Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Informatika dan Multimedia Jurnal Teknik Pertanian Terapan
Sariati
Politeknik Negeri Pontianak
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Energy Engineering Environmental Science

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementasi Simple dan Weighted Moving Average dalam Peramalan Produksi Keripik Labu Kuning pada UMKM X di Pontianak: Implementation of Simple and Weighted Moving Average in Forecasting the Production of Yellow Pumpkin Chips at MSME X in Pontianak Sariati; Borneo Satria Pratama; Yesrol Elia Sanak; Alfred Pandapotan Saragih; Erinkha Miftah Urrahmah; Elsa Windiastuti; Th. Candra Wasis Agung Sutignya; Holpu Ronal Ambarita; Rianta Chen Yohana Manik; Triva Maria Manik
Jurnal Teknik Pertanian Terapan Vol. 3 No. 1 (2025): Agustus
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtpt.v3i1.6291

Abstract

UMKM (Usaha Mikro, Kecil, dan Menengah) X merupakan produsen keripik labu kuning di Pontianak yang mengalami fluktuasi produksi akibat belum adanya perencanaan berbasis data historis. Penelitian ini bertujuan untuk menerapkan metode Simple Moving Average (SMA) dan Weighted Moving Average (WMA) dalam peramalan jumlah produksi serta membandingkan tingkat akurasi keduanya menggunakan Mean Absolute Deviation (MAD). Data produksi keripik labu dikumpulkan selama periode Desember 2023 hingga November 2024. Peramalan dilakukan untuk bulan Desember 2024 dengan dua rentang waktu (n = 3 dan n = 6). Hasil menunjukkan bahwa SMA dengan n = 6 memberikan hasil ramalan sebesar 16,67 kg dengan nilai MAD terendah sebesar 1,74. Sementara itu, WMA dengan n = 6 menghasilkan ramalan sebesar 16,24 kg dengan nilai MAD sebesar 2,09. Berdasarkan hasil tersebut, metode SMA dengan periode 6 bulan memberikan akurasi peramalan terbaik. Oleh karena itu, pendekatan ini direkomendasikan untuk digunakan UMKM X sebagai dasar dalam perencanaan produksi dan operasional yang lebih efisien.
React-Based Static Website Development for Decision Support System Using ROC and SAW: A Case Study on Hedonic Preferences of Chicken Meatballs Borneo Satria Pratama; Donor Utomo Muhammad Susilo; Sariati; Nayla Fadillah; Dodi Mahendra; Jimmy Angkasa; Elisabeth Erinawati; Penansius Delon; Fransiskus Kurnia Sandi
Jurnal Informatika dan Multimedia Vol. 18 No. 1 (2026): Jurnal Informatika dan Multimedia
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jtim.v18i1.9985

Abstract

This study presents the development of Qbico (Q-毘古), a React-based static website decision support system (DSS) integrating the Rank Order Centroid (ROC) method for attribute weighting and the Simple Additive Weighting (SAW) method for alternative ranking. Unlike previous web-based DSS implementations that rely on server-side architectures, Qbico operates entirely on the client-side via React CDN, making it lightweight and freely deployable via GitHub Pages without a dedicated server. The system was evaluated using a case study involving hedonic preference data from four chicken meatball formulations assessed by 18 trained panelists across three attributes: taste, texture, and saltiness level. One-Way ANOVA confirmed statistically significant differences among formulations for all three attributes (p ≤ 0.05). ROC weighting based on expert-determined priority order of taste > texture > saltiness level yielded weights of 0.611, 0.278, and 0.111, respectively. SAW computation produced a final ranking of YA > YB > XA > XB, with formulation YA identified as the best alternative, consistent with manual calculations in Microsoft Excel. Black-box testing across 17 test cases confirmed full functional correctness, and System Usability Scale (SUS) evaluation from 18 respondents yielded an average score of 90.4, corresponding to grade A+ "Best Imaginable," demonstrating excellent usability and user acceptance. Future development may extend Qbico to support additional MADM methods and incorporate data export functionality to broaden its applicability in agroindustrial decision-making.
Co-Authors Alfred Pandapotan Saragih Borneo Satria Pratama Dodi Mahendra Donor Utomo Muhammad Susilo Elisabeth Erinawati Elsa Windiastuti Erinkha Miftah Urrahmah Fransiskus Kurnia Sandi Holpu Ronal Ambarita Jimmy Angkasa Nayla Fadillah Penansius Delon Rianta Chen Yohana Manik Th. Candra Wasis Agung Sutignya Triva Maria Manik Yesrol Elia Sanak