Analysing User Reviews with ETL using Pentaho Data Integration

Authors

  • Tri Luhur Indayanti Sugata Universitas Pembangunan Nasional Veteran Jawa Timur
  • Rafika Rahmawati Universitas Pembangunan Nasional Veteran Jawa Timur
  • Tri Puspa Rinjeni Universitas Pembangunan Nasional Veteran Jawa Timur
  • Virdha Rahma Aulia Universitas Pembangunan Nasional Veteran Jawa Timur
  • Prasasti Karunia Farista Ananto Universitas Pembangunan Nasional Veteran Jawa Timur
  • Iqbal Ramadhani Mukhlis Universitas Pembangunan Nasional Veteran Jawa Timur

DOI:

https://doi.org/10.62712/juktisi.v4i2.403

Keywords:

Pentaho Data Integration, User Review, ETL, Sentuh Tanahku, Data

Abstract

User reviews are a crucial element in guiding the continuous improvement of mobile applications for developers. This research aims to utilize Extract, Transform, Load (ETL) techniques using Pentaho Data Integration to analyze user reviews of government mobile applications which is ‘Sentuh Tanahku’, focusing on improving service quality through actionable data insights. The ETL process involves collecting and cleaning data from the Google Play Store to derive valuable insights that inform recommendations for app improvement. After data extraction, text preprocessing steps, such as cleansing, case folding, and keyword filtering, were applied to prepare the data for analysis. By categorizing user reviews into key aspects such as user interface, performance, bug fixes, security, compatibility and feature development this research enables the identification of most frequently discussed and complained about by users. The output of this research includes a structured dataset in Excel format. By demonstrating the effectiveness of ETL and text analysis in transforming unstructured user reviews into strategic insights, this research contributes to utilizing Pentaho Data Integration as an alternative and effective tool for processing and analyzing user reviews.

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References

U. R. Sa’adah, Murwaniyah, D. I. Pradana, Masutiah, N. Panggabean, and Hamka, “APLIKASI SENTUH TANAHKU SEBAGAI INOVASI PELAYANAN PUBLIK DI KANTOR WILAYAH BADAN PERTANAHAN NASIONAL PROVINSI D.K.I. JAKARTA,” Jurnal Administrasi Bisnis Terapan, vol. 5, no. 1, Dec. 2022, doi: 10.7454/jabt.v5i1.1037.

Mariana Derlan Masia Harahap, F. Ferdinand, and Luluk Tri Harinie, “Pemanfaatan Aplikasi Sentuh Tanahku Guna Perbaikan Kinerja Layanan di Kantor Pertanahan Kota Palangka Raya,” Edunomics Journal, vol. 4, no. 2, pp. 103–125, Jun. 2023, doi: 10.37304/ej.v4i2.10015.

Z. Jiang, V. Liu, and M. Erne, “Examining the Usefulness of Customer Reviews for Mobile Applications,” Journal of Database Management, vol. 35, no. 1, pp. 1–23, May 2024, doi: 10.4018/JDM.343543.

H. Sujadi, “ANALISIS SENTIMEN PENGGUNA MEDIA SOSIAL TWITTER TERHADAP WABAH COVID-19 DENGAN METODE NAIVE BAYES CLASSIFIER DAN SUPPORT VECTOR MACHINE,” INFOTECH journal, vol. 8, no. 1, pp. 22–27, Mar. 2022, doi: 10.31949/infotech.v8i1.1883.

F. A. Larasati, D. E. Ratnawati, and B. T. Hanggara, “Analisis Sentimen Ulasan Aplikasi Dana dengan Metode Random Forest,” 2022. [Online]. Available: http://j-ptiik.ub.ac.id

T. J. Firdaus, J. Indra, S. Arum, P. Lestari, and H. Hikmayanti, “SENTIMENT ANALYSIS OF THE SAMBARA APPLICATION USING THE SUPPORT VECTOR MACHINE ALGORITHM,” vol. 5, no. 4, pp. 1183–1192, 2673, doi: 10.52436/1.jutif.2024.5.4.2673.

G. Rosalinda, R. Santoso, and P. Kartikasari, “PEMODELAN TOPIK ULASAN APLIKASI NETFLIX PADA GOOGLE PLAY STORE MENGGUNAKAN LATENT DIRICHLET ALLOCATION,” Jurnal Gaussian, vol. 11, no. 4, pp. 554–561, Feb. 2023, doi: 10.14710/j.gauss.11.4.554-561.

