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INDONESIA
INFOKUM
Published by SEAN INSTITUTE
ISSN : 23029706     EISSN : 27224635     DOI : -
Core Subject : Science,
Computer Science & IT
The INFOKUM a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences. Software Engineering. Image Processing Datamining Artificial Neural Networks
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 842 Documents
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The Transmission of Terrorist Movements in Sulawesi through the Narrative of the Islamic State of DI/TII (1953-1965) Ahmad Subair
INFOKUM Vol. 14 No. 01 (2026): Infokum, January - February 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i01.3074

Abstract

This study analyses the transmission of the narrative of the Darul Islam/Indonesian Islamic Army (DI/TII) movement in Sulawesi led by Kahar Muzakkar (1953–1965) into the ideology of contemporary terrorist groups in the region. Using historical methods within a Systematic Literature Review (SLR) framework, the study reveals the mechanisms of transmission through kinship networks, informal education, and the circulation of literature that mythologises the history of this resistance. The findings show that the DI/TII narrative has been adapted and synthesised with transnational ideologies such as ISIS, resulting in historical-emotional legitimacy for groups such as Mujahidin Indonesia Timur (MIT). This process of ‘glocalisation of jihad’ confirms that counter-terrorism approaches in Sulawesi must critically consider the historical roots and memory of local conflicts, in addition to countering global narratives.
Laptop Price Prediction Based on Technical Specifications Using the Random Forest Algorithm Nabillah Nasywa Syahrani; Satria Nouval Wahyudi; Antonious Ariel Afendra; Wisti Dwi Septiani; Syaifur Rahmatullah Abdul
INFOKUM Vol. 14 No. 02 (2026): Infokum, March-April 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i02.3066

Abstract

This study develops a laptop price prediction model based on technical specifications using the Random Forest Regressor algorithm. The dataset, obtained from publicly available platforms such as Kaggle, comprises several key attributes, including brand, device category, processor type, user rating, and price. The analytical procedure involves data preprocessing, categorical feature encoding, model training, and performance evaluation. The evaluation results demonstrate strong predictive performance, with an R² value of 0.938, an RMSE of 22,021, and an MAE of 12,667, indicating high prediction accuracy and the model’s ability to explain more than 93% of the variance in laptop prices. These findings suggest that the Random Forest algorithm is highly effective for developing specification-based laptop pricing models and shows substantial potential for implementation in e-commerce platforms and automated pricing recommendation systems.

Page 85 of 85 | Total Record : 842

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