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All Journal Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Jurnal Mantik Penusa JIPN (Journal of Informatics Pelita Nusantara) Jurnal Nasional Komputasi dan Teknologi Informasi Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JOISIE (Journal Of Information Systems And Informatics Engineering) PITIN Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama Journal of Intelligent Decision Support System (IDSS) Jurnal Sistem Informasi dan Teknologi Jaringan Jurnal Pengabdian Pada Masyarakat Jurnal Pengabdian Masyarakat Nauli
Murni Marbun
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Sistem Pendukung Keputusan Penentuan Tingkat Kecanduan Masyarakat Terhadap Rokok dengan Metode Fuzzy Mamdani Daniel Andre Marpaung; Murni Marbun
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 4, No 1 (2021): Februari 2021
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v4i1.2748

Abstract

A person's addiction to smoking can be seen from the characteristics of the cigarette addict, including: difficulty controlling the desire to smoke, high appetite, frequent coughing, sleep disturbances, and difficulty concentrating. A person's addiction to cigarettes can have a bad impact on the health of that person. The research used the Fuzzy Mamdani method. The system was built using the Hypertext Preprocessor (PHP) programming language. The database management system uses My Structured Query Language (MYSQL). The criteria for the level of community addiction to cigarettes are cost, smoking frequency, and the environment. This study aims to design a Decision Support System for determining the level of community addiction to smoking and applying the Fuzzy Mamdani method for determining the level of community addiction to cigarettes. So it can be concluded that the person's level of addiction is at number 13 or categorized as CANDU. 
Implementasi Logika Fuzzy dalam Memprediksi Tingkat Kelulusan Tes Seleksi CPNS dengan Menggunakan Metode Tsukamoto Romantika Tambunan; Murni Marbun
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 4, No 1 (2021): Februari 2021
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v4i1.2750

Abstract

Applicants who take part in the selection of Candidates for Civil Servant Candidates (CPNS) must pass through the steps that must be taken which can determine the graduation rate. The criteria for predicting the passing of the CPNS selection test are used by the Basic Competency Selection (SKD) which consists of a Personal Characteristic Test (TKP), General Intelligence Test (TIU), National Insight Test (TWK), Competency Selection Section (SKB) which consists of a computer assisted test (CAT) and interviews, and the number of quotas received. This research is the implementation of Fuzzy Tsukamoto Logic in Predicting the Passing Rate of the CPNS Selection Test. The system for predicting the passing of the CPNS selection test was built using the Web-based PHP programming language. Data management using MySQL database. The overall defuzzyfication (Z) result in the system predicts the passing rate of CPNS = 61.950223979 = 62.
Co-Authors Anita Sindar Arjon Samuel Sitio Arjon Sitio Aswin Aswin Bambang Krismoyo Bobby Reza Bobby Reza Bobby Reza Bosker Sinaga Christina Aritonang Daniel Andre Marpaung Dinda Tiara Dolok Saribu, Enjeli Vista Bela Duy Murdy Lingga Dwi Putri Rahayu Dwi Septiani Putri Geri Reonaldo Sitepu Hardianti Manurung Hengki Tamando Sihotang Hoga Saragih Hoga Saragih Hoga Saragih Jijon Raphita Sagala Kordia Rodiana Br Turnip Lolita Lumban Gaol Maliki Ginting Melda Agustina Nababan Nafasansono Harefa Normi Verawati Marbun Petti Indrayati Sijabat Raudhatul Hasanah Sinaga Rici Surya Ardani Diningrat Ridho, Irhamir Rini Simanullang Romantika Tambunan Sadar Budi Wibowo Sansono Harefa Sianipar, Geovani Sinaga, Anita Sindar R M Winda Ayu Astuti