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All Journal Jurnal Pengabdian Teknologi, Ekonomi dan Humaniora Journal Technology Information and Data Analytic
Timor Setiyaningsih
Darma Persada University
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Library & Information Science Social Sciences Other

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Training on the Use of AI Tools to Support High School/Vocational High School Education in Jakarta Herianto S.Pd., MT; Timor Setiyaningsih; Linda Nur Afifah
JEPTIRA Vol 2 No 2 (2024)
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/jep.v2i2.69

Abstract

The numerous facets of education have been significantly transformed by artificial intelligence (AI) technology. It is currently in widespread use to improve the efficiency of learning, provide personalized learning experiences, and assist instructors in managing administrative responsibilities. In addition to its advantages, the integration of AI into education also poses obstacles, including ethical concerns, excessive dependence on technology, and doubts about the validity of learning outcomes. The objective of this community service activity is to investigate the potential benefits and drawbacks of AI applications in education, as well as to offer suggestions for their effective implementation. Educators can employ AI more responsibly and effectively by comprehending both the advantages and obstacles. The training is administered online to ensure that a diverse audience, including high school and vocational school teachers in Jakarta, has access to the material. It commences with a pre-test to assess the initial comprehension of AI tools among participants. A post-test is administered at the conclusion of the session to assess the extent to which the knowledge has been enhanced as a result of the training
Overview of LabVIEW as a Graphical Programming Tool for Developing Industrial Technology Proficiency Reza Istoni; Yefri Chan; Nur Hasanah; Sarah Isniah; Budi Sumartono; Suzuki Syofian; Timor Setiyaningsih
JEPTIRA Vol 3 No 1 (2025)
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/jeptira.v3i1.94

Abstract

The purpose of this session is to expose participants with technical and vocational educational backgrounds to LabVIEW graphics programming software. In technical and industrial domains like biotechnology, aircraft, and telecommunications, LabVIEW is a commonly used system development tool. Hands-on practice and a demonstrative approach are used in the in-person instruction. LabVIEW's foundations, industrial applications, and hardware and software integration are all covered in the curriculum. The training results show that participants have a better understanding of visual programming and its possible uses in the business. This program is a component of a larger strategy to promote Industry 4.0-aligned technological literacy.
Decision Tree Regression Approach to Modeling Dengue, Tuberculosis, and Diarrhea Case Numbers Muhammad Dzaki Zahirsyah; Timor Setiyaningsih
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 2 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i2.121

Abstract

The increasing incidence of Dengue Hemorrhagic Fever (DHF), Tuberculosis (TB), and Diarrhea in a district area highlights the urgent need for a data-driven prediction system to support public health policy. This study develops a predictive model of case numbers at the sub-district level using the Decision Tree Regression algorithm within the CRISP-DM methodology. Secondary data from 2020-2023 were utilized, including disease case records (Health Office), demographic data (BPS), and environmental data (BMKG). The system was implemented as a web-based application built with PHP and Python/Flask, enabling dataset management, model retraining, and interactive visualization of predictions, complemented by risk classification and recommended interventions. Experimental results demonstrate high predictive accuracy, with R² values of 0.9130 for TB, 0.8805 for DHF, and 0.8228 for Diarrhea. Overall, the proposed system serves as an objective and measurable decision-support tool, assisting the District Health Office in formulating preventive policies more rapidly and effectively.
Co-Authors Budi Sumartono Herianto S.Pd., MT Linda Nur Afifah Muhammad Dzaki Zahirsyah Nur Hasanah Reza Istoni Sarah Isniah Suzuki Syofian yefri chan