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All Journal IJISTECH (International Journal Of Information System & Technology) JIIP (Jurnal Ilmiah Ilmu Pendidikan) IJISTECH
Firmansyah, Moch
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

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Dakwah “Pemuda Tersesat: Gaya Bahasa Dakwah Habib Ja’far Al Hadar” Firmansyah, Moch; Nasvian, Moch Fuad
JIIP - Jurnal Ilmiah Ilmu Pendidikan Vol. 5 No. 5 (2022): JIIP (Jurnal Ilmiah Ilmu Pendidikan)
Publisher : STKIP Yapis Dompu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (685.095 KB) | DOI: 10.54371/jiip.v5i5.599

Abstract

Tantangan berdakwah dalam era Covid 19 sangatlah berat, larangan untuk berkerumun, dan berjabat tangan merupakan faktor yang mengahuruskan da’i untuk berdakwah menggunakan platform digital. Pemanfaatan teknologi informasi menghapus hambatan ruang dan waktu sehingga teknologi informasi sebagai sarana untuk berdakwah yang mengharuskan da’i untuk memutar otak agar mad’u tetap menerima pesan dakwah dengan segala kekurangannya. Gaya Bahasa konten dakwah yang mengikuti generasi millenial yang dilakukan oleh Habib Ja’far Al-Hadar ini tentunya butuh diuji penerimaannya dari berbagai sudut pandang audience, termasuk dari sudut pandang Ustadz dan Ustadzah yang berasal dari generasi milenial. Ustadz dan ustadzah bagi santri tidak hanya menyampaikan ilmu tapi juga memberikan standar akhlak sehingga jika ustadz memiliki keluasan pengetahuan dan akhlak hal ini juga akan memberikan standar tersebut kepada para santrinya. Peneliti menggunakan metode penelitian kualitatif deskriptif dengan menggunakan pendekatan analisis resepsi model encoding dan decoding dari Stuart Hall. Kemenarikan gaya komunikasi dakwah Husein Ja’far dapat diamati baik dari pesan-pesan dakwahnya yang kebanyakan disampaikan secara tegas namun tetap dengan penyampaian dakwah yang tepat sasaran dibarengi humor khas “Pemuda Tersesat”. Pandemi Covid-19 masih belum ada tanda-tanda segera berakhir sehingga informan beranggapan dakwah menggunakan media youtube merupakan trobosan baru dan efekti untuk menjalankan dakwah agar aktivitas dakwah tidak boleh berhenti.
Improve Accuracy in The Process of Diagnosing Various Types of Lung Diseases by Using The Naïve Bayes Classifier Firmansyah, Moch
IJISTECH (International Journal of Information System and Technology) Vol 7, No 2 (2023): The August edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i2.305

Abstract

In the humans’ body, there are several organs that function to support humans’ life, one of these organs is lungs, in its development, many things happen to these organs, for examples, infected by various diseases, including the lungs. There are many types of diseases that can infect the lungs including Asthma, Dyspnea, Tuberculosis, COPD, Pneumonia, Bronchitis, Hemoptysis, Hemoptoe, and these diseases can be diagnosed based on the symptoms, but unfortunately there are difficulties in the classification process, because it has similar symptoms experienced by people with the disease. The purpose of this study is to be able to classify lung disease based on symptoms experienced using the navies bayes classification method. This method doesn’t use much training data in determining the estimated parameters used in the classification process. This is what makes researchers use this method. This study used patient medical records as many as 200 patient data. Data collection is carried out from February to May. Data testing using rapid miner tools resulted in 90.22% accuracy for lung disease diagnosis.
Improve Accuracy in The Process of Diagnosing Various Types of Lung Diseases by Using The Naïve Bayes Classifier Firmansyah, Moch
IJISTECH (International Journal of Information System and Technology) Vol 7, No 2 (2023): The August edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i2.305

Abstract

In the humans’ body, there are several organs that function to support humans’ life, one of these organs is lungs, in its development, many things happen to these organs, for examples, infected by various diseases, including the lungs. There are many types of diseases that can infect the lungs including Asthma, Dyspnea, Tuberculosis, COPD, Pneumonia, Bronchitis, Hemoptysis, Hemoptoe, and these diseases can be diagnosed based on the symptoms, but unfortunately there are difficulties in the classification process, because it has similar symptoms experienced by people with the disease. The purpose of this study is to be able to classify lung disease based on symptoms experienced using the navies bayes classification method. This method doesn’t use much training data in determining the estimated parameters used in the classification process. This is what makes researchers use this method. This study used patient medical records as many as 200 patient data. Data collection is carried out from February to May. Data testing using rapid miner tools resulted in 90.22% accuracy for lung disease diagnosis.
Co-Authors Moch Fuad Nasvian