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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Manajemen Informatika Jayakarta El-Mujtama: Jurnal Pengabdian Masyarakat Bulletin of Multi-Disciplinary Science and Applied Technology Journal of Information Systems and Technology Research Journal of Artificial Intelligence and Engineering Applications (JAIEA) Journal of Mathematics and Technology (MATECH) Jurnal Pengabdian Pada Masyarakat METHABDI International Journal of Health, Engineering and Technology Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Saturnus: Jurnal Teknologi dan Sistem Informasi
Sihombing, Anton
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Journal : Saturnus: Jurnal Teknologi dan Sistem Informasi

 1 
Prediksi Tingkat Stunting Anak di Kabupaten Langkat Menggunakan Metode Regresi Linear Berganda : (Studi Kasus : Dinas PPKB-PPA Kab.Langkat) Dhea Alfiya Ningsih; Relita Buaton; Anton Sihombing
Saturnus : Jurnal Teknologi dan Sistem Informasi Vol. 2 No. 4 (2024): Oktober : Saturnus : Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v2i4.344

Abstract

Stunting is a growth and development disorder in children caused by chronic malnutrition over a long period of time, especially in the first 1,000 days of life, namely from pregnancy to the first 2 years of life. There are more than 149 million (22%) toddlers worldwide who are stunted, of which 6.3 million are Indonesian toddlers. Based on data from the Ministry of Health, the stunting rate in Indonesia in 2023 was recorded at 21.5 percent, only down 0.1 percent from the previous year which amounted to 21.6 percent. Predicting the number of stunted toddlers is very important and necessary to know the stunting rate in Langkat Regency in 2024, and the prediction results can help health workers in handling and preventing the spread of stunting. The method applied to this prediction system is Multiple Linear Regression where this analysis determines whether each independent variable is positively or negatively related, the direction of the relationship between variables, and estimates the value of the dependent variable will increase or decrease. The prediction system is carried out using the RapidMiner application because this application is very appropriate to produce information output in the form of prediction results for the coming year. The prediction results obtained are an increase and decrease in 2024 in each sub-district and there are sub-districts that do not experience an increase and decrease. The sub-district with the highest number was Secanggang with approximately 177 people, and the sub-district with the lowest number of stunted children was West Berandan with approximately 55 people. Then Stabat sub-district became the sub-district that experienced the most increase in the number of stunting, which was around 15 people, and the sub-district that experienced the most decrease was Kuala sub-district with a total of approximately 23 people. From the overall results it can be calculated that the number of stunting in all districts in Langkat Regency amounted to approximately 2453 people in 2024. And testing the error rate of prediction results using RMSE in the RapidMiner application of 7.63%, where the level of accuracy in the prediction of child stunting in Langkat Regency is 92.46%.
Penerapan Metode Monte Carlo pada Simulasi Antrian Poliklinik RSUD DR. RM. Djoelham Desty Dwi Putri; Akim M.H. Pardede; Anton Sihombing
Saturnus : Jurnal Teknologi dan Sistem Informasi Vol. 2 No. 4 (2024): Oktober : Saturnus : Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v2i4.368

Abstract

Long queues at the polyclinic of RSUD RM DR Djoelham Binjai often cause inconvenience to patients and reduce service efficiency. This study aims to analyze the queuing system at the hospital's polyclinic using the Monte Carlo method, which is able to model uncertainty in patient arrivals and service times. With this method, it is expected that a more accurate picture of patient waiting time and queue performance can be obtained so that improvement measures can be identified. The data used in this simulation includes the number of patients who come and the service time in the polyclinic. Monte Carlo simulations are carried out to predict various queuing scenarios based on variations that occur in patient arrivals and service duration. The simulation results provide information related to the estimated average waiting time of patients, and the level of queue density. This study shows that the application of the Monte Carlo method is effective in providing a more measurable solution to minimize waiting time and improve service quality at the polyclinic of RM DR Djoelham Binjai Hospital. These results are expected to be a reference for hospital management in making strategic decisions related to the optimization of health services. With the average waiting time for patients in the queue is 10.59 minutes while the average patient time is 25.34 minutes.
Co-Authors ., Novriyenni Achmad Fauzi ACHMAD FAUZI Adelia Ramadani Agung Aulia Tama Ahmad Fauzi Ahmad Nawawi Ambarita, Indah Andriansyah, M Juli Angel, Kiki Astari, Rizki Yulidha Astrika, Rahayu Buaton, Relita Budi Serasi Ginting Budi Serasi Ginting Clara Rosa Wijaya Desty Dwi Putri Dewi, Sintia Dhea Agustina Akmal Dhea Alfiya Ningsih Dini Syahfitri Fauzi, Achmad Fitri Handayani Fuji Dodo Aritonang Ginting, Budi Serasi Hana Niska Tafonao Hermansyah Sembiring Hotler Manurung Ihsan Wibowo Zakti Indah Malasari Julia Br Sembiring Kadim, Lina Arliana Nur Khair, Husnul Kiki Angel Kiki Angel Lailatul Magfiroh M Agung Hidayat Magdalena Simanjuntak Marto Sihombing Marto Sihombing Mhd Ferdiansyah Putra Natalia Sianturi, Ruth Naufal Falaah Nduru Novriyenni Novriyenni Novriyenni, Novriyenni Novriyenni, Novriyenni Pardede, Akim Manaor Hara Rahmat Ramadhan Ramadani, Suci Ratna Cantika Riski Ramadhansyah Risna Serviya Rizki Yulidha Astari Rusmin Saragih, Rusmin Serasi Ginting, Budi Serviya, Risna Shelly Maulia Sihombing, Marto Sirait, Suprianto Suci Rahmadani suci ramadani Suci Ramadhani, Suci Supri Anto Sirait Suprianto Sirait Syahputri, Heni Tasya Maysarah Br. Sembiring Tasya Maysarah Sembiring Triono, Arif Yani Maulita