Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal JEECS (Journal of Electrical Engineering and Computer Sciences) Journal of Engineering and Technology Innovation
Luki Ardiantoro
Universitas Bina Sehat PPNI
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Transportation

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Penerapan Kerangka COBIT 2019 dalam Meningkatkan Efektivitas Tata Kelola TI di Kantor Pos X Asrul Asrul; Luki Ardiantoro; Sitti Aisa
Journal Of Engineering And Technology Innovation ( JETI ) Vol. 2 No. 01 (2025): Journal Of Engineering And Technology Innovation ( JETI )
Publisher : Rey Media Grafika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66084/jeti.v2i01.429

Abstract

Penelitian ini bertujuan untuk mengevaluasi penerapan tata kelola Teknologi Informasi (TI) di Kantor Pos Kotabumi berdasarkan framework COBIT 2019, dengan fokus pada domain Deliver, Service, and Support (DSS) serta Monitor, Evaluate, and Assess (MEA). Pendekatan yang digunakan adalah kualitatif dengan metode studi kasus melalui observasi, wawancara, dan studi dokumentasi. Hasil penilaian menunjukkan bahwa sebagian besar proses berada pada tingkat kematangan Level 0 hingga 2, yang mengindikasikan bahwa tata kelola TI masih dalam tahap awal dan belum terstruktur sepenuhnya. Analisis kesenjangan dilakukan untuk membandingkan kondisi aktual dengan target ideal, dan menghasilkan rekomendasi strategis berupa penguatan SOP, integrasi sistem pemantauan, pelatihan SDM, serta audit rutin. Validasi melalui Focus Group Discussion (FGD) mengonfirmasi bahwa temuan dan rekomendasi penelitian sesuai dengan kebutuhan organisasi dan dapat diimplementasikan secara bertahap.
Data-Driven Sentiment Analysis of Public Opinion on National Football Team Coaching Using Naïve Bayes Luki Ardiantoro; Nisa Ayunda; Muhammad Irfan
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 11 No. 2 (2026): December
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v11i2.4

Abstract

The appointment of a national football team coach often generates intense public discourse, particularly on social media, where opinions are expressed rapidly and at scale. However, such evaluations are typically subjective and lack a systematic, data-driven foundation. This study proposes a quantitative approach to assess public sentiment toward the Indonesian national team coach using sentiment analysis based on the Naïve Bayes classifier within the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. A dataset of 2,000 Indonesian-language tweets was collected from social media X and processed through data cleansing, normalization, tokenization, and sentiment labeling. The Naïve Bayes model was applied to classify sentiment polarity, and its performance was evaluated using accuracy, precision, recall, and ROC–AUC metrics. The results show that the model achieves an accuracy of 94.17%, with precision of 92.86% and recall of 94.55%, indicating strong classification performance. However, the AUC value of 0.686 suggests moderate discriminative ability. The findings reveal that public sentiment toward the coach is predominantly positive, reflecting increased supporter confidence. This study demonstrates the effectiveness of data-driven approaches for objective evaluation in sports analytics and highlights opportunities for improvement using advanced machine learning techniques.
Co-Authors Asrul Asrul Irfan, Muhammad Nisa Ayunda Sitti Aisa