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Vioneka, Ranti
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Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science

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IDENTIFIKASI DATA PENERIMAAN MAHASISWA BARU DI UNIVERSITAS MUHAMMADIYAH BENGKULU Yoga Widianto, Indra; Vioneka, Ranti; Jayusta, Evan; Juhardi, Ujang; Ristontowi
Jurnal Ilmiah Mahasiswa Kuliah Kerja Nyata (JIMAKUKERTA) Vol. 4 No. 1 (2024): JIMAKUKERTA
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Muhammadiyah Bengkulu

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Abstract

Tujuan dari penelitian ini adalah untuk menganalisis data penerimaan mahasiswa baru Universitas Muhammadiyah Bengkulu tahun 2023. Metode analisis data yang digunakan meliputi statistik deskriptif untuk mengetahui jumlah pelamar, jumlah pelamar yang berhasil, serta karakteristik demografi dan akademik siswa yang berhasil. Kami juga melakukan analisis komparatif dengan tahun sebelumnya untuk memahami tren jumlah mahasiswa yang terdaftar di universitas kami. Kegiatan ini dilaksanakan dimulai dari tanggal 1 Februari sampai dengan tanggal 29 Februari 2024. Data yang digunakan dalam penelitian ini berasal dari Bagian Penerimaan Mahasiswa Baru Universitas Muhammadiyah Bengkulu. Analisis tersebut menunjukkan tren pendaftaran, demografi, dan profil akademik mahasiswa baru. Studi ini dapat memberikan wawasan yang berguna bagi para pengambil kebijakan universitas dalam merancang strategi penerimaan mahasiswa baru di masa depan. Kesimpulan dari analisis data menunjukkan bahwa UMB telah efektif menggunakan Teknologi Informasi (TI) dalam proses penerimaan mahasiswa baru, terutama melalui sistem pendaftaran online.
Sistem Pakar Untuk Mendeteksi Gangguan Pencernaan Pada Manusia Vioneka, Ranti; Sunardi, Dandi; Hidayah, Agung Kharisma; Witriyono, Harry
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5771

Abstract

Currently, technology capable of absorbing human thought processes and patterns is known as artificial intelligence. An expert system is a component of artificial intelligence that contains knowledge and experience acquired from an expert in a particular field. The aim of this study is to develop a web-based expert system designed to detect digestive disorders in humans. Its purpose is to provide patients with information about their health status, correlated with their presenting symptoms, with a certain degree of accuracy. Through the use of this expert system, patients have the ability to identify potential digestive disorders based on individual symptoms or combinations of symptoms they may be experiencing. Additionally, it facilitates early detection of digestive disorders without the need to delay treatment until doctors or specialists are available. The method used is Forward Chaining, which involves collecting symptom data to determine the appropriate type of disease. Forward Chaining is a reasoning technique used in expert systems and rule-based systems. It begins with known events or conditions and then attempts to match these events with the IF (combination) clauses from the IF-THEN rules that are available.
Co-Authors Dandi Sunardi hidayah, agung kharisma Jayusta, Evan Juhardi, Ujang Ristontowi Witriyono, Harry Yoga Widianto, Indra