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Pengaruh Ukuran Partikel Ampas Kelapa dan Rasio Kacang Tanah pada Karakteristik Snack bar Tinggi Serat Siti Aisyah; Yuliana Erning Indrastuti; Donor Utomo Muhammad Susilo; Dodi Iskandar; Suharyani Amperawati
Journal of Food Security and Agroindustry Vol. 4 No. 2 (2026): JUNE
Publisher : PAKIS JOURNAL INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58184/jfsa.v4i2.979

Abstract

Coconut dregs are a byproduct of the coconut oil processing industry, and their utilization as food is limited, even though they still contain crude fiber. This study aimed to analyze the effects of the size and ratio of peanuts and coconut dregs on the physical (color), chemical (water content and crude fiber), and sensory characteristics of snack bars. This study used a Completely Randomized Design (CRD) with two factors: the first factor is size of the coconut dregs (coarse and fine). The second factor was the ratio of coconut dregs to peanuts (15:85, 20:80, and 25:75 g/g). The analysis carried out on the snack bar was water content, fiber content, color (L*, a*, b*, whiteness index and browning index), sensory analysis (taste, color, aroma and texture) and hedonic. The results showed that the size of coconut dregs and the ratio of coconut dregs: peanuts did not affect the water content, b*, aroma, but did affect the fiber content, L*, a*, browning index, sensory taste, color, texture and hedonic. The 25:75 g ratio of coarse coconut dreg to peanuts had the highest preference score, with water and fiber contents of 4.51% and 17.52 %, respectively. The browning index of the snack bar with the highest preference score was the lowest. The coarse coconut dreg had a browning index of 28.80. The browning index of the snack bar with a coconut dreg:peanut ratio of 25:75 g had a browning index of 27.61.
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.
Particle Board Supply Chain Design from Palm Oil Solid Waste in West Borneo Province Iwan Rusiardy; Muflihah Ramadhia; Donor Utomo Muhammad Susilo
Journal of Economics and Management Scienties Volume 8 No. 2, March 2026
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jems.v8i2.335

Abstract

As the furniture industry develops, demand for wood-based particle board continues to increase, while the availability of wood from natural forests continues to decline. This situation has led to the need for sustainable alternative raw materials. Solid waste from oil palm in the form of empty fruit bunches (EFB) has great potential to be developed as a raw material for particle board. In West Kalimantan Province, the area of oil palm plantations reached 2,017,456 hectares in 2019, with a potential EFB production of around 7,470,639 tons. Therefore, this study aims to design an optimal supply chain network for the distribution of TKKS from palm oil processing plants in Sanggau Regency to particle board factories, as well as its distribution to all regencies/cities in West Kalimantan. The model developed uses a mixed-integer linear programming (MILP) approach to minimize total costs, including the costs of opening production sites, transportation, and distribution, while taking into account various constraints. The modeling results show that the optimal location for establishing a particle board factory is in Parindu District with a maximum capacity of 120,000 m³/year and a total investment of IDR 82,604,211,380.00. This model is expected to serve as the basis for long-term strategic decision-making for the West Kalimantan Provincial Government and be further developed by integrating TKKS as a by-product of the palm oil industry.