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All Journal ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Jurnal farmasi UIN Alauddin Makassar Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Ilmiah Teknologi Informasi dan Robotika Djtechno: Jurnal Teknologi Informasi Prosiding Snastikom Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Kecerdasan Buatan dan Teknologi Informasi Jurnal Computer and Technology
Ahmad Zakir
Unknown Affiliation
Automotive Engineering Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Library & Information Science Medicine & Pharmacology Public Health

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Journal : Prosiding Snastikom

 1 
Sistem Informasi Geografis Capaian Vaksinasi Covid-19 Kabupaten Labuhanbatu Utara Berbasis Webgis Menggunakan Algoritma K-Means Febriansyah Marwan; Ahmad Zakir; Eka Rahayu
SNASTIKOM Vol. 1 No. 01 (2022): SEMINAR NASIONAL TEKNOLOGI INFORMASI & KOMUNIKASI (SNASTIKOM) 2022
Publisher : Unit Pengelola Jurnal Universitas Harapan Medan

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Abstract

Coronavirus Disease or COVID-19 is still a concern around the world. COVID-19 is a new disease caused by a new strain of coronavirus, Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV2). To control thespread of COVID-19, an effort is needed, namely vaccination. Meanwhile, in recording vaccination achievements,the North Labuhanbatu district government takes vaccination data from health facilities that carry out thevaccination program. The vaccination data is then compiled to be submitted to the North Sumatra provincialgovernment to be processed into information and released to the public. The absence of classification ofvaccination achievement data at the sub-district level is considered less than optimal because each sub-district isdifficult to determine whether the sub-district meets the vaccination target achievement or not. Therefore, analgorithm called K-Means Clustering is used. K-Means Clustering is used to group data based on the similarityof the data so that later it can be used to classify data on achievement of vaccination targets in each sub-districtin North Labuhanbatu district. The results of the classification of the data on the achievement of the vaccinationtarget are visualized in the form of a mapping. The mapping is realized through a web-based GeographicInformation System (GIS). The Geographic Information System of COVID-19 Vaccination in North LabuhanbatuRegency based on Webgis is able to classify data on the achievement of COVID-19 vaccination targets inLabuhanbatu Utara Regency using the K-Means Clustering algorithm where based on the results of the K-Meansiteration calculation, five of the eight sub-districts in North Labuhanbatu Regency North Labuhanbatu district hasmet the achievement of the vaccination target.
Analisis Data Pasien Klinik Halim Untuk Menentukan Masa Menopouse Menggunakan Metode Teorema Bayes Melfiyanti Wau; Ahmad Zakir; Septiana Dewi Andriana
SNASTIKOM Vol. 1 No. 01 (2022): SEMINAR NASIONAL TEKNOLOGI INFORMASI & KOMUNIKASI (SNASTIKOM) 2022
Publisher : Unit Pengelola Jurnal Universitas Harapan Medan

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Abstract

Abstract Menopause is a transitional period from mentruation to no longer having menstruation. Women who have enteredmenopause are likely to experience a deterioration in health, especially physical changes. Hot flushes, vaginasbecoming dry, sagging skin and wrinkles are examples of physical changes. The physical changes caused bymenopause can affect the psychological condition of menopausal women such as irritability, anxiety, stress anddepression. The problem of uncertainty of knowledge in this expert system is solved using the method of Bayes' Theorem. The process of determining the diagnosis in this expert system begins with a consultation session, wherethe system will ask relevant questions to the patient according to the main symptoms of monopause diseaseexperienced by the patient. Bayes' theorem is used to calculate the probability of an event occurring based on theinfluence obtained from the results of observations. In addition to this bayes theorem method makes use of sampledata obtained from the population also takes into account an initial distribution called the prior distribution. Thefinal result of this study is an expert system for diagnosing monopause diseases along with the probability valueof the diagnosed disease, which shows the level of system confidence in the disease and the therapeutic advice thatshould be given.
Co-Authors Andi Marwan Elhanafi Arfah Aini Boni Oktaviana Sembiring Dedy Irwan Edy Rahman Syahputra EKA RAHAYU Endi Utama MS Lubis Fadia Azzahra Febriansyah Marwan Hadinata, Edrian Haeria Haeria Lubis, Husni lubis, ihsan Melfiyanti Wau Melia Riska Mhd Fauzul Rizky Muhammad Zaul Rabbani W.D Nurshalati Tahar Septiana Dewi Andriana, Septiana Dewi Syifaa Salsabiila Putri Wahyu Hidayat Windy Hariyani Yermia Ndruru Yolanda Estefania Hasibuan