Judul: Optimasi Rencana Produksi Sayuran Hidroponik Nutrient Film Technique (NFT) Pada PT XY
Abstrak: Rencana produksi sayuran hidroponik NFT yang dilakukan PT XY belum berdasarkan pada forecasting permintaan. Hal tersebut menyebabkan produksi tidak cukup untuk memenuhi seluruh permintaan. Tujuan penelitian ini adalah memperoleh prakiraan permintaan dengan metode ARIMA dan menentukan jumlah produksi berdasarkan forecasting tersebut dengan menggunakan simpleks linear programming. Jenis sayuran yang diamati adalah selada keriting, lollorossa, dan romaine. Dari hasil optimasi, untuk memenuhi seluruh demand, penanaman tidak selalu dilakukan setiap hari namun jumlah tanaman yang ditanam dilakukan secara optimal. Penanaman tersebut dialokasikan dengan menyesuaikan persentase populasi hidup, peluang umur tanaman yang dipanen, prakiraan permintaan dan kapasitas lubang tanam yang tersedia. Hasil menunjukkan bahwa keuntungan dapat meningkat menjadi Rp484 988 563 dengan 127% prakiraan permintaan terpenuhi. Dibandingkan dengan data aktual, keuntungan yang didapat lebih rendah dengan permintaan yang dipenuhi hanya 78% bahkan apabila persentase disamakan menjadi 127%. Dengan demikian, optimasi ini dapat meningkatkan keuntungan dan memenuhi seluruh permintaan konsumen.
Keyword: ARIMA, forecasting, hidroponik, linear programming, produksi

Judul: Optimize Hydroponic Vegetable Production Plan at PT Sumber Agro Semesta (PT SAS), Tanjung Sari District, Bogor Regency
Abstrak: Perencanaan jadwal tanam sayur hidroponik di PT Sumber Agro Semesta (PT SAS) masih dilakukan secara subjektif oleh PIC hidroponik, yaitu dengan menggunakan prakiraan rata-rata permintaan sayur pada siklus sebelumnya. Perencanaan jadwal tanam belum dilakukan berdasarkan prakiraan permintaan sehingga terjadi perbedaan antara rencana tanam dan permintaan aktual. Kapasitas greenhouse produksi sebesar 38.556 lubang tanam juga belum digunakan secara maksimal sehingga banyak lubang tanam yang tidak terisi. Adapun tujuan dari penelitian ini adalah menentukan prakiraan permintaan, serta menentukan rencana produksi yang optimal berdasarkan prakiraan permintaan dan penggunaan maksimal kapasitas greenhouse. Prakiraan permintaan pada pakcoy, bayam hijau, caisim, kangkung dan kailan dilakukan melalui dua metode, yaitu menggunakan metode ARIMA dan asumsi peningkatan permintaan sebesar 10% dari permintaan aktual yang terakhir. Hasil optimasi dengan teknik linear programming pada kedua kondisi tersebut menghasilkan keuntungan masing-masing sebesar Rp. 71.296.390 untuk hasil optimasi berdasarkan metode ARIMA dan Rp. 70.690.398 untuk hasil optimasi berdasarkan asumsi peningkatan permintaan sebesar 10%. Selain itu, dilakukan pula optimasi produksi berdasarkan penggunaan maksimal kapasitas greenhouse produksi. Sayur yang dioptimasi penjadwalannya adalah pakcoy, bayam hijau, caisim, kangkung, kailan, siomak, pagoda, bayam merah, romain, selada, dan kale. Hasil optimasi dengan teknik linear programming pada kondisi tersebut menghasilkan keuntungan sebesar Rp. 70.904.345 dan total bobot produksi sekitar 1,5 ton., The planning of the hydroponic vegetable planting schedule at PT Sumber Agro Semesta (PT SAS) is still subjectively to hydroponic PIC, using the forecast of the average vegetable demand in the previous cycle. The planting schedule has not been planned based on the demand forecast, so there is a difference between the planting plan and the actual demand. The greenhouse production capacity of 38,556 planting holes has not been used optimally, so many planting holes are not filled. The purpose of this research is to determine the demand forecast and determine the optimal production plan based on the demand forecast and the maximum use of a greenhouse. Forecasting demand for pakcoy, green spinach, caisim, kangkung, and kailan is made through two methods, namely using the ARIMA method and the assumption of an increase in demand by 10% from the last actual demand. Techniques of linear programming in both conditions produce a profit of Rp. 71,296,390 for optimization results based on the ARIMA method and Rp. 70,690,398 for optimization results based on the assumption of a 10% increase in demand. In addition, production optimization is also carried out based on the maximum use of greenhouse production capacity. Vegetables that are optimized for scheduling are pakcoy, green spinach, caisim, kale, kailan, dumplings, pagoda, red spinach, romain, lettuce, and kale. Techniques of linear programming in these conditions generate a profit of Rp. 70,904,345 and a total production weight of about 1.5 tons.
Keyword: ARIMA, demand forecasting, linear programming, production plan

Judul: Categorization in Macaca fascicularis.
Abstrak: Categorization is an ability to group individuals or events into different classes mediated by conceptualized mental images. There are several levels of categorization and within a taxonomy the levels are nested. At the most concrete level of categorization, all or most members of the category shared common physical attributes that differ from other categories. The higher the level of category, the fewer common attributes between members of the group. In addition to humans, the ability to categorize has also been proposed in animals. One example of categorization in animal is species discrimination. Using matching-tosample task, present experiment tested ability of the long-tailed macaque (Macaca fascicularis) in discriminating dichotomous-stimuli of different animals. The species has been shown to be able to see photos as representations of real object so I used facial photos of humans and animals for the stimuli. First, I tested their ability to classify humans and macaques into separate group. Second, I tested their ability to discriminate their conspecific from other macaques. And the last, I tested whether the subjects were able to discriminate non-human animals from humans. In all of these experiments I found that the subjects showed high performance in categorizing objects, even when I discarded details of visual informations, such as color and local shapes. The ability to identify objects with reduced representation of physical properties means the subjects were able to generalize attributes of members of the group. This would indicate that the subjects created a higher level abstraction. On the other hand, in discriminating intrageneric macaque species I found that they were able to extract uniqueness of each species. More over, I also found that the subjects were able to put photos of non-human animals that shared very few similarities in physical percepts into one group. I suggested that the subjects could create a more abstract concept based on non-percepts relations as a basis to put the objects into one category. Thus, I concluded that M. fascicularis were able to perform multiple levels of categorizations.
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