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All Journal JUSIM (Jurnal Sistem Informasi Musirawas) Sriwijaya Journal of Informatics and Applications
Nabila Rizky Oktadini
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Computer Science & IT Decision Sciences, Operations Research & Management

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PERBANDINGAN METODE WEIGHTED PRODUCT DAN PROFILE MATCHING DALAM PROMOSI JABATAN KARYAWAN PT.XYZ Allsela Meiriza; Pacu Putra; Putri Eka Sevtyuni; Rani Mardiah; Riska Yunita; Gusti Barata; Apriansyah Putra; Ari Wedhasmara; Nabila Rizky Oktadini
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 7 No 2 (2022): JUSIM (Jurnal Sistem Informasi Musirawas) DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v7i2.1720

Abstract

Promosi jabatan merupakan suatu yang penting bagi jenjang karir seorang karyawan. Dengan mendapatkan promosi, maka karyawan tersebut dapat mengembangkan karirnya dari posisi sebelumnya. Saat ini PT. XYZ belum mempunyai metode pendukung keputusan yang tepat dalam penentuan promosi jabatan karyawan, sehingga menghasilkan keputusan subjektif, oleh sebab itu, penelitian ini bertujuan membantu PT. XYZ dalam menemukan metode pendukung keputusan yang tepat agar diperoleh keputusan yang objektif dengan melakukan perbandingan. Adapun metode yang dibandingkan yaitu metode weighted product dan profile matching. Pengujian menggunakan pendekatan confusion matrix. Hasilnya metode weighted product memiliki nilai lebih tinggi dari metode profile matching dalam tingkat akurasi 95%, presisi 100%, dan recall 75%.
Fuzzy Time Series Optimization using Particle Swarm Optimization for Forecasting the Number of Fresh Fruit Bunches (FBB) of Palm Oil Aisyah Filza Aliyah; Alvi Syahrini Utami; Nabila Rizky Oktadini
Sriwijaya Journal of Informatics and Applications Vol 2, No 2 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v2i2.21

Abstract

Palm oil is a reliable vegetable oil producer because the oil produced has advantages than oils from other plants. The amount of Fresh Fruit Bunches (FFB) raw material from Palm oil has a significant impact on the palm oil production process. Therefore, we need a method to forecasting the amount of palm oil (FFB). One of the suitable forecasting methods is fuzzy time series (FTS). However, FTS still has shortcomings such as innacurate determination of the interval length. For this reason, we need to optimize FTS interval to get optimal forecasting. This research implements Particle Swarm Optimization as the optimization method, FTS Chen-Hsu as the forecast method, and Mean Absolute Percentage Error (MAPE) as the measurement of error. The optimization result using PSO produce an error value of 2.0262% smaller than FTS 3.7108%.
Co-Authors Aisyah Filza Aliyah Allsela Meiriza, Allsela Alvi Syahrini Utami Apriansyah Putra Ari Wedhasmara Gusti Barata Pacu Putra Putri Eka Sevtyuni Rani Mardiah Riska Yunita