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All Journal Jurnal Sains Informatika Terapan (JSIT) Innovative: Journal Of Social Science Research
Lusinia, Shary Armonitha
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Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Public Health Other

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Optimalisasi Human Resource Management Dengan Metode AHP Untuk Pemberian Bonus Karyawan PT. Talang Gugun Sari Nusantara Yuliandri, Mario; Muhammad, Abulwafa; Lusinia, Shary Armonitha
Jurnal Sains Informatika Terapan Vol. 4 No. 1 (2025): Jurnal Sains Informatika Terapan (Februari, 2025)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v4i1.440

Abstract

PT Talang Gugun Sari Nusantara already has dozens of employees in each branch, each employee has various criteria in every job. Therefore, PT Talang Gugun Sari Nusantara has a way to improve the performance of every employee. By giving bonuses to employees who do their work well and in accordance with the Company's wishes. PT Talang Gugun Sari Nusantara previously conducted an assessment in a manual way that made its assessment irrelevant to the circumstances that occurred. With this problem, the company needs a Decision Selection System using the Analysis Hierarchy Process method to assess employees with several criteria such as attendance, sales of each employee, responsibility, and manners. The research conducted aims to build a software on "Optimizing Human Resource Management by Determining the Provision of Bonuses to Employees of Pt. Talang Gugun Sari Nusantara Using the Analytical Hierarchy Process (AHP) Method". In this study, a case was raised, namely looking for the best alternative based on the criteria that had been determined by using. This method was chosen because it was able to select the best alternative from 4 criteria. In this case, the intended alternative is those who are entitled to receive employee bonuses based on the specified criteria. This research was carried out by finding the value weight of each attribute and then a ranking process was carried out that would determine the optimal alternative, namely employees receiving bonuses.
Analisa Prediksi Penyakit Diabetes Menggunakan Metode Naive Bayes dan K-NN Rahmansyah, Nugraha; Lusinia, Shary Armonitha; Ilmawati, Ilmawati
Innovative: Journal Of Social Science Research Vol. 5 No. 1 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i1.17737

Abstract

Diabetes mellitus adalah salah satu penyakit kronis yang semakin umum di dunia termasuk di Indonesia. Mendeteksi penyakit ini sejak dini sangatlah penting untuk mencegah munculnya komplikasi serius. Penelitian ini dilakukan untuk menganalisis prediksi penyakit diabetes menggunakan dua metode pembelajaran mesin, yaitu Naïve Bayes dan K-Nearest Neighbor (KNN). Naïve Bayes dikenal sebagai metode klasifikasi yang sederhana namun efektif berdasarkan probabilitas, sementara KNN merupakan metode klasifikasi berbasis instance yang menggunakan kedekatan data dengan data yang sudah ada. Dataset yang digunakan mencakup 8 atribut kesehatan, seperti usia, jenis kelamin, hipertensi, penyakit jantung, riwayat merokok, BMI, kadar HbA1c, dan kadar glukosa darah, dengan label target berupa status diabetes (1 untuk diabetes, 0 untuk non-diabetes). Tahapan tersebut mencakup pengolahan awal data, seperti mengisi nilai kosong, menormalisasi atribut numerik, dan mengkode atribut kategori. Naïve Bayes memanfaatkan distribusi probabilitas, sedangkan KNN mengelompokkan data berdasarkan jarak ke tetangga terdekat. KNN lebih baik digunakan untuk dataset dengan pola yang rumit, sementara Naïve Bayes lebih efisien dalam hal komputasi
Co-Authors Arsyah, Ulya Ilhami Devia Kartika Gema, Rima Liana Ilmawati, Ilmawati Muhammad, Abulwafa Permana, Randy Pratiwi, Mutiana Rahmansyah, Nugraha Syam, Vera Arnelis Yuliandri, Mario