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All Journal Jurnal CoreIT JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL PENDIDIKAN TAMBUSAI IJISTECH (International Journal Of Information System & Technology) EQIEN - JURNAL EKONOMI DAN BISNIS Jurnal Infortech IJISTECH Tridharmadimas: Jurnal Pengabdian Kepada Masyarakat Jayakarta SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Abdimas Dosma (JAD) Jurnal Ilmiah Teknik Informatika dan Komunikasi Socius: Social Sciences Research Journal Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Abdimas Dosma
Imam Budiawan
Universitas Nusa Mandiri
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Pelatihan Dasar Ms.Power Point dalam Peningkatan Kreatifitas Presentasi bagi Staf dan Pengajar TKQ-TPQ Kecamatan Tanjung Priok Jakarta Utara Ummu Radiyah; Mulyani, Astriana; Sidik; Budiawan, Imam
JURNAL ABDIMAS DOSMA (JAD) Vol. 2 No. 2 (2023): JUNI
Publisher : IKATAN ALUMNI DOSEN MAGANG KEMENRISTEKDIKTI TAHUN ANGKATAN 2017

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70522/jad.v2i2.28

Abstract

The staff and teachers of TKQ/TPQ Kec. Tanjung Priok in their work activities is not proficient in using technology or applications that make work easier. The problems experienced include not being able to make creative presentation material. Based on the problems experienced by TKQ/TPQ staff and teachers in Tanjung Priok District, basic Ms. Power Point training was carried out to help find solutions to the problems they faced. Ms. Power Point basic training is held to make it easier for staff and teachers to be more able to use and apply technology in the work activities carried out. Ms. Power Point training can also help prepare creative and interesting presentation materials so that teaching and learning activities become dynamic and material can be conveyed by attracting the interest and attention of students and can be timely in disseminating teaching materials. The service method consists of survey stages, training, and evaluation stages. The results of the service show that the TKQ/TPQ staff and teachers, kec. Tanjung Priok can make presentation materials or teaching media that are effective and interesting.
Komparasi Algoritma Machine Learning (SVM, Random Forest, dan Regresi Logistik) untuk Prediksi Tingkat Obesitas Achmad Rivai Syahputra; Rian Hidayat; Fathur Rismansyah; Sumanto Sumanto; Imam Budiawan; Roida Pakpahan
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 5 No. 3 (2025): November: Jurnal Ilmiah Teknik Informatika dan Komunikasi 
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v5i3.1716

Abstract

Obesity is a global health issue with a continuously increasing prevalence. Early prediction of obesity levels is crucial for designing more effective intervention strategies. This study aims to apply and analyze the performance of three machine learning classification methods: Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression (LR), for predicting obesity levels. The research methodology utilizes a public dataset, ObesityLevels, downloaded from the Kaggle platform, which consists of 2111 medical and lifestyle records. The process includes data preprocessing to convert categorical features into numerical ones, splitting the data into training and testing sets with a 70:30 ratio, model training, and evaluation using accuracy, precision, recall, and F1-score metrics. The results indicate that the Random Forest (RF) algorithm achieved the highest performance, with an accuracy of 90.3%, precision of 90.3%, recall of 90.3%, and an F1-score of 90.3%. Based on these findings, it is concluded that the Random Forest model is the most effective choice for an obesity level prediction system based on the dataset used.
Co-Authors Achmad Rivai Syahputra Ade Setiawan Ahmad Yusuf Amas Sari Marthanti Arfhan Prasetyo - STMIK Nusa Mandiri Arfhan Prasetyo - UBSI Astriana Mulyani Astriana Mulyani, Mulyani Bella - STMIK Nusa Mandiri Bella - UBSI Belsana Butar Butar Desmulyati, Desmulyati Dwi Arum Ningtyas FAHRIZAL Fathur Rismansyah Firstianty Wahyuhening Fibriany Gata, Windu Hani Harafani Hani Harafani, Hani Hari, Raga Suhada Henny Leidiyana Hoiriah Hoiriah I Ispandi Ika Kurniawati Imam Sujarwo ispandi ispandi Ispandi Ispandi Ispandi Ispandi, Ispandi Kiswanto, Andi Diah Martua HamiSiregar Muhammad Nasrulloh Mulyadi Mulyadi Mulyani, Astriana Mushliha Prasetya, Arfhan Rian Hidayat Rizky, Fernando Jovanca Roida Pakpahan Romdonni, Achmad Roddi Rusli, Ahmad Rais Sidik Sidik Sidik Sidik Sidik Sulistyowati, Daning Nur Sumanto, Sumanto Sungkar, Adam Andrea Susan Rachmawati Ummu Radiyah Ummu Radiyah Ummu Radiyah, Ummu Wati Erawati Yasin, Saeful Yuris Alkhalifi