Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ipteks Terapan : research of applied science and education
Ahmad Kamal
Institut Bisnis Dan Teknologi Pelita Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Veterinary Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
IT-DASHBOARD APPLICATION TO DETERMINE THE TYPE OF SUBSIDIZED ASSISTANCE Renita Astri; Zulfahmi Zulfahmi; Zulfahmi -; Ahmad Kamal
Jurnal Ipteks Terapan : research of applied science and education Vol. 17 No. 3 (2023): Jurnal Ipteks Terapan
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22216/jit.v17i3.2356

Abstract

IT-Dashboard is a user interface that shows information that can be read easily by users. The IT-Dashboar application of the subsidized assistance type decision support system was built to help and facilitate the community to find information on the type of subsidized assistance, as well as to help sub-district officials to determine which residents are eligible to receive assistance according to the criteria set by the central government so that assistance can be distributed on target. The case study will be conducted on poor families in the Lubuk Begalung sub-district of Padang city. This decision support system uses the AHP (Analytical Hierarchy Process) method to determine the type of subsidy for poor families. The AHP method is basically a comprehensive decision-making model by considering qualitative and quantitative aspects. The AHP method was chosen because it is conceptually simple, easy to understand, computationally efficient, and can measure the relative performance of decision-making alternatives. Keywords: Assistance, Subsidized, Support, Decision, Poor
Harnessing BERT for Semantic Understanding in Tourism Recommendation Engines Renita Astri; Lai Po Hung; Suaini Binti Sura; Ahmad Kamal
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6575

Abstract

It will be necessary for attraction managers within hotels to track guests' lifestyles to keep the business running. Such an understanding may be achieved, for example by analyzing reviews on attractions to capture the attitudes of the visitors towards the services and business within the tourism industry. The approach utilizes web scraping to gather user-generated reviews, using text preprocessing, data pre-processing, and further improvement of the model using labelled sentiment data divided into three sentiment classes: positive, negative, or neutral. The dataset consisting of 908 reviews were divided in 70:15:15 ratio for training, validation and testing. Model performance was measured in terms of accuracy, precision, recall and F1-score. In this study, the BERT deep learning model is used to classify sentiments of Indonesian tourist. Using the SmallBERT variant fine-tuned on 515k reviews for 5 epochs, the model achieved 91.40% accuracy, 90.51% precision, recall, and F1 score. The results indicate a dominance of positive sentiments, visualized using tableau. This research provides a robust foundation for developing intelligent sentiment-based recommendation systems in the tourism sector and suggests future exploration using other transformer-based models such as GPT, T5, or BART for comparative analysis.
Co-Authors Lai Po Hung Renita Astri Suaini Binti Sura Zulfahmi - Zulfahmi Fahmi