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All Journal Seminar Nasional Informatika (SEMNASIF) Jurnal Informatika Upgris JRSI (Jurnal Rekayasa Sistem dan Industri) JURNAL MEDIA INFORMATIKA BUDIDARMA Informatics for Educators and Professional : Journal of Informatics Jurnal Komputer Terapan Jurnal TAM (Technology Acceptance Model) IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Sarwahita : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Komputer dan Sistem Informasi @is The Best [Accounting Information System & Information Technology Business Enterprise] Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Santika : Jurnal Ilmiah Sains dan Teknologi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Cakrawala Repositori Imwi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Pengabdian Kepada Masyarakat Abdi Putra International Journal Engineering and Applied Technology (IJEAT) JURNAL ILMIAH INFOKOM Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Rekayasa Teknologi Nusa Putra Jurnal TAM (Technology Acceptance Model)
Dudih Gustian
Nusa Putra University
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Journal : Progresif: Jurnal Ilmiah Komputer

 1 
Perancangan Sistem Pakar Berbasis Web Menggunakan Case Based Reasoning Untuk Diagnosa Dini Covid-19 Mega Lumbia Sinaga; Dudih Gustian; Falentino Sembiring
Progresif: Jurnal Ilmiah Komputer Vol 17, No 2: Agustus 2021
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (543.337 KB) | DOI: 10.35889/progresif.v17i2.646

Abstract

AbstrackThe COVID-19 pandemic has a profound impact on many aspects of people's lives. Various ways are being sought to help resolve the spread of COVID 19. The addition of new symptoms that have continued to vary from the beginning to the present has made the public more and more anxious. The symptoms that are felt are usually difficult for the general public to self-diagnose, making it difficult for the public to take preventive action. This paper presents a Web-based expert system model to diagnose Covid-19 early using the Case Based Reasoning Method to help the public diagnose Covid 19 early. Application testing is carried out by comparing the diagnostic results of expert system applications with expert opinions. The test results on 6 sample cases show that the application can diagnose all cases according to expert opinion.Keywords: Expert System, COVID-19, Case Based ReasoningAbstrakPandemi COVID-19 menimbulkan dampak bagi banyak sendi kehidupan kemasyarakat. Berbagai cara diupayakan untuk membantu menyelesaikan penyebaran COVID 19. Bertambahnya gejala-gejala baru yang terus bervariasi sejak awal hingga saat ini membuat masyarakat semakin was-was. Gejala-gejala yang dirasakan biasanya sulit untuk didiagnosa sendiri oleh masyarakat awam, sehingga sulit bagi masyarakat melakukan tindakan pencegahan. Paper ini menyajikan model sistem pakar berbasis Web untuk mendiagnosa secara dini Covid-19 menggunakan Metode Case Based Reasoning untuk membantu masyarakat mendiagnosa dini Covid 19. Pengujian aplikasi dilakukan dengan membandingkan hasil diagnosa aplikasi sistem pakar dengan pendapat pakar. Hasil uji terhadap 6 sampel kasus menunjukkan aplikasi dapat mendignosa keseluruhan kasus sesuai pedapat pakar.Kata kunci: Sistem Pakar, COVID-19, Case Based Reasoning
Implementasi K-Means Dalam Pengelompokan Penyebaran COVID-19 di Jawa Barat Muhammad Wildan Goni; Dudih Gustian; Falentino Sembiring
Progresif: Jurnal Ilmiah Komputer Vol 17, No 2: Agustus 2021
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.46 KB) | DOI: 10.35889/progresif.v17i2.648

