Judul: Water Footprint Analysis on Subsurface Irrigation Systems in Greenhouse for Pakcoy (Brassica rapa L.) Cultivation
Abstrak: Air menjadi salah satu unsur pokok yang dibutuhkan tanaman pakcoy untuk tumbuh dan berkembang. Banyaknya kebutuhan air dalam menghasilkan produk dapat dikaji dengan pendekatan water footprint. Penelitian ini bertujuan menganalisis nilai water footprint pada budidaya Pakcoy (Brassica rapa L.) dengan berbagai skenario tinggi muka air. Penelitian dilakukan di dalam greenhouse Kinjiro Farm, Bogor, Jawa Barat pada bulan Maret - Mei 2023. Terdapat tiga perlakuan pada pengaturan tinggi muka air yaitu Tinggi Muka Air 1 (TMA 1) dengan ketinggian air 13 cm, Tinggi Muka Air 2 (TMA 2) dengan ketinggian air 10 cm, dan Tinggi Muka Air 3 (TMA 3) dengan ketinggian air 7 cm. Nilai water footprint TMA 1, TMA 2, dan TMA 3 berturut-turut sebesar 0,84 m3/kg, 0,63 m3/kg, dan 0,68 m3/kg. TMA 2 memiliki nilai water footprint terendah karena menghasilkan produksi tertinggi. Rata-rata pertumbuhan tinggi tanaman pakcoy, jumlah daun, dan berat hasil panen pakcoy tertinggi terjadi pada kondisi TMA 2, dengan rata-rata tinggi tanaman sebesar 19 cm dan rata-rata jumlah daun sebanyak 15 helai daun pada minggu terakhir serta berat total panen sebesar 250 gram. Perlakuan pada sistem TMA 2 merupakan perlakuan yang paling optimal dibandingkan dua perlakuan yang lain., Water is one of the main elements needed by the pakcoy plant to grow and develop. The amount of water needed to produce products can be assessed using the water footprint approach. This study aims to analyze the value of the water footprint in pakcoy cultivation with various scenarios of high water levels. The research was conducted in the greenhouse of Kinjiro Farm, Gunung Batu from March to May 2023. There were three treatments for setting the water level, namely Water Level 1 (TMA 1) with a water level of 13 cm, Water Level 2 (TMA 2) with a height water 10 cm, and Water Level 3 (TMA 3) with a water level of 7 cm. The water footprint values of TMA 1, TMA 2, and TMA 3 are respectively 0.84 m3/kg, 0.63 m3/kg and 0.68 m3/kg. The highest average growth of pakcoy plant height, number of leaves, and weight of the highest pakcoy harvest occurred in TMA 2, with an average plant height of 19 cm and an average number of leaves of 15 leaves in the last week and a total harvest weight of 250 grams. The treatment on the TMA 2 system is the most optimal treatment compared to the other two treatments.
Keyword: Greenhouse, Irigasi Bawah Permukaan, Pakcoy, Tinggi muka air, Water footprint

Judul: Analisis Water Footprint pada Budidaya Pakcoy dengan Sistem Irigasi Bawah Permukaan Pocket Fertigation
Abstrak: Keterbatasan ketersediaan air dan penurunan produktivitas tanaman sawi khususnya pakcoy menyebabkan diperlukannya teknologi irigasi tepat guna. Pocket fertigation merupakan pengembangan dari sistem irigasi cincin yang diharapkan dapat meningkatkan produktivitas tanaman dan air. Penelitian ini bertujuan menganalisis water footprint tanaman pakcoy menggunakan sistem irigasi pocket fertigation denganberbagai skenario, serta menentukan sistem irigasi yang paling optimal. Penelitian dilaksanakan pada bulan April-Juni 2022 bertempat di Kinjiro Farm, Kota Bogor. Tahapan penelitian meliputi persiapan lahan, pengumpulan data, pengolahan data, dananalisis water footprint. Rancangan skenario irigasi dipengaruhi faktor sistem irigasi pocket fertigation (P1) dan konvensional (P2), serta pemberian air satu kali evaporasi (A1) dan dua kali evaporasi (A2). Total water footprint pada skenario P1A1, P2A1, P1A2, dan P2A2 secara berturut-turut sebesar 251,72 m3/ton, 231,56 m3/ton, 296,18 m3/ton, dan 222,53 m3/ton dengan produktivitas air tertinggi terjadi pada skenario P2A1, sehingga diperlukan pengembangan pocket fertigation lebih lanjut untuk meminimalkan water footprint dan meningkatkan produktivitas air., The limited availability of water and the decrease in the productivity of mustard plants, especially bok choy, have led to the need for appropriate irrigation technology. Pocket fertigation is the development of a ring irrigation system which is expected to increase crop and water productivity. This study aims to analyze the water footprint of bok choy plants using pocket fertigation irrigation system with various scenarios, and to determine the optimal irrigation system. The research was conducted in April-June 2022 at Kinjiro Farm, Bogor City. The research stages include land preparation, data collection, data processing, and water footprint analysis. The irrigation scenario design is influenced by the pocket fertigation (P1) and conventional irrigation systems (P2), as well as the provision of water one time evaporation (A1) and two times evaporation (A2). The total water footprint in the P1A1, P2A1, P1A2, and P2A2 scenarios, respectively, was 251,72 m3/ton, 231,56 m3/ton, 296,18 m3/ton, and 222,53 m3/ton with the highest water productivity occurs in the P2A1 scenario, so that further pocket fertigation is needed to minimize the water footprint and increase water productivity.
Keyword: bok choy, pocket fertigation, subsurface irrigation, water footprint

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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