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All Journal Journal Of Informatics And Busisnes Jurnal Ilmu Komunikasi dan Sosial Politik Jurnal Intelek Dan Cendikiawan Nusantara
Dwi Saputra
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Computer Science & IT Economics, Econometrics & Finance Environmental Science Library & Information Science Other

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Perubahan Model Bisnis Media Massa Dalam Era Digital: Dampaknya Terhadap Kualitas Jurnalisme Modern Di Sumatera Ekspres Dwi Saputra; Sumaina Duku; Jufrizal, Jufrizal
Jurnal Ilmu Komunikasi Dan Sosial Politik Vol. 2 No. 4 (2025): April - Juni
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62379/jiksp.v2i4.2866

Abstract

The development of communication and information technology has threatened the print media industry. The most obvious threat is the reduction in print media readers who have switched to online media. Therefore, changes are needed to maintain the current print media industry, one of which is through media convergence. This study aims to determine how changes in the mass media business model in the digital era affect the quality of modern journalism at Sumatera Ekspres and the journalistic convergence model applied in the process towards media change carried out by Sumatera Ekspres. In this study, the researcher used qualitative research methods and a case study approach. The results of the study show that Sumatera Ekspres carried out a media convergence transformation by changing news platforms, improving quality, and utilizing social media. Sumatera Ekspres uses the journalistic convergence model according to Grant, namely newsroom convergence, newsgathering convergence and content convergence. In its application, Sumatera Ekspres has carried out newsroom convergence to the maximum because it uses rooms that have been combined in producing news on each platform. Newsgathering convergence where in this model reporters are required to be able to work multitasking and content convergence is a convergence model that provides content in multimedia form with a combination of images, videos, writing, andpodcasts.
PERAN DEMOKRASI, POPULASI, INDEKS PEMBANGUNAN MANUSIA, DALAM MENDORONG PERTUMBUHAN EKONOMI PROVINSI LAMPUNG Winda Novitriyani; Dwi Saputra; Popya Siska; Anas Malik
Jurnal Intelek Dan Cendikiawan Nusantara Vol. 1 No. 6 (2024): Desember 2024 - Januari 2025
Publisher : PT. Intelek Cendikiawan Nusantara

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Abstract

Penelitian ini mengkaji peran demokrasi, populasi, dan Indeks Pembangunan Manusia (IPM) dalam mendorong pertumbuhan ekonomi di Provinsi Lampung. Pertumbuhan ekonomi adalah proses dinamis yang mencerminkan kemampuan suatu daerah untuk menyediakan barang dan jasa bagi penduduknya. Penelitian ini menggunakan data sekunder dari tahun 2018 hingga 2023, dengan menerapkan model data panel dan analisis regresi linier untuk menilai dampak faktor-faktor tersebut terhadap pertumbuhan ekonomi. Temuan menunjukkan bahwa pertumbuhan populasi berpengaruh positif terhadap pertumbuhan ekonomi dengan memperluas pasar untuk barang dan jasa, sementara IPM yang lebih tinggi dapat berdampak negatif terhadap pertumbuhan ekonomi. Selain itu, studi ini mengungkapkan bahwa demokrasi tidak memiliki pengaruh signifikan terhadap pertumbuhan ekonomi di Lampung. Hasil ini menunjukkan bahwa strategi pembangunan ekonomi harus fokus pada keseimbangan antara pertumbuhan populasi dan peningkatan pembangunan manusia untuk mencapai pertumbuhan ekonomi yang berkelanjutan.
Penerapan Algoritma C4.5 Dalam Klasifikasi Penyakit Diabetes Menggunakan Dataset Pima Indians Fakhri Hamdani; Muhammad Ari Shidqi; Arip Rahman; Piero Ariessandy; Dwi Saputra; Gregorius Waek; Maria Oktaviani
Journal Of Informatics And Busisnes Vol. 3 No. 4 (2026): Januari - Maret
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i4.4039

Abstract

The increasing number of diabetes mellitus sufferers makes early identification a crucial step to reduce the risk of complications. Utilizing health data through a data mining-based approach offers opportunities to assist in more systematic disease analysis and classification. This research focuses on the application of the Decision Tree C4.5 algorithm to classify diabetes using the Pima Indians Diabetes dataset. The data used consisted of 768 female patients with eight medical attributes related to health conditions, such as glucose levels, body mass index, blood pressure, age, and number of pregnancies. The research process included data processing, model development, and evaluation of the classification results using the CRISP-DM workflow. The results showed that the classification model built using the C4.5 algorithm achieved an accuracy of 77.04%. The resulting decision tree structure demonstrated that the glucose level attribute played a dominant role in determining the classification results. These findings demonstrate that the Decision Tree C4.5 algorithm can be utilized as a fairly effective approach to assist in the initial classification of diabetes based on medical data.
Co-Authors Anas Malik Arip Rahman Fakhri Hamdani Gregorius Waek Jufrizal Jufrizal MARIA OKTAVIANI Muhammad Ari Shidqi Piero Ariessandy Popya Siska Sumaina Duku Winda Novitriyani