh pohon keputusan yang dihasilkan. Ini berarti variabel Peran Digital Marketing, Model TOE, Strategi Bisnis Digital, Adopsi technopreneurship mempunyai peranan besar atau dampak yang signifikan terhadap UKM dalam melaksanakan transformasi digital pada bisnisnya.
KLASIFIKASI KEMATANGAN PISANG BERDASARKAN CITRA WARNA KULIT MENGGUNAKAN DECISION TREE DAN SUPPORT VECTOR MACHINE DENGAN INTEGRASI YOLOV8 Deva Gitisari; Restu Putri Nisrina; Nayla Natania Putri; Sujiliani Heristian; Veti Apriana; Rame Santoso
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 2 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i2.6488

Abstract

  Di Indonesia, panen pisang sering dilakukan sebelum buah mencapai kematangan fisiologis. Akibatnya, seringkali pisang yang belum matang beredar di pasaran. Tujuan dari penelitian ini adalah untuk mengevaluasi akurasi dua algoritma Machine Learning, yaitu Decision Tree dan Support Vector Machine (SVM) untuk menentukan tingkat kematangan pisang dengan  menggunakan dataset 6000 gambar pisang yang dikategorikan unripe, ripe, overripe, dan rotten. Dataset dipecah dalam rasio 80:20 untuk data latih dan data uji. Kemudian, metrik akurasi, presisi, recall, dan skor F1 digunakan untuk menguji. Hasil pengujian menunjukkan algoritma SVM memiliki akurasi tertinggi 92%, melampaui Decision Tree yang memiliki akurasi 82%. Model SVM Terbaik kemudian dikombinasikan dengan YOLOv8 untuk identifikasi kematangan pisang secara real-time menggunakan kamera. Penelitian ini memberikan kontribusi dengan menunjukkan efektivitas kombinasi HSV-SVM serta implementasi real-time menggunakan YOLOv8 menawarkan solusi praktis untuk pemantauan kualitas pisang secara otomatis.
PENGEMBANGAN SISTEM INFORMASI PROPERTI SEWA BERBASIS WEB: PENDEKATAN DBLC DAN PERSPEKTIF MANAJEMEN SISTEM INFORMASI Jihan Zhafira Thamrin; Nurhafifah Matondang; Rifka Dwi Amalia
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 2 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i2.6531

Abstract

Rental properties particularly boarding houses, require fast, accurate, and structured information to manage tenants, rooms, and payments at scale. This study designs and develops a web-based Rental Property Information System for “Grogol Mansion” using the Database Life Cycle (DBLC) method. Requirements were elicited via interviews and observation, then modeled with ERD and translated into a relational schema implemented in PHP–MySQL. Core modules include public room catalog & availability, account registration and booking, payment recording, tenant complaints, and an admin dashboard with multi-role access. Black-box testing and user acceptance testing (UAT) confirmed that all critical flows ran without errors, data were consistently recorded, confirmations/notifications appeared as expected, and UI response times met the ≤3-second criterion under normal load. The system improved operational efficiency, data accuracy, and service transparency, while providing a digital promotion channel. From a Management Information Systems perspective, the solution strengthens decision-making through structured data, controlled access, and auditable reports.
TINJAUAN SISTEMATIS TREN, METODE, DAN DATA PADA PREDIKSI KELULUSAN MAHASISWA Rudy Ansari; Rudy Ansari; Sunardi Sunardi; Imam Riadi
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 2 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i2.6551

Abstract

Penelitian tentang prediksi kelulusan mahasiswa banyak dipublikasikan akan tetapi biasanya metode beserta data yang dihasilkan dikemas secara terpisah dan kompleks sehingga gambaran tentang topik prediksi kelulusan mahasiswa saat ini kurang komprehensif. Tinjauan literatur ini bertujuan untuk mengidentifikasi dan menganalisis tren penelitian, dataset, dan metode tentang prediksi kelulusan mahasiswa yang dipublikasikan antara tahun 2020-2025. Berdasarkan kriteria inklusi dan ekslusi, tercatat sebanyak 75 artikel dari 199 artikel yang bersumber pada jurnal kuartil 1-4. Tinjauan literatur sistematis dapat didefinisikan sebagai proses mengidentifikasi, menilai, dan menginterpretasikan semua bukti penelitian yang tersedia untuk memberikan jawaban atas pertanyaan penelitian yang spesifik. Hasil analisis dalam lima tahun terakhir mengungkapkan bahwa penelitian prediksi kelulusan mahasiswa terdapat empat topik yaitu prediksi/klasifikasi, analisis dataset, pengelompokan (clustering), dan estimasi. Selain itu,  terdapat juga dua tren yang dibahas yaitu pemilihan fitur (feature selection) dan data tidak seimbang (imbalance data). Kategori data yang digunakan pada lima tahun terakhir lebih banyak menggunakan data private atau data real sebanyak 91% daripada data public. Metode yang paling sering digunakan pada topik-topik tersebut adalah Random Forest (RF), dan paling jarang yaitu metode Artificial Neural Network (ANN). Terdapat juga penggabungan metode untuk optimasi parameter di beberapa klasifikasi.
PENERAPAN METODE UCD DALAM PERACANGAN SISTEM INFORMASI PENGELOLAAN PEMINJAMAN BUKU PERPUSTAKAAN KOTA PADANGSIDEMPUAN Bunga Adella Utami; Ali Ikhwan
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 2 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i2.6706

