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All Journal Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jurnal Informatika Ekonomi Bisnis Insearch: Information System Research Journal J-Icon : Jurnal Komputer dan Informatika Jurnal Informatika Ekonomi Bisnis
Nova Hayati
Universitas Putra Indonesia YPTK Padang
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Mathematics Physics Social Sciences Other

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Optimalisasi Prediksi Penjualan Produk Herbal Menggunakan Metode Monte Carlo dalam Meningkatkan Transaksi Nova Hayati
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 4 (2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.355 KB) | DOI: 10.37034/infeb.v2i4.54

Abstract

Herbs are a product that is in great demand by the public. With so many enthusiasts of herbal products, there is a need for product availability to increase sales transactions for these products. To increase sales transactions for these products, one process that can be done is to predict the sales of herbal products, with data used from January 2018 to December 2019 at the An Nabawi herbal shop. The prediction process is carried out using the Monte Carlo method and to simplify the prediction process a web-based system with the PHP programming language is implemented to make it easier. With the Monte Carlo method used in this study to predict sales of herbal products so that the leadership can use it to make decisions on the availability of herbal products in the shop. The sales prediction results obtained from the Monte Carlo simulation process with an accuracy rate of 87.91%. In this way, the Monte Carlo method can be applied to predict the future sales of herbal products and can be used by store leaders to make decisions regarding the availability of herbal products.
Sistem Informasi Pengenalan dan Pendaftaran Santri Berbasis Website pada LKP Tar-Q Padang Nova Hayati
Insearch: Information System Research Journal Vol 2, No 02 (2022): Insearch (Information System Research) Journal
Publisher : Fakultas Sains dan Teknologi UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/isrj.v2i02.4417

Abstract

Sistem yang telah dijalankan pada LKP Tar-Q Padang masih menggunakan proses manual dalam pendaftaran dan pengelolaan data yang masih belum rapi. Sehingga memepersulit dalam proses penyimpanan data serta arsip santri dan pengajar secara keseluruhan. Untuk proses pembuatan laporan pendaftaran  santri baru  membutuhkan waktu yang lama dengan menggunakan data manual. Dengan hal itu website LKP Tar-Q Padang ini bertujuan untuk membantu dan memudahkan LKP Tar-Q dalam proses pengenalan dan pendaftaran serta proses seleksi dan pengolahan data santri dan pengajar di LKP Tar-Q Padang. Metode yang digunakan dalam proses seleksi yaitu SAW ( Simple Addtive Weight ). Alat bantu perancangan yang digunakan untuk pembuatan sistem ini adalah UML (Unified Modeling Language), dengan menggunakan software astah, bahasa pemrograman yang digunakan yaitu PHP serta database MySQL dan dengan server Mowes portable II. Berdasarkan uraian di atas, akan dirancang sebuah sistem berbabis website untuk pengenalan dan pendaftaran serta seleksi pada LKP Tar-Q Padang sehingga dapat mempermudah LKP dalam proses kinerja.
Optimalisasi Prediksi Penjualan Produk Herbal Menggunakan Metode Monte Carlo dalam Meningkatkan Transaksi Nova Hayati
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 4 (2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.355 KB) | DOI: 10.37034/infeb.v2i4.54

Abstract

Herbs are a product that is in great demand by the public. With so many enthusiasts of herbal products, there is a need for product availability to increase sales transactions for these products. To increase sales transactions for these products, one process that can be done is to predict the sales of herbal products, with data used from January 2018 to December 2019 at the An Nabawi herbal shop. The prediction process is carried out using the Monte Carlo method and to simplify the prediction process a web-based system with the PHP programming language is implemented to make it easier. With the Monte Carlo method used in this study to predict sales of herbal products so that the leadership can use it to make decisions on the availability of herbal products in the shop. The sales prediction results obtained from the Monte Carlo simulation process with an accuracy rate of 87.91%. In this way, the Monte Carlo method can be applied to predict the future sales of herbal products and can be used by store leaders to make decisions regarding the availability of herbal products.
The Prediction of The Drought Index in The Indragiri Watershed Using SARIMA and SPI Methods Widdya Rahmalina; Asrina Mulyati; Nova Hayati; Widya; Novreta Ersyi Darfia
Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Vol. 20 No. 1 (2023): Sainmatika : Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/sainmatika.v20i1.11501

