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All Journal AJAD : Jurnal Pengabdian kepada Masyarakat Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Fahmi, Hakon
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Humanities Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science

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Implementasi Sistem Penjualan Pada Berbasis Aplikasi Baidowi, Ahmad; Yakob, Galih Satria; Barronzoeputra, Gaoeng Qalbun; Fahmi, Hakon; Sarimole, Frencis Matheos
AJAD : Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/ajad.v4i1.279

Abstract

Businesses today benefit greatly from information technology, especially in creating computer-based applications, websites, and sales information systems. This technology allows for quick and easy sales data management and buy-sell transactions. This system can process sales transaction data efficiently, which allows precise and fast information reports to be generated. By creating an application, Warkuy Cafe, located in Bekasi City, overcomes the problem of manual sales data recap. This system aims to increase the convenience, attractiveness, and efficiency of online services and ordering. These applications include information about sales transactions, delivery messages, booking order systems, and e-wallet payments. Software such as Learning Management System (LMS) and Content Management System (CMS), which help users and administrators edit data, created the applications. This innovation enhances Warkuy Cafe's operations and improves customers' shopping experience.
Implementasi Data Mining Klasifikasi Gejala Penyakit TB Menggunakan Algoritma Naive Bayes pada Studi Kasus Puskesmas Pegangsaan Dua B Fahmi, Hakon; Sutisna
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.970

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. The bacteria can enter the lungs, causing the patient to experience shortness of breath and chronic coughing. The infection process in TB progresses through three main stages: primary infection, latent infection, and active infection. During the primary infection stage, the bacteria enter the lungs through inhaled air. If the immune system successfully controls the bacteria, the infection becomes latent, where the bacteria remain inactive and cause no symptoms. However, if the immune system fails, the infection becomes active, and the bacteria attack healthy lung cells, leading to severe symptoms. Tuberculosis remains a major cause of global morbidity and mortality. According to the 2022 WHO report, Indonesia ranks second in the world with an estimated 969,000 TB cases, or 354 per 100,000 people, and a mortality rate of 144,000, or 52 per 100,000 people. This study aims to improve the accuracy of TB diagnosis through the application of the Naive Bayes algorithm, applied to patient data from the Pegangsaan Dua B Community Health Center. The dataset includes 1,527 training data and 1,029 testing data, covering attributes such as patient name, gender, age, identification number, registration date, address, diagnosis status, and diagnosis results. The results indicate that the Naive Bayes algorithm achieved an accuracy of 99.71%, showing its potential for early and accurate TB diagnosis prediction.
Co-Authors Ahmad Baidowi Barronzoeputra, Gaoeng Qalbun Sarimole, Frencis Matheos Sutisna Yakob, Galih Satria