Abstract

Proses pengelolaan peminjaman buku di Perpustakaan Kota Padangsidempuan masih menghadapi berbagai kendala, seperti ketidakakuratan data, keterlambatan pencatatan, serta keterbatasan akses informasi bagi pengguna akibat sistem yang masih manual. Kondisi tersebut berdampak pada rendahnya efisiensi layanan serta kurang optimalnya pengalaman pengguna dalam mencari, meminjam, maupun mengembalikan buku. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem informasi pengelolaan perpustakaan berbasis web dengan menerapkan metode User Centered Design, sehingga kebutuhan pengguna dapat diidentifikasi secara akurat dan terakomodasi dalam solusi sistem yang dibangun. Penelitian menggunakan pendekatan kualitatif melalui observasi, wawancara, dan studi pustaka untuk menggali kebutuhan pustakawan dan anggota perpustakaan. Hasil penelitian mencakup perancangan prototipe sistem yang meliputi fitur login, pengelolaan koleksi, pencarian buku, peminjaman, pengembalian, pemesanan (booking) buku, serta rekomendasi otomatis berbasis Collaborative Filtering. Pengujian menggunakan metode Black Box Testing menunjukkan bahwa seluruh fitur berjalan dengan baik sesuai fungsi yang diharapkan. Kesimpulan penelitian menyatakan bahwa penerapan UCD mampu menghasilkan sistem informasi yang lebih efisien, mudah digunakan, dan relevan dengan kebutuhan pengguna, sehingga dapat meningkatkan kualitas layanan perpustakaan serta mendukung proses administrasi secara lebih efektif.
ANALISIS KINERJA TATA KELOLA TEKNOLOGI INFORMASI PADA PERPUSTAKAAN XYZ MENGGUNAKAN FRAMEWORK COBIT 5.0 Yanuar Wicaksono; Denis Ariski; Tri Rochmadi; Raden Nur Rachman Dzakiyullah
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 2 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The use of information technology in organizations, including government agencies, is crucial for improving efficiency and service quality. XYZ Library utilizes information technology in various aspects of its operations, thus requiring an analysis of information technology governance to ensure optimal utilization. This study aims to analyze the performance of information technology governance at XYZ Library using the COBIT 5.0 Framework, focusing on the Deliver, Service, and Support (DSS) and Monitor, Evaluate, and Assess (MEA) domains. The research method used is a qualitative descriptive method, with data collection through interviews, observations, and questionnaires. The analysis was conducted to measure the level of capability of the DSS and MEA domains and identify gaps (GAP) between the current state (as-is) and the expected state (to-be). The results show that four of the five domains are at levels 4 or 3, with a GAP of 1 level from the expected target. DSS01, MEA02, and MEA03 show fairly consistent processes but still need improvement in terms of innovation, documentation, and compliance audits. Meanwhile, the DSS02 and MEA01 domains still require improvement in terms of documentation and incident evaluation procedures, as well as system performance. This study provides strategic recommendations aimed at strengthening information technology governance at the XYZ Library on a sustainable basis in the future.
ANALISIS SENTIMEN KOMUNITAS SEKOLAH TERHADAP KEBIJAKAN ECO SCHOOL MENGGUNAKAN MODEL INDOBERT Mufadhil; Joko Handoyo
Indonesian Journal of Business Intelligence (IJUBI) Vol 9 No 1 (2026): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

