Judul: Aplikasi Sequential Pattern Discovery Using Equivalence Classes (Spade) Pada Data Transaksi Penjualan (Studi Kasus Produk Kecantikan Dan Perawatan Tubuh).
Abstrak: Setiap toko ritel memiliki data transaksi penjualan yang besar yang dihimpun setiap harinya. Data-data transaksi tersebut dapat diolah sehingga diperoleh informasi-informasi berguna, di antaranya pola belanja konsumen. Pola belanja konsumen dapat digunakan sebagai bahan untuk perancangan strategi pemasaran. Analisis yang biasa digunakan yaitu analisis asosiasi pada transaksi penjualan. Penelitian ini menggunakan metode pola sekuensial dengan algoritme SPADE ‘Sequential PAttern Discovery using Equivalence classes’. Data yang digunakan adalah data riil transaksi penjualan toko ritel produk kecantikan dan perawatan tubuh sejak 1 Januari-22 April 2015. Minimum support (batas minimum banyaknya pembeli) yang digunakan 0.01% dan minimum confidence (batas minimum peluang kejadian) sebesar 1%, kedua nilai tersebut ditentukan berdasarkan keadaan data. Berdasarkan hasil yang diperoleh, menunjukkan item yang paling diminati adalah sabun pencuci muka dan minyak penghilang jerawat berbahan kayu putih, grup yang paling diminati adalah grup make up bibir dan make up dasar. Pada data latih dan data uji yang relatif seimbang, semakin panjang periode penjualan dan semakin banyak transaksi maka semakin baik pula akurasi pembelian kembali yang diduga.
Keyword: data transaksi, pola sekuensial, SPADE, strategi pemasaran.

Judul: Penentuan pola sekuensial data transaksi pembelian menggunakan algoritme SPADE
Abstrak: The rapid development of information technology that is happening these days requires people to adapt into these developments. This human efforts can be seen from the many activities carried out by computerization that produces large amounts of data. From these available abundant data, the discovery of useful knowledge from large database becomes popular and attractive. This discovery of useful knowledge can be done using the concept of sequential pattern mining. One of the algorithms that applies the concept of sequential pattern mining is Sequential Pattern Discovery using Equivalence classes (SPADE) that is able to determine the sequential pattern of a data transaction. By adopting the functions contained in the SPADE algorithm, the purchasing tendency of items by customer at a specific time period can be seen. This research use the purchase transactions data of Sinar Mart Swalayan in period of 1 March to 31 March 2004. In this research, the minimum support was tested starting from 45% to 89% and minimum confidence from 20% to 96%. Minimum support and minimum confidence which is given is determined based on the condition of the data. Experimental results showed that the maximum value of minimum support that still could generate frequent sequences was 89%.
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Judul: Methane Consumption (CH4) on Upland Rice Cultivation Under Micro Climate Cobdition With N Fertilizer Levels
Abstrak: Methane (CH4) is one of radiatively active trace gases or greenhouse gas, having strong absorbsivity to the infrared outgoing radiation emitted by the earth's surface, hence causing the warming of the atmosphere. Methane concentration in the atmosphere increases with a rate of about 12+1 ppbv/yr, or 36 Tg/yr. The increase of methane was predicted to have a significant impact on the earth's climate. The presence of 1.3 ppmv of methane in the atmosphere causes the globally average surface temperature 1.30C higher than it would be with no methane.
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