Judul: Postharvest Handling Design at Vegetable Packaging House in Ciaruteun Ilir Village
Abstrak: Desa Ciaruteun Ilir merupakan salah satu daerah produksi sayur daun terbanyak di Kabupaten Bogor dimana komoditas kangkung merupakan komoditas utama yang diproduksi dengan luas panen sebesar 136.000 hektar. Petani memasarkan beberapa jenis sayur daun seperti kangkung, bayam merah, bayam hijau, caisim, daun ginseng dan selada ke pasar, kompleks perumahan dan Mitra X. Sayur daun yang diproduksi petani Ciaruteun Ilir, terutama sayur kangkung, cepat layu karena kesegarannya tidak tahan lama sehingga mengalami penurunan mutu yang ditandai dengan perubahan warna pada sayur. Penanganan pascapanen secara fisik tanpa menggunakan bahan kimia dapat dilakukan dengan perlakuan heat shock dan hydrocooling. Penelitian ini bertujuan merancang penanganan pascapanen untuk sayur daun guna mempertahankan mutu dan kesegarannya. Penelitian dilakukan dengan dua tahap yaitu penelitian pendahuluan untuk memilih perlakuan antara heat shock dan hydrocooling dimana perlakuan dengan efek yang lebih baik akan diterapkan pada penelitian penyelesaian. Penelitian penyelesaian dilakukan variasi waktu perendaman perlakuan terpilih, suhu penyimpanan dan perlakuan kemasan. Perlakuan hydrocooling dengan waktu perendaman 11 menit, penyimpanan pada suhu rendah (10–15oC) dan dikemas plastik polypropylene (PP) berlubang memberikan efek paling baik terhadap sayur kangkung yang dapat mempertahankan mutu sayur berdasarkan parameter susut bobot, perbedaan warna, kenampakan warna, penerimaan kesegaran dan umur simpan. Kangkung yang diberikan perlakuan hydrocooling pada suhu 8-10oC selama 11 menit, disimpan pada suhu rendah (10-15oC) dan dikemas plastik PP berlubang memiliki umur simpan selama 4 hari. Hydrocooling berpengaruh baik terhadap semua parameter mutu kangkung., Ciaruteun Ilir Village is one of the largest leaf vegetable production areas in Bogor Regency where water spinach is the main commodity produced with a harvested area of 136,000 hectares. Farmers market several types of leaf vegetables such as water spinach, red spinach, green spinach, caisim, ginseng, and lettuce leaves to markets, housing complexes, and Mitra X. Leaf vegetables produced by Ciaruteun Ilir farmers, especially water spinach, wilt quickly because their freshness does not last long so that experienced a decrease in quality which was marked by a change in the color of the vegetables. The postharvest handling physically without using chemicals are heat shock and hydrocooling treatments. This study aims to design postharvest handling of leaf vegetables to maintain their quality and freshness. This study was conducted in two stages, namely preliminary research to choose a treatment between heat shock and hydrocooling where the treatment with better effect will be applied to the complete research. The completion research was carried out by varying the immersion time of the selected treatment, storage temperature, and packaging treatment. Hydrocooling treatment with an immersion time of 11 minutes, storage at low temperature (10–15oC) and packaged in perforated polypropylene (PP) plastic gave the best effect on water spinach which can maintain vegetable quality based on parameters of weight loss, color difference, color appearance, freshness acceptance, and shelf life. Water spinach treated with hydrocooling treatment at a temperature of 8-10oC for 11 minutes, stored at a low temperature (10-15oC), and packaged in perforated PP plastic has a shelf life of 4 days. Hydrocooling has a good effect on all quality parameters of water spinach.
Keyword: heat shock, hydrocooling, kangkung, kualitas, penanganan pascapanen

Judul: Optimasi Rantai Dingin Dan Penjadwalan Kirim Untuk Peningkatan Ekspor Sayuran (Studi Kasus Unit Prosesing Sayuran Dataran Rendah Di Pekanbaru Riau)
Abstrak: Post harvest losses of horticultural products that occur in developing countries such as Indonesia have reached 1-50%. This study is an attempt to reduce postharvest losses of caisin and pak choi in the vegetable processing unit, Pekanbaru-Riau. The study was began by identifying of existing posharvest handling of vegetables, optimization of hydrocooling and storage temperature and optimization of vegetables export schedule. There was two of hydrocooling treatments and one control: without immersion(32oC) (A1), immersion in wells water(28oC) (A2) and soaking with ice water(5oC) (A3), and two cold chain temperature treatments: 4oC (B1) and 0oC (B2). The parameters observed were weight loss, leaf discoloration and organoleptic test. Postharvest handling in the processing unit consisted of harvesting, transportation to packing house, air precooling, trimming and sortation, packaging and storage. The losses of existing postharvest handling was 17,86% and 22,77% for caisin and pak choi. The results showed that hydrocooling of caisin and pak choi gave significant effect to weight loss. The combination of hydrocooling and storage temperature gave also significant effect to weight loss. Meanwhile, total weight losses for caisin on hydrocooling at 28oC and storage at 4oC and pak choi on hydrocooling at 28oC and storage at 0oC combination treatment gave the smallest weight loss influence about 7,83% and 8,35% respectively. The hydrocooling at 28oC and storage at 4oC (caisin) and 0oC(pak choi) is optimum postharvest treatment for decreasing weight losses. The results showed that hydrocooling treatment for both caisin and pak choi did not significantly affect to leaf color (L, a, and b). While combination of hydrocooling and storage temperature provided a significant effect on leaf color. The export optimization is reached by scheduling vegetables delivery during the period of a month.
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Judul: Sistem Pengklasifikasian Entitas pada Pesan Twitter Menggunakan Ekspresi Regular dan Naïve Bayes
Abstrak: The widespread use of social networks like Twitter encourages some institutions to find out the entities that are discussed and the sentiment toward the entities. This research aims to build a system that can extract entities in tweets and classify the sentiment from the tweets. Entity extraction process is done using regular expressions. Writing regular expressions can capture the diverse entities. Sentiment classification is performed using naïve Bayes classification with Multinomial and Bernoulli models. Sentiment in this research consists of three classes, namely positive, negative, and neutral. Before entering the classification, tweets are normalized by replacing the non-standard words with the standard ones. The test results show that regular expression is quite effective for the entity extraction process. As for the results of the classification, naïve Bayes method produces high accuracy (96.75% for Multinomial and 96.33% for Bernoulli). However, the accuracy obtained depends on the neutral class which amounts to 97.88% for Multinomial and 99.95% for Bernoulli, while the positive class are 85.66% and 33.13% and negative class are 33.67% and 0%.
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