Abstract

Farmers are concerned about the problem of drought in agriculture because it will disrupt the production system and cause losses. In 2015, the Indragiri Hulu area experienced a drought on 273 hectares of agricultural land. This area is part of the Indragiri River Watershed in Riau Province. To prevent the impact of future droughts, forecasting is required. The level of drought is influenced by rainfall, so the Seasonal Auto Regressive Integrated Moving Average (SARIMA) method is used to model rainfall data. In addition, the Standardized Precipitation Index (SPI) is also used to analyze the drought index. After the analysis, it was found that the best model in forecasting is SARIMA model (1,0,1)(2,1,1)12 with an average residual square of 18.0175, and the drought index in the Indragiri watershed is currently included in the  "Normal" category. The results of this forecasting are expected to assist the Riau Province National Disaster Management Agency in anticipating and mitigating the impact of future drought disasters.
The Prediction of The Drought Index in The Indragiri Watershed Using SARIMA and SPI Methods Widdya Rahmalina; Asrina Mulyati; Nova Hayati; Widya; Novreta Ersyi Darfia
Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Vol. 20 No. 1 (2023): Sainmatika : Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/sainmatika.v20i1.11501

Abstract

Farmers are concerned about the problem of drought in agriculture because it will disrupt the production system and cause losses. In 2015, the Indragiri Hulu area experienced a drought on 273 hectares of agricultural land. This area is part of the Indragiri River Watershed in Riau Province. To prevent the impact of future droughts, forecasting is required. The level of drought is influenced by rainfall, so the Seasonal Auto Regressive Integrated Moving Average (SARIMA) method is used to model rainfall data. In addition, the Standardized Precipitation Index (SPI) is also used to analyze the drought index. After the analysis, it was found that the best model in forecasting is SARIMA model (1,0,1)(2,1,1)12 with an average residual square of 18.0175, and the drought index in the Indragiri watershed is currently included in the  "Normal" category. The results of this forecasting are expected to assist the Riau Province National Disaster Management Agency in anticipating and mitigating the impact of future drought disasters.
SISTEM PENUNJANG DALAM PENGAMBILAN KEPUTUSAN PEMBERIAN REWARD DOSEN TERBAIK MENGGUNAKAN METODE TOPSIS Nova Hayati; Aldo Eko Syaputra; Yofhanda Septi Eirlangga
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.12390

Abstract

Lecturers are professional teaching staff who provide all their knowledge and loyalty through teaching students, research and community service. To increase the performance and loyalty of lecturers to tertiary institutions, this is done by giving rewards to the best lecturers. In making the decision to give rewards to lecturers, there are several steps and criteria that must be met, because the large number of lecturers and criteria causes the assessment team to experience difficulties in processing the criteria data and lecturer data who are entitled to the reward, so a method is needed that is implemented into a computerized system that will facilitate the work of the assessment team in data processing and the resulting data to be accurate and reliable. The data applied in this research is data from permanent university lecturers and the conditions set by the university. The purpose of this research is to maximize the performance of the assessment team in processing criteria data and university permanent lecturers to get the best lecturers who are entitled to receive rewards using the TOPSIS method. The decision in determining the alternative to giving rewards to the best lecturers, by selecting 3 lecturers as recipients of the best lecturer rewards as an alternative is the result of this study. From these results, there are influential criteria, namely Research, Teaching, and Attendance.
Co-Authors Aldo Eko Syaputra Asrina Mulyati Novreta Ersyi Darfia Widya Widya Yofhanda Septi Eirlangga