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Abstract

The Eco School (Adiwiyata School) program is an environmental education policy involving students, teachers, and parents as key stakeholders. The success of this program depends heavily on the perceptions of these three groups. This study aims to analyze school community sentiment towards the implementation of the Eco School policy using a Natural Language Processing (NLP) approach based on the IndoBERT model. A total of 1,000 text data points were collected from social media, educational discussion forums, and open-ended questionnaires, then went through preprocessing, manual labeling, and fine-tuning stages of the IndoBERT model to classify positive, neutral, and negative sentiments. The analysis results show a distribution of sentiment: positive 65%, neutral 25%, and negative 10%, with a model accuracy reaching 91.2%. Positive sentiment is predominantly triggered by creative and practical activities that increase environmental awareness, while negative sentiment is related to the administrative burden on teachers, additional costs for parents, and inconsistencies in program implementation. Analysis by group shows significant differences in perception: students tend to be the most positive (78%), while teachers (58%) and parents (55%) are more critical of administrative and financial aspects. These findings confirm the effectiveness of the transformer architecture for analyzing Indonesian-language education policy and emphasize the need for a segmented change management approach. The study recommends streamlining administrative systems, ensuring funding transparency, and tailoring communication strategies to the characteristics of each stakeholder group.
POLA KEPUASAN PELANGGAN PDAM MENGGUNAKAN DATA MINING PADA BIG DATA OPERASIONAL DAN LAYANAN Nanang Fahrurozi; Joko Handoyo
Indonesian Journal of Business Intelligence (IJUBI) Vol 9 No 1 (2026): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study addresses the challenges faced by PDAM (Regional Water Company) in holistically understanding customer satisfaction due to fragmented data. By applying data mining to the integrated big data of Perumda Air Minum Tirta Amerta Blora, the study combined 7,766 data points from technical reports, meter calibrations, SIMPel complaints, the Si Tampan application, and social media using the CRISP-DM methodology. K-Means Clustering analysis identified four customer segments: Loyal Satisfied (18%), Technical Complaints (32%), Administrative Issues (29%), and Dissatisfied (21%). Three areas—Cepu, Ngawen, and Randublatung—were confirmed as critical areas with a Silhouette Score of 0.58. Random Forest Classification revealed five dominant satisfaction factors: complaint response time (0.224), water pressure (0.198), frequency of interruptions (0.156), meter status (0.142), and arrears (0.134). A strong correlation was found between water pressure and complaint frequency (r = -0.72). The predictive model demonstrated excellent performance with 89% accuracy, 88% precision, 85% recall, F1-score 0.86, and AUC-ROC 0.93. TF-IDF sentiment analysis confirmed the dominance of technical complaints on the terms "leak" and "water not coming out," as well as appreciation for digital innovation with 54% positive sentiment on social media. These findings recommend prioritizing infrastructure improvements in critical areas, optimizing complaint response times to less than 8 hours, developing a real-time analytics dashboard, strengthening Si Tampan's digital services, and a proactive social media strategy with rapid responses to continuously improve customer satisfaction.
MODEL RANDOM FOREST PREDIKSI KUNJUNGAN ULANG BERDASARKAN POLA PENGELUARAN Laga Kusuma Laga; Joko Handoyo
Indonesian Journal of Business Intelligence (IJUBI) Vol 9 No 1 (2026): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Noyo Gimbal View Blora tourism has experienced a significant decline in visits, from 500,552 (2024) to a projected 300,000 (2025), with revenue dropping from IDR 3 billion to IDR 1.5 billion. This research aims to build a predictive Model to identify potential tourist disloyalty using the Random Forest algorithm based on spending patterns and service satisfaction. The research method utilizes 3,000 visit records (June 2023–December 2025) from ticket transactions and Google Maps reviews. The target variable is loyalty status derived from revisit history. Modeling employs Random Forest with Hyperparameter optimization through GridSearchCV and 5-fold cross-validation, along with Model interpretation using Feature Importance and SHAP. Results show the Model achieves 87.3% Accuracy, 83.5% Precision, 78.2% Recall, 80.8% F1-Score, and 0.91 AUC. The three most influential features are review sentiment score (0.26), spending variation (0.20), and number of facility complaints (0.17). Characteristics of at-risk tourists include negative sentiment, at least 2 complaints, rating ≤ 2 stars, spending < IDR 20,000, high spending variation, and high Recency days. In conclusion, service satisfaction factors are more dominant than spending patterns in determining tourist loyalty. This Model can be implemented as an early warning system to design intervention strategies for increasing tourist retention.

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