Article Per Year (5 Year)
p-Index From 2020 - 2025
3.212
P-Index
This Author published in this journals
All Journal E-Journal Home Economic and Tourism Jurnal Pendidikan Teknologi dan Kejuruan Journal of Nonformal Education Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Ilmiah Telaah SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL PENDIDIKAN TAMBUSAI Data Science: Journal of Computing and Applied Informatics Jurnal Pendidikan dan Keluarga ABDIKARYA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Indo-MathEdu Intellectuals Journal Flawless INCOME: Indonesian Journal of Community Service and Engagement Jurnal Pengabdian Literasi Digital Indonesia
Hayatunnufus Hayatunnufus
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

Published : 53 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Data Science: Journal of Computing and Applied Informatics

 1 
Daycare Recommendation System Using Fuzzy Logic Method and Haversine Formula (Case Study : Medan City) Br Sirait, Friska Pegrisentia; Hayatunnufus, Hayatunnufus; Hardi, Sri Melvani
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 1 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i1-14354

Abstract

The problem currently faced is the lack of trust from some parents towards daycare due to the lack of detailed information about daycare and the lack of attractive promotional media for working parents to entrust their children. Therefore, a decision support system is needed that uses the fuzzy logic method and haversine formula to assist in decision making when choosing the best alternative in daycare selection. The criteria used in this study were price, distance, quantity of caregivers, quality of caregivers, and facilities and infrastructure. The results of this study indicate that the system calculations are in accordance with manual calculations and the results of system testing prove that this system percieved of usefulness it has an actual score of 93.69% (0.9369), in terms of percieved ease of use it has an actual score of 93.21% (0, 9321), in terms of attitude toward using it has an actual score of 92.68% (0.9368) and in terms of behavior in use it has an actual score of 91.19% (0.9119). This was obtained by distributing questionnaires to 28 users (parents) during system testing.
Prediction of Dengue Fever in Coastal Areas of North Sumatera (Kuala Namu and Belawan) With Random Forest and Support Vector Machine (SVM) Methods Surbakti, Suzi; Hayatunnufus, Hayatunnufus; T. Henny Febriana
Data Science: Journal of Computing and Applied Informatics Vol. 7 No. 2 (2023): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v7.i2-14355

Abstract

Dengue Fever is a really infectious disease. This disease may cause death. The lack of health facilities in several regions can increase the number of cases and death. Thus, a proper prevention is needed so the number of cases can be decreased and the spread of the fever can be prevented especially in remote area like the coast area of North Sumatera. Because of this, a system that can predict the number of cases based on several parameters is needed to prevent the spread of fever in several areas, using Random Forest dan Support Vector Machine method. Both methods have different forecast results but the number is close to the actual number of cases. Random Forest can predict more accurate with MSE value at 43.
Co-Authors Agustina, Fadiya Aini, Wirdatul Amelia Widiatuti Asri, Diahning Aulia Azizah Ayuning, Geby , Denada Betris Sonita Br Sirait, Friska Pegrisentia Chairani, Vici Syahril Darmurtika, Linda Ayu Dedy Arisandi Dewi, Desi Hastika Dewi, Siska Miga Divia Indri Paramita Dwi Septiarini Eka Putri, Nela Aprilia Enjely, Ramona Fabitiary, Annisa Rizqa Fadilah, Rahmi Fandiga, Irfan Fatmawati, Eva Febrina, Eci Feriantano Sundang Pranata Fransisca, Devi Dwi Hanafi, Hafizul Fahri Harlini, Siti Miki Hidayatullah, M Wildan Hutasuhut, Nurul Inayah Ibrahim, Taupik Ida Ayu Putu Sri Widnyani Ika Parma Dewi Indra Saputra Ismail, Mazeni Isnanto Isnanto Jaya, Nurhadi Khunaefi, Rafli Komala, Yulia Laily, Rohisotul Linardita Ferial, Linardita Lindawati, Ayu Mandalika, Mandalika Marbun, Resida Damiana Mardani, Nuzra Melda Mahniza Murni Astuti Mursyida, Lativa Muzakiyah Qurrata A'yuni Nafiz Annas Ningrum, Mercylia Noviarti, Geni Eka NURHASANAH, AYU Nurhasanah, Rossy Pratiwi, Novika Pulungan, Aflah Mutsanni Purnamasari, Fanindia R. Sapto Hendri Boedi Soesatyo Rafsanjani, Ayatullooh Rahmadani Rahmadani Rahmiati Rahmiati Reflianto, Reflianto Reni Haerani Resmita, Resmita Ria Andriani Riska Desriani Saputri RIZA, YULIA Rosalina, Linda Rostamailis Rostamailis RR, Maylina Safrina, Adhelia Permata Sahbani, Fazira Sari, Adha Kurnia Setiawati, Erlin Simangunsong, Daisy Sere Damara Sri Melvani Hardi SUKRISTIANI, DWI Surbakti, Suzi Syamsul Arifin SYOFIA MELISA PUTRI T. Henny Febriana Tania, Shifa TATI NURHAYATI Toyib, Abu Yanita, Merita Yasnita Yasnita Yeni Elviza Febrianti Yolalalita, Suci Yolanda, Siska Septia Yuliana Yuliana yulyana sendia martina YUPELMI, MIMI Yusia Peni Yusmar Emmy Katin Yusuf, Rifki Maulana Zera, Yevawelita