Judul: Clustering data kategorik menggunakan algoritma K-histogram (studi kasus: data PPMB IPB)
Abstrak: Perkembangan teknologi mengakibatkan meningkatnya data dalam jumlah besