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All Journal Jurnas Nasional Teknologi dan Sistem Informasi Faktor Exacta Kilat STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal PkM (Pengabdian kepada Masyarakat) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Kapas: Kumpulan Artikel Pengabdian Masyarakat
Yulianingsih Yulianingsih
Universitas Indraprasta PGRI
Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Journal : Faktor Exacta

 1 
Pengembangan Model RNN untuk Prediksi Produksi Daging Sapi dalam Perencanaan Pembangunan Nasional Yulianingsih Yulianingsih; Tri Yani Akhirina; Za’imatun Niswati
Faktor Exacta Vol 15, No 3 (2022)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v15i3.12820

Abstract

Data is an important component because it will support in policies / decisions making, serve as control tools to prevent error from occuring and support transparent, accountable and participative governance. This study examines the prediction of beef production and product consumption with the Long Short Term Memory (RNN LSTM) Recurrent Neural Network approach. Using statistical data on beef production and consumption of products per capita per week from BPS. The data used were 12 records for each data source. LSTM contains information outside the normal flow of recurrent network in the gate cell. Cell makes decisions about what should be stored and when to permit reading, writing and deletion, through open and closed gates. The gate conveys information based on the strength that enters into it and will be filtered to be the weight of the gate itself. These weights are the same as the input and hidden unit weights that are adjusted through learning process on the recurrent network. The results of research carried out by building prediction models of beef production and product consumption get the best results using data for 3 years with RMSE 32121.297 for beef production and 0.001 for product consumption.
Implementasi Metode Simple Additive Weighting Pada Perancangan Sistem Penilaian Reseller di Showroom Aska Motor Garage Ananda, Rizki; Yulianingsih, Yulianingsih; Megiati, Yunita Endra
Faktor Exacta Vol 17, No 2 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i2.20768

Abstract

Aska Motor Garage Showroom is a company engaged in motorcycle sales. As a sales-oriented business, Aska Motor Garage needs a strategy to boost its sales. One of the strategies that can be implemented is by establishing partnerships with resellers through the provision of rewards in the form of incentives. Therefore, there is a need for an objective and measurable assessment system. The Simple Additive Weighting method is one of the techniques used to determine the best value based on criteria and weights that can be customized according to the partners' needs, and it is considered quite appropriate for use in this research. The result of this system design is a decision support system that provides information about the assessment of the top resellers, using four supporting criteria, including monthly sales, innovation, work quality, and adherence to target pricing.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN BONUS KARYAWAN PADA PT GAHAKA KARYA PRIMA MENGGUNAKAN METODE SAW Subekti, Aditya Rindang; Yulianingsih, Yulianingsih; Prasetya, Rudi
Faktor Exacta Vol 17, No 4 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i4.25117

Abstract

Implementasi Sistem Klasifikasi Inventaris Menggunakan Metode Clustering dengan Algoritma K-Means untuk Pengelolaan Stok Barang di D'Cafe Indramayu Dhona, Dina Rima; Yulianingsih, Yulianingsih; Saputra, Suranto
Faktor Exacta Vol 18, No 2 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i2.25182

Abstract

One effective marketing strategy to attract consumer interest is the implementation of a "buy one get one free" promotional program on select products. However, this strategy necessitates sustainable inventory availability and must be aligned with the marketing unit's objectives. This research applies the K-Means algorithm to classify products based on price parameters and stock availability levels. The analysis results reveal the formation of three primary clusters: (1) products within the low to medium price range, (2) products within the medium to high price range, and (3) products in the highest price category. This clustering is based on the proximity of each product to its cluster centroid, accompanied by quantitative information regarding the number of products within each cluster. The output from this analysis is implemented through an application developed using the Java programming language. This application is designed to be utilized by the marketing unit in formulating and optimizing sales strategies to increase sales volume and enhance inventory management effectiveness.
Co-Authors Ade Angga Saputra Agung Prastiwa Hadi Samudra Arief Kurniawan Awis Razata Bayu Jaya Tama Berta Dian Theodora, Berta Dian Dhona, Dina Rima Forkas Tiroy Santos Butarbutar Indah Suciati Megiati, Yunita Endra Mutia, Intan Ninda Yulyanti Pandhu Pramarta Rifki Romadhoni Rizki Ananda Rudi Prasetya Saputra Dwi Nurcahya Saputra, Suranto Soepardi Harris Sri Melati Sagita Subekti, Aditya Rindang Tri Yani Akhirina Wahyu Nur Cholifah Wahyu Nur Cholifah Za’imatun Niswati