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All Journal Jurnal Riset Informatika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi)
Fajaryanti, Julia
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Transportation

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IMPLEMENTASI METODE NAÏVE BAYESPADA SPK UNTUK MEMPREDIKSI POLA KELULUSAN MAHASISWA PERGURUAN TINGGI SWASTA Rogayah, Rogayah; Fajaryanti, Julia; Banowosari, Lintang Yuniar
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 1 No. 1 (2017): PROSIDING SEMNAS INOTEK Ke-I Tahun 2017
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v1i1.418

Abstract

Mahasiswa adalah aspek penting dalam evaluasi keberhasilan penyelenggaraan program studi pada suatu perguruan tinggi. Dalam melakukan pengambilan keputusan yang dilakukan oleh kepala program studi dibutuhkan data mahasiswa dan data jumlah kelulusan . Untuk meningkatkan pelayanan dan kinerja program studi objek penelitian dalam pengambilan keputusan dan kebijakan bagi mahasiswa dibutuhkan sistem yang dapat membantu dalam proses pengolahan data mahasiswa. Dalam mengolah data, dibutuhkan basis data akademik mahasiswa pada program studi yang terjadi dalam kurun waktu empat (4) tahun. Penggunaan data mahasiswa bertujuan untuk membangun sebuah sistem penunjang keputusan yang dapat menghasilkan klasifikasi atau pola-pola mahasiswa yang lulus tepat waktu berdasarkan hasil penambangan data menggunakan metode Naïve Bayes. Metode penelitian yang digunakan meliputi pembahasan tempat, waktu dan jadwal penelitian, alat dan bahan penelitian, metodologi penelitian, jenis data, dan teknik pengumpulan dan analisis data. Hasil penelitian ini adalah pola kelulusan mahasiswa sesuai pola yang dihasilkan oleh metode Naïve Bayes sehingga membantu program studi objek penelitian untuk melakukan langkah-langkah tepat bagi mahasiswa yang termasuk ke dalam mahasiswa tidak dapat lulus tepat waktu.
EXPERT SYSTEM DEVELOPMENT TO IDENTIFY EMPLOYEE PERSONALITY TYPES USING DEMPSTER SHAFER THEORY Fajaryanti, Julia; Rogayah, Rogayah
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (798.414 KB) | DOI: 10.34288/jri.v4i3.162

Abstract

Human resources are an essential asset for the company to develop and realize the company's goals. One of the efforts to optimize the capacity of employees is to know their personality. Personality is the form an individual possesses in behaving and all the characteristics that distinguish one individual from another. Understanding employees' personality is essential for the company and the employees themselves. Because by knowing a person's personality, the company can maximize the potential of employees and place certain positions that suit the employee's personality. This study aims to implement the dempster-Shafer theory on an inference engine in building an expert system to identify employee personality types. Dempster-Shafer's approach can perform probability calculations so that evidence can be carried out based on confidence and logical reasoning. The system developed can identify the employee's personality type through the nature or symptoms that exist in the employee. In addition, the system can display the diagnosis results with an explanation of the personality type, its character in work and occupations or positions suitable for that personality type. Based on the results of the accuracy-test obtained from the comparison of expert system diagnoses with the analysis of an expert, the accuracy value reaches 85%.
Co-Authors Lintang Yuniar Banowosari Rogayah, Rogayah