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Open research questions in Data Mining and Machine Learning Applications

76 unresolved questions extracted from the limitations and future-work sections of 284 Data Mining and Machine Learning Applications papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • The lack of optimized machine learning models for the classification of recipients of Direct Cash Assistance. The high error rate in determining recipients of Direct Cash Assistance.

    Optimasi Model Machine Learning untuk Reduksi Kesalahan Klasifikasi Penerima BLT Berbasis Data Sosial-Ekonomi · 2026 · DOI

  • Stunting is a complex problem affected by various factors. The prevalence of stunting in Nusa Tenggara Timur is high. There is a need to develop effective strategies to reduce stunting.

    Klasifikasi Stunting Balita Nusa Tenggara Timur Berdasarkan Faktor Sosial Ekonomi Kesehatan dengan Supervised Learning · 2026 · DOI

  • The challenge is the degradation of moral values among teenagers. The challenge is the limited understanding of the transformative stages of character internalization. The challenge is the lack of effective character education programs.

    Internalisasi Karakter Sabar dan Tanggung Jawab Melalui Tartil Al-Qur’an: Studi Kasus di SMPN 21 Samarinda · 2026 · DOI

  • Technical issues, such as bugs and notification problems, affect Google Classroom's effectiveness. Limited functionality and user experience issues can lead to negative user sentiment. Integrating Google Classroom with other digital learning tools can be challenging.

    Analisis Sentimen Pengguna Google Classroom terhadap Efektivitas Pembelajaran Digital Menggunakan Naive Bayes · 2026 · DOI

  • Deforestation poses significant environmental and conservation challenges. The complexity of predicting future deforestation scenarios. The need for accurate land cover classification and change detection.

    Analisis Spasial Deforestasi Kawasan Hutan Konservasi Taman Nasional Kerinci Seblat Akibat Ekspansi Perkebunan Gambir di Kecamatan Sutera Kabupaten Pesisir Selatan · 2026 · DOI

  • The study identifies challenges faced by teachers in implementing Pancasila education. The research highlights the need for teacher training and support. The study suggests the need for further studies on the effectiveness of Pancasila education.

    IMPLEMENTASI PEMBELAJARAN PENDIDIKAN PANCASILA DALAM PENGEMBANGAN SIKAP TOLERANSI PESERTA DIDIK KELAS VIII DI SMP NEGERI 6 SAMARINDA · 2026 · DOI

  • Further research is needed to explore the challenges of implementing CSR programs in the context of local development policies. Further research is needed to examine the impact of CSR programs on local development outcomes.

    ANALISIS SINERGITAS SEKTOR SWASTA DAN PEMERINTAH DAERAH DALAM PENGELOLAAN CSR DI KOTA MALANG · 2026 · DOI

  • The lack of synchronization between CSR programs and local development policies. The lack of understanding of the effectiveness of CSR programs in achieving local development goals.

    ANALISIS SINERGITAS SEKTOR SWASTA DAN PEMERINTAH DAERAH DALAM PENGELOLAAN CSR DI KOTA MALANG · 2026 · DOI

  • The study identifies a gap in the existing literature on emergency event analysis in Surabaya. The study aims to address this gap by using the K-Means Clustering algorithm to group emergency event data into three clusters.

    Clustering of Emergency Events in Surabaya Using K-Means Algorithm · 2026 · DOI

  • Further analysis of public sentiment towards Danantara. The application of SVM to other sentiment analysis tasks.

    Analisis Sentimen Publik Pada Media Sosial X Terhadap Pembentukan Danantara Menggunakan Metode <i>Support Vector Machine</i> · 2026 · DOI

  • The lack of understanding of the distribution of new students based on their school of origin and geographic location. The need for targeted promotion strategies.

    Penerapan K-Means Clustering, DBSCAN, dan K-Modes untuk Segmentasi Mahasiswa Baru Berdasarkan Asal Sekolah dan Wilayah Geografis (Studi Kasus: STIKES Guna Bangsa Yogyakarta) · 2026 · DOI

  • The study faced challenges in terms of the limited number of features and instances in the dataset. The study faced challenges in terms of the complexity of the student dropout problem and the need to develop accurate prediction models. The study faced challenges in terms of the need to understand the relationship between PCA and Random Forest in machine learning.

