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PENDAMPINGAN MASYARAKAT LOKAL DALAM PELATIHAN PEMBUATAN BAKSO BERBAHAN BAKU SAGU DAN IKAN GASTOR Ginting, Nina Maksimiliana; Rizal, Abdul; Adrianus, Adrianus; Witdarko, Yus; Yusuf, Mega Ayu; Malesi, Wa Ode Asryanti Wida; Daoed, Denvy Meidian
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 4 No. 5 (2023): Volume 4 Nomor 5 Tahun 2023
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v4i5.21602

Abstract

Bakso merupakan makanan khas Indonesia yang banyak digemari Masyarakat. Bahan tambahan bakso dapat berupa daging dan ikan. Salah satu pengolahan bakso sagu yang didampingi kepada Masyarakat lokal adalah ikan gastor, karena ikan gastor merupakan ikan rawa yang banyak d temui di Kabupaten Merauke khususnya Kampung Zanegi, Kampung Tambat dan Kampung Kaliki. Dengan adanya pendampingan ini, Masyarakat yang ada di ketiga kampung tersebut dapat mengaplikasikannya untuk menambah pendapatan keluarga karena bahan-bahan yang digunakan banyak tersedia di Kampung tersebut.
Pendugaan umur simpan tepung pisang berdasarkan parameter kandungan air kritis Yusuf, Mega Ayu; Jamaludin, Jamaludin; Camara, Gode Vridus Titi; Limbongan, Amelia Agustina
AGRICOLA Vol 14 No 2 (2024): AGRICOLA
Publisher : Universitas Musamus, Merauke, Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35724/ag.v14i2.6433

Abstract

Banana (Musa paradisiaca) is a fruit that contains many minerals, vitamins and carbohydrates. There are various types of bananas that are popular among people. Starting from commercial bananas which have a high market value to bananas in processed form. This research was conducted to estimate the shelf life of banana flour using the Accelerated Shelf-Life Testing method which refers to the Arrhenius Model where the critical parameter is water content. The banana used is the kepok banana type at the No.2 ripeness level with the characteristics of the banana skin still being green but showing a tinge of yellow at the tip of the fruit accompanied by black dots around the surface of the banana skin. The packaging uses polyethylene film (thickness 0.10). Each package contains a 100 gram sample. Samples were stored at different conditions, namely 30oC, 35oC, 40oC and 55oC in an atmosphere with 80% relative humidity (RH) for eight weeks of storage. Once every week, samples are evaluated for critical water content. The research results showed that the sample packaging in polyethylene film was able to last up to 2.3159 months.
Shelf-Life Estimation of Dried Sago Noodles Using the Accelerated Shelf-Life Testing (ASLT) Method Jamaludin, Jamaludin; Asari, Muhamad Azis; Sutisna, Setya Permana; Yusuf, Mega Ayu
Jurnal Keteknikan Pertanian Vol. 13 No. 3 (2025): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.013.3.375-386

Abstract

Indonesia holds significant potential for sago (Metroxylon sp.) development, especially in the eastern regions. Sago starch offers an alternative to wheat flour in noodle production, promoting local food diversification. This study aims to estimate the shelf-life of dried sago noodles using the Accelerated Shelf-Life Testing (ASLT) method based on selected quality parameters. Dried sago noodles were produced from sago starch sourced from Merauke, South Papua, and stored at 35°C, 45°C, and 55°C. Quality attributes—moisture content, aroma, and taste—were analyzed during storage to model degradation kinetics and determine activation energy (Ea) using the Arrhenius approach. Among the tested parameters, aroma exhibited the lowest activation energy (636.04 cal/mol), indicating it as the critical parameter for predicting shelf-life. Based on the regression of ln k versus 1/T, the shelf-life at 27°C (room temperature) was estimated at 49 days. The study concludes that aroma degradation is the key factor in determining the shelf-life of dried sago noodles, and that accurate sensory evaluation using trained panelists is crucial for improving the reliability of shelf-life prediction.