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All Journal Jurnal Mantik ALACRITY : Journal Of Education
Yulita Molliq Rangkuti
Universitas Negeri Medan, Indonesia
Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Other

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Design of a geographic information system (gis) for the spread of covid-19 disease in medan city Melania Justice Panggabean; Yulita Molliq Rangkuti; Ichwanul Muslim Karo-Karo
Jurnal Mantik Vol. 6 No. 4 (2023): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i4.3437

Abstract

The world is currently facing an outbreak of the corona virus (Covid-19). Covid 19 is a group of highly diverse, enveloped, single-stranded RNA viruses. This disease causes respiratory tract infections in humans with severity ranging from mild to fatal. Examples of mild illnesses such as influenza while for deadly diseases such as MERS and SARS. Medan city is one of the areas that is prone to Covid-19 disease. Where the spread of Covid-19 has reached 16.4% the positive case rate with an assessment of the Covid-19 situation as of February 2022 is at Level 4. So, we need a sytem that can monitor the progress of the case. The purpose of this research is to build a geographic information sytem using the Fuzzy C-Means method and integrate GeoJSON to map the spread of the Covid-19 disease in Medan City.  The results of clustering calculations using the Fuzzy C-Means method yield the following results: Cluster 1 which contains the sub-districts of Medan Amplas, Medan Area, Medan Baru, Medan Barat, and Medan Perjuangan is in the green zone. Cluster 2 which contains the sub-districts of Medan Denai, Medan Tembung, Medan Petisah, Medan Kota, and Medan Timur is in the red zone. Cluster 3 which contains the sub-districts of Medan Tuntungan, Medan Selayang, Medan Johor, Medan Sunggal, and Medan Helvetia is in the orange zone. And Cluster 4 which contains the sub-districts of Medan Polonia, Medan Maimun, Medan Deli, Medan Labuhan, Medan Marelan, and Medan Belawan is in the yellow zone. 
Penggunaan K-Means Clustering untuk Segmentasi Tokoh Politik Berdasarkan Potensi Kepemimpinan Di Sumatera Utara M. Ananda Rizki Tambunan; Said Iskandar Al Idrus; Zulfahmi Indra; Yulita Molliq Rangkuti; Sudianto Manullang
ALACRITY : Journal of Education Volume 6 Issue 1 Februari 2026
Publisher : LPPPI Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52121/alacrity.v6i1.986

Abstract

Penelitian ini membahas penerapan algoritma K-Means Clustering untuk mengelompokkan tokoh politik di Sumatera Utara berdasarkan potensi kepemimpinan mereka. Permasalahan yang diangkat meliputi kesenjangan pembangunan antarwilayah, kompleksitas evaluasi kandidat, serta keterbatasan metode penilaian tradisional yang cenderung subjektif. Data yang digunakan merupakan data sekunder dari KPUD Sumatera Utara, Kemendagri, dan media sosial, dengan tiga variabel kuantitatif utama: tingkat pendidikan, pengalaman kepemimpinan, dan tingkat elektabilitas. Proses analisis meliputi normalisasi data, penentuan jumlah klaster optimal menggunakan metode elbow, dan penerapan algoritma K-Means untuk menghasilkan pengelompokan tokoh politik. Hasil penelitian menghasilkan beberapa klaster dengan karakteristik berbeda yang dapat memberikan gambaran profil kepemimpinan potensial di Sumatera Utara. Penelitian ini diharapkan dapat menjadi referensi objektif bagi masyarakat dan pemangku kepentingan dalam pengambilan keputusan politik, sekaligus memberikan kontribusi teoretis terhadap penerapan machine learning dalam analisis politik lokal.
Co-Authors Ichwanul Muslim Karo Karo M. Ananda Rizki Tambunan Melania Justice Panggabean Said Iskandar Al Idrus Sudianto Manullang Zulfahmi Indra