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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Rekayasa Bahan Alam dan Energi Berkelanjutan Machine : Jurnal Teknik Mesin TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Journal of Innovation Information Technology and Application (JINITA) Indonesian Journal of Chemical Studies (Indones. J. Chem. Stud.) JURNAL AGROTEKNOSAINS Journal of Artificial Intelligence and Digital Business Journal of Farming and Agriculture
Pratama, Borneo Satria
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Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering

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Implementation of Simple and Weighted Moving Average for Forecasting Tela-Tela Production in MSME X Sariati, Sariati; Pratama, Borneo Satria; Albar, Ferdy; Sitio, Dea Yolanda Putri; Riandry, Dimas Dwika; Antonio, Marcho; Januarti, Sri; Aliansyah, Bayu Rimba; Sutignya, Th. Candra Wasis Agung; Solfianti, Maidia; Erwan, Erwan; Sembiring, Loko Jeremia
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.5205

Abstract

Accurate production forecasting is essential for micro, small, and medium enterprises (MSMEs) to support effective production planning, inventory control, and decision-making. This study evaluates the performance of the Simple Moving Average (SMA) and Weighted Moving Average (WMA) methods in forecasting tela-tela production demand at MSME X using different historical period lengths. Production data from November 2023 to October 2024 were analyzed, and forecasting accuracy was assessed using the Mean Absolute Percentage Error (MAPE). The results indicate that forecasting accuracy varies depending on both the length of the moving average period and the weighting scheme applied. The WMA model with a 4-period window (n = 4) achieved the highest accuracy, producing the lowest MAPE value of 8.36%, which is classified as highly accurate. The SMA model with n = 4 also demonstrated good performance, with a MAPE value of 14.40%. Meanwhile, models employing longer historical periods (n = 8) yielded MAPE values of 16.20% for WMA and 19.82% for SMA, both falling within the good forecasting performance category but exhibiting lower responsiveness to recent demand changes. These findings highlight that shorter historical periods, when combined with appropriate weighting, can more effectively capture recent demand patterns in dynamic production environments. Accordingly, the WMA method with a 4-period window is recommended for MSME X as a reliable and accurate approach to support production planning, optimize resource allocation, and reduce the risk of overproduction or stock shortages.  
The Effect of Germination Time and Aloe vera Rind Ratio on Physicochemical and Nutritional Properties of Peanut Sprout Snack Bars: ROC-SAW Approach for Product Optimization Narsih; Pratama, Borneo Satria
Indonesian Journal of Chemical Studies Vol. 4 No. 2 (2025): Indones. J. Chem. Stud. December 2025
Publisher : Indonesian Scholar Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55749/ijcs.v4i2.148

Abstract

This study examined the effects of peanut germination time and the ratio of germinated peanut sprout flour to aloe vera rind flour on snack bar quality. Two experimental parameters were used in the study: flour proportions of 90:10, 80:20, and 70:30, and germination times of 12, 24, and 36 hours. The first evaluation concentrated on proximate composition, which included quantities of moisture, ash, fat, protein, fiber, and carbohydrates. Both factors and their interaction had a substantial (p < 0.05) impact on all proximal metrics. In order to determine the best formulation, these proximate data were then integrated into a multi-criteria decision-making framework using the Rank Order Centroid (ROC) and Simple Additive Weighting (SAW) techniques. The ROC–SAW results showed that the best combination of a 36-hour germination period and a 70:30 flour ratio yielded 23.79% protein, 8.81% fiber, 15.15% fat, and 31.37% carbohydrates. Additional analyses of the optimized formulation included antioxidant evaluation, amino acid profile, and FT-IR spectroscopy. FT-IR spectra revealed the presence of functional groups such as hydroxyl, carbonyl, amide, alcohol, and ether. Aspartic acid, glutamate, and arginine were the most frequently detected amino acids. The antioxidant activity IC50 value obtained from the DPPH experiment was 10,734.27 ppm. All things considered, combining germinated peanut sprout flour with aloe vera rind flour shows promise for producing a functional snack bar with enhanced nutritional content and bioactive potential.
Co-Authors Aditya Wahyu Nugraha Afifah, Amalia Afnita, Deviola Yuri Afnita Albar, Ferdy Aldriana, Putri Alfiqriyansyah, Alfiqriyansyah Aliansyah, Bayu Rimba Andhik Ampuh Yunanto Antonio, Marcho Bambang Ismuyanto Cahya Brutu, Henrike Lehla Devita, Wilda Harlia Drantantiyas, Nike Dwi Grevika Endo Pebri Dani Putra Erwan Erwan, Erwan Fahrezy, Fico Dika Gaol, Merdiaty Lumban Gunawan, Desdy Hendra Hartati, Intan Dwi Hidayati, A.S Dwi Saptati Nur Ilham Marvie Indrastuti, Y. Erning Januarti, Sri Jatmiko Eko Witoyo Lestianti, Khairunnisa Arika Maulana, Rizka Syaiful N Narsih Nadi, Muhammad Abi Berkah Narsih Noveliska Br Sembiring, Noveliska Br Pangestuti, Martasari Beti Pertiwi, Aulia Hana Putra, Tamam Athallah Rhely Riandry, Dimas Dwika Rukmana, Fitri Hardiyanti S, Arya Dwicahya Safitri, Sela Saniah Sariati Sariati Sariati, Sariati Sembiring, Loko Jeremia Sitio, Dea Yolanda Putri Solfianti, Maidia Subara, Deni Th. Candra Wasis Agung Sutignya Tri Hadiah Muliawati, Tri Hadiah Winda Winda Yunira, Eka Nur'azmi