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All Journal Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Teknologi dan Otomasi
Imam Muslem
Universitas Almuslim Bireuen
Computer Science & IT

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Konsep Penyelesaian Permasalahan Kelangkaan Gas Elpiji 3kg di Indonesia dengan Memanfaatkan Teknologi Informasi Imam Muslem; Rizky Maulana; Afriana
Jurnal Teknologi dan Otomasi Vol. 1 No. 2 (2025): (December) Jurnal Jambo Digitech (Jurnal Teknologi Informatika dan Komputer)
Publisher : LLDIKTI WILAYAH XIII

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Abstract

Gas Elpiji 3 Kg merupakan bahan bakar bersubsidi yang diperuntukkan bagi masyarakat berpenghasilan rendah. Namun, praktik penyalahgunaan distribusi oleh agen dan pengecer ilegal sering menyebabkan kelangkaan, sehingga kelompok masyarakat yang berhak justru kesulitan memperoleh gas bersubsidi. Penelitian ini bertujuan mengusulkan konsep pemanfaatan teknologi informasi untuk meningkatkan transparansi dan akuntabilitas dalam distribusi Elpiji 3 Kg. Metode yang digunakan berupa studi literatur, observasi lapangan, serta analisis praktik distribusi untuk merumuskan model sistem informasi yang mampu meminimalkan potensi kecurangan. Hasil kajian menunjukkan bahwa penerapan sistem informasi berbasis komputerisasi dengan verifikasi data konsumen dapat memperbaiki pola distribusi, mengurangi manipulasi stok oleh agen, dan menjamin subsidi tepat sasaran. Kontribusi utama penelitian ini adalah menghadirkan kerangka solusi berbasis teknologi yang aplikatif bagi pemerintah dan pemangku kepentingan dalam mengatasi masalah kelangkaan gas bersubsidi.
Prediction of KIP Scholarship Eligibility at Universitas Almuslim Using an Explainable Artificial Intelligence–Based XGBoost Algorithm Zulkifli; Rizky Maulana; Muhammad Yasar Al Wafi; Imam Muslem
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 04 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i04.1963

Abstract

The selection process for Kartu Indonesia Pintar (KIP) scholarship recipients at the higher education level continues to face several challenges, including subjective assessment, limited transparency, and the suboptimal use of data-driven decision support systems. This study aims to develop a predictive model for KIP scholarship eligibility at Universitas Almuslim using the XGBoost algorithm integrated with an Explainable Artificial Intelligence (XAI) approach. The dataset employed in this study consists of synthetic data constructed based on official KIP selection parameters, encompassing economic, academic, social, and demographic aspects, thereby ensuring the confidentiality of student data. The research stages include data preprocessing, predictive modeling, policy-based validation, and analysis of prediction results. The XGBoost algorithm is utilized to generate eligibility predictions along with associated probability scores, which are subsequently evaluated to ensure alignment with scholarship selection principles and regulations. The simulation results demonstrate a clear separation between eligible and non-eligible students, with prediction probabilities predominantly concentrated at extreme values, indicating a high level of model confidence. Further analysis reveals that economic indicators and social affirmation variables exert a more dominant influence than academic factors, which function as supporting criteria. These findings indicate that the proposed system is capable of producing stable and consistent predictions while enhancing transparency and accountability in the decision-making process. This study proposes an interpretable scholarship eligibility prediction framework that can be adapted by other higher education institutions as a fair and data-driven decision support system.
Co-Authors Afriana Muhammad Yasar Al Wafi Rizky Maulana Zulkifli