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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Sistemasi: Jurnal Sistem Informasi
Balqis, Fika Halimah
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Library & Information Science Other

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House Price Prediction using the Random Forest Regression Algorithm Balqis, Fika Halimah; Aini, Qurrotul
Sistemasi: Jurnal Sistem Informasi Vol 15, No 2 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i2.5726

Abstract

House price prediction is a complex problem because it is influenced by various factors such as building quality, location, and living area size. As a result, conventional methods often lack accuracy in estimating housing prices. This study aims to apply the Random Forest Regression (RFR) algorithm to predict house prices using the House Prices – Advanced Regression Techniques dataset from Kaggle, which contains 1,460 property records. The SEMMA (Sample, Explore, Modify, Model, Assess) methodology was adopted due to its systematic workflow and structured focus, which improves the reliability of the developed model. In the modeling stage, RFR was implemented because it is capable of handling non-linear patterns and maintains stable performance even with a large number of features. Based on the evaluation results, the model achieved a Root Mean Squared Error (RMSE) of 28,452.75 and a coefficient of determination (R²) of 89%. This was followed by a robustness test with an RMSE of 30,665.40, indicating the stability of the model. Feature importance analysis also revealed that OverallQual had the greatest influence on house price prediction. These findings confirm that Random Forest Regression is a reliable method for predicting house prices and has strong potential to be further developed for price recommendation systems, automated property valuation, and integration into digital platforms within the real estate industry.
Evaluasi Tata Kelola Teknologi Informasi pada PT Telkom Data Ekosistem (NeutraDC) Menggunakan Framework COBIT 2019 Domain APO Balqis, Fika Halimah; Hasbi Aufa Ibrahim; Nur Aeni Hidayah
JSI: Jurnal Sistem Informasi (E-Journal) Vol 17 No 2 (2025): JSI: Jurnal Sistem Informasi (E-Journal)
Publisher : Jurusan Sistem Informasi Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/jsi.v17i2.364

Abstract

This study evaluated information technology governance at PT Telkom Data Ekosistem (NeutraDC), a subsidiary of Telkom Indonesia operating in the data center services industry. As a key player in Indonesia’s digital transformation, NeutraDC was expected to ensure effective management of information and data security. The study focused on evaluating governance capabilities in two areas of COBIT 2019: APO13 (Managed Security) and APO14 (Managed Data). The main issues addressed were the absence of a formal assessment of existing capabilities and the lack of improvement benchmarks. A quantitative descriptive methodology was applied, involving questionnaires and interviews with information technology staff, and analyzed using the six-level COBIT capability model. The results showed that both areas achieved Level 5 (Optimizing), indicating the presence of strong policies, continuous monitoring, and proactive risk management. These findings reflected a mature and robust information technology governance process. However, the study recommended continuous improvement through regular audits, training, and policy updates to keep pace with technological and regulatory developments. The study provided actionable insights for organizations seeking to strengthen their data governance and information security through a unified framework.
Co-Authors Hasbi Aufa Ibrahim Nur Aeni Hidayah Qurrotul Aini