    Principal Component Analysis pada Random Forest untuk Deteksi Dini Dropout Mahasiswa · 2026 · DOI

  • Future studies should investigate the effect of using different numbers of principal components or different PCA techniques on the performance of Random Forest. Future studies should compare the performance of Random Forest with PCA with other machine learning algorithms. Future studies should investigate the application of PCA and Random Forest in other domains, such as predicting student performance and identifying students at risk of failing.

    Principal Component Analysis pada Random Forest untuk Deteksi Dini Dropout Mahasiswa · 2026 · DOI

  • The study faces challenges in obtaining accurate population data. The study needs to address the issue of reliable population estimation.

    Analisis Data Mining dalam Prediksi Pertumbuhan Penduduk Kabupaten Serdang Bedagai Menggunakan Regresi Linear Berganda · 2026 · DOI

  • Disrupted access to food, health services, and sanitation in post-disaster areas. Limited infrastructure and resources in disaster areas.

    Model Explainable Machine Learning pada Aplikasi Nutrisiaga untuk Prediksi Risiko Stunting di Wilayah Pascabencana · 2026 · DOI

  • The complexity of car body surface images. The need for high accuracy and efficiency in defect detection. The large volume of image data.

    Car Body Surface Defect Detection System Based on Image Analysis and Big Data · 2026 · DOI

  • The lack of sentiment analysis on Danantara. The need for a comprehensive understanding of public sentiment towards Danantara.

    Analisis Sentimen Publik Pada Media Sosial X Terhadap Pembentukan Danantara Menggunakan Metode <i>Support Vector Machine</i> · 2026 · DOI

  • K-Means has a significant weakness: the number of clusters is determined randomly. There is a need for a method to automatically determine the optimal number of clusters.

    OPTIMASI K-MEANS CLUSTERING PSO UNTUK PENENTUAN JUMLAH CLUSTER OPTIMAL PADA DATA KANKER PAYUDARA · 2026 · DOI

  • Future research can apply the study's approach to other villages or communities. Further research can explore the use of other data mining algorithms for health data analysis.

    PENERAPAN DATA MINING UNTUK CLUSTERING POTENSI KESEHATAN MASYARAKAT DESA MENGGUNAKAN ALGORITMA K-MEANS · 2026 · DOI

  • The study identifies a gap in health data analysis for community health planning. The research aims to address this gap by applying data mining techniques.

    PENERAPAN DATA MINING UNTUK CLUSTERING POTENSI KESEHATAN MASYARAKAT DESA MENGGUNAKAN ALGORITMA K-MEANS · 2026 · DOI

  • There is a need to identify the dominant factors that influence IPK. Prior studies have not provided a comprehensive view of the factors that influence IPK.

    Analisis Data Akademik Pada Faktor-Faktor yang Mempengaruhi IPK Mahasiswa Studi Kasus : Program Studi Sistem Informasi Universitas Mahakarya Asia · 2026 · DOI

  • Further studies can explore the use of other supervised learning algorithms in classifying stunting. Further studies can investigate the impact of other factors on stunting.

    Klasifikasi Stunting Balita Nusa Tenggara Timur Berdasarkan Faktor Sosial Ekonomi Kesehatan dengan Supervised Learning · 2026 · DOI

  • The study focuses only on academic attributes, excluding non-academic factors. Future research could incorporate additional variables for a more holistic understanding.

    Analisis Klasterisasi Prestasi Siswa Dengan Metode K-Means di SMP Negeri 92 Jakarta · 2026 · DOI

  • Current evaluation methods lack objectivity and comprehensiveness. There is a need for methods that can identify distinct patterns in student achievement.

    Analisis Klasterisasi Prestasi Siswa Dengan Metode K-Means di SMP Negeri 92 Jakarta · 2026 · DOI

  • To evaluate the methods on multi-class datasets. To compare the performance of the methods with other techniques. To apply the methods to real-world applications.

    Komparasi Metode SMOTE-Tomek dan SMOTE-ENN untuk Mengatasi Data Imbalanced · 2026 · DOI

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76 open questions have been extracted from the limitations and future-work passages of 284 Data Mining and Machine Learning Applications papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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