P. Bhuvaneshwari, A. N. Rao, Y. H. Robinson, and M. N. Thippeswamy, “Sentiment analysis for user reviews using Bi-LSTM self-attention based CNN model,” Multimed Tools Appl, vol. 81, no. 9, pp. 12405–12419, Apr. 2022, doi: 10.1007/s11042-022-12410-4.

A. D. Barahama and R. Wardani, “Utilization Extract, Transform, Load For Developing Data Warehouse In Education Using Pentaho Data Integration,” J Phys Conf Ser, vol. 2111, no. 1, p. 012030, Nov. 2021, doi: 10.1088/1742-6596/2111/1/012030.

I. Putu, W. Prasetia, I. Nyoman, and H. Kurniawan, “Implementasi ETL (Extract, Transform, Load) pada Data warehouse Penjualan Menggunakan Tools Pentaho,” TIERS Information Technology Journal, vol. 2, no. 1, pp. 39–47, 2021, [Online]. Available: https://journal.undiknas.ac.id/index.php/tiers

I. P. A. Eka Pratama and R. Bernard, “Analisa Kategori Barang dengan Penjualan Terbanyak dalam Jangka Waktu 3 Bulan Menggunakan Data Warehouse,” Jurnal ELTIKOM, vol. 6, no. 1, pp. 65–78, Jan. 2022, doi: 10.31961/eltikom.v6i1.457.

R. I. Alif, M. Idhom, and W. S. JS, “PENERAPAN TEKNIK ETL PADA KOMENTAR APLIKASI FLIP.ID DI APLIKASI PLAYSTORE DENGAN APLIKASI PENTAHO,” Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, vol. 5, no. 2, pp. 1264–1272, Aug. 2024, doi: 10.46306/lb.v5i2.713.

Purwita Sari, Lucky Indra Kesuma, Mira Afrina, and Dedy Kurniawan, “Pemodelan Integrasi Data Barang Milik Negara di Perguruan Tinggi Menggunakan Metode ETL (Extract, Transform, Load) dengan Pentaho,” The Indonesian Journal of Computer Science, vol. 13, no. 5, Oct. 2024, doi: 10.33022/ijcs.v13i5.4424.

N. W. S. Saraswati and N. M. L. Martarini, “Extract Transform Loading Data Absensi Stmik Stikom Indonesia Menggunakan Pentaho,” MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 19, no. 2, pp. 273–281, May 2020, doi: 10.30812/matrik.v19i2.564.

E. Haddi, X. Liu, and Y. Shi, “The Role of Text Pre-processing in Sentiment Analysis,” Procedia Comput Sci, vol. 17, pp. 26–32, 2013, doi: 10.1016/j.procs.2013.05.005.

K. Kmgs and R. Rahm, “Learning to Use Normalization Techniques for Preprocessing and Classification of Text Documents,” 2022.

S. Malgaonkar, S. A. Licorish, and B. T. R. Savarimuthu, “Prioritizing user concerns in app reviews – A study of requests for new features, enhancements and bug fixes,” Inf Softw Technol, vol. 144, Apr. 2022, doi: 10.1016/j.infsof.2021.106798.

S. Pradha, M. N. Halgamuge, and N. Tran Quoc Vinh, “Effective Text Data Preprocessing Technique for Sentiment Analysis in Social Media Data,” in 2019 11th International Conference on Knowledge and Systems Engineering (KSE), IEEE, Oct. 2019, pp. 1–8. doi: 10.1109/KSE.2019.8919368.

W. Maalej, Z. Kurtanović, H. Nabil, and C. Stanik, “On the automatic classification of app reviews,” Requir Eng, vol. 21, no. 3, pp. 311–331, Sep. 2016, doi: 10.1007/s00766-016-0251-9.

Y. Kalmukov, “USING WORD CLOUDS FOR FAST IDENTIFICATION OF PAPERS’ SUBJECT DOMAIN AND REVIEWERS’ COMPETENCES 15.” [Online]. Available: www.compsystech.org

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Published

2025-07-07

How to Cite

Sugata, T. L. I., Rafika Rahmawati, Tri Puspa Rinjeni, Virdha Rahma Aulia, Prasasti Karunia Farista Ananto, & Iqbal Ramadhani Mukhlis. (2025). Analysing User Reviews with ETL using Pentaho Data Integration. Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI), 4(2), 451–458. https://doi.org/10.62712/juktisi.v4i2.403