Abstract

AbstractConfirmed cases of the COVID-19 virus that are still unstable, as well as the comparison of total confirmed and total recoveries are quite far, which if not treated quickly will cause the number of people exposed to be increasing. This article aims to test the K-Means algorithm in grouping the spread of Covid-19 in West Java. The grouping was carried out based on confirmed parameters, isolated/under treatment, completed isolation/recovered and died from each area in West Java Province. K-means performs clustering in 3 clusters, namely the high distribution cluster (C1), the moderately distributed cluster (C2) and the lightly distributed cluster (C3). Based on the results of system analysis and testing, there are 2 regions in the high distribution cluster (C1), 6 regions for the medium distribution cluster (C2), and 19 regions for the low distribution cluster (C3).Keywords: Spread of COVID-19, K-Means Algorithm, Grouping AbstrakKasus terkonfirmasi virus COVID-19 yang masih belum stabil, serta perbandingan total terkonfirmasi dan total sembuh cukup jauh, dimana jika tidak segera ditangani dengan cepat akan menyebabkan jumlah orang yang terpapar menjadi semakin banyak. Artikel ini bertujuan untuk menguji algoritma K-Means dalam pengelompokan penyebaran Covid-19 di Jawa Barat. Pengelompokkan dilakukan berdasarkan parameter terkonfirmasi, isolasi/dalam perawatan, selesai isolasi/sembuh dan meninggal dari masing-masing daerah yang ada di Provinsi Jawa barat. K-means melakukan klasterisasi dalam 3 cluster yaitu cluster penyebaran tinggi (C1), cluster penyebaran sedang (C2) dan cluster penyebaran ringan (C3). Berdasarkan hasil analisis dan pengujian sistem, daerah yang masuk ke cluster penyebaran tinggi (C1) sebanyak 2 daerah, untuk cluster penyebaran sedang (C2) sebanyak 6 daerah, dan cluster penyebaran rendah (C3) sebanyak 19 daerah.Kata kunci: Penyebaran COVID-19, Algoritma K-Means, Pengelompokan
Co-Authors A. Oktian Permana Aan Setiawan Aan Setiawati Aang Hasanudin Acep Saepulrohman Ade Bahrum Adhitia Erfina Aditya Nurfitri Agraeni, Rosalia Agum Taufikurrahman Ahmadi, Muhammad Iqbal Ainaya, Regina Alamsyah, Zaenal Alfaudzan, Adriansyah Muhamad Alia Ahadi Argasah Alun Sujada Ammar Ammar Anak Agung Gede Sugianthara Anang Suryana Anggy Pradiftha Junfithrana Anita Rahayu Annisa Desi Pratiwi Anti Aprianti Arti Hariyanti Ati Sulastri Atika Fauzia Akbari Azkia Aura Shanda Cecep Warman Debby Rahmawati Debby Rahmawaty Dede Irwan Dede Sukmawan Dede Wahidin Dewa Saepurrahman Dewi Destinasari Dharma Saputra Dhea Lestari Dicki Nugraha Dzikril, Tubagus Edwinanto Ekky Noor Mahmudi Elsa Ramadanti Elsa Yulia Rahman Eneng Mia Rizkianti Enti Sulastri falentino sembiring Faridatun Ni’mah Faturrohman Al-Ghozi Fatwa Adib Soetedjo Fauzi Yuni Hastuti Fauziah Nur Octafiani Fuji Apriani Goni, Muhammad Wildan Harry Atmami Heri Firmansyah Imam Faisal Arridzwani Indra Supriadi Indra Yustiana Indriyani Indriyani Ismi Nurhadianti Rusmana Jannah, Gina Raodotul Jelita Asian Jihad Hari Jordan Chan William Kartika, Mila Kirishchieva Irina Rafaelevna Kudin Rustaman LESTARI, BUNGA Lucas Crammer M Dezan Sya’ban S M. Syukron Nawawi M. Yosef Ismatulloh Marina Marina Artiyasa Marina Artiyasa Maryam Nurhasanah Mega Lumbia Sinaga Megasari Putri Meisa Sindriama Rinelda Mia Kurniasari Mochamad Khilmi Mohamad Najib Muahamad Taufik Muhamad Amar Muhamad Renaldi Aripin Muhamad Rivqi Nurridwan Muhamad Salman Al-Farits Muhamad Zaenal Abidin Muhamad Zidane Mustofa Muhamd Ammar Muhammad Alman Firdaus Muhammad Ammar Muhammad Arip Muhammad Arsyad Muhammad Fachreza Faturrahman Muhammad Iqbal Ahmadi Muhammad Natsir Muhammad Wildan Goni Muslih, Muhamad Neng Mira Indri Anggraeni Neng Resti Noviansyah Nunik Destria Arianti Nur Apriyanti Nur Apriyanti Nur Fauza Muhidin Nuraeni Nursyi’ah, Sitiyana Pahmi, Samsul Paikun Panji Narputro Rahayu Awaliyah Rian Nugraha Rico Sihotang Rifaldi Zulkarnaen Rimalya Widian Rinrin Rinrin Rintho Rante_Rerung Rival Maulana Rosita, Moneyta Dholah RR. Ella Evrita Hestiandari Rudi Heryanto Saepudin, Sudin Salsa Lisna Audina Sarah Sifa Antadipura Sastradipraja, C K Satish Kumar Damodar Seko Lesmana Selsa Khairunisa Fadiya haya Sholihat, Anisa Sihabudin Sihabudin Sihabudin Siti Handayani Siti Hasna Fadhilah Siti Khalifah Siti Mulia Agustina Siti Olis Somantri Somantri Sri Rejeki, Nada Suratno, Erip Taufik Bahrul Alam Wildan Riswandi Wulan Alinda Wahyumi Yayatillah Rubiati Yoga Vikriansyah Yudi Nata Yudi Nata Yunita Gusti Nurani Yusuf Iskandar Zaid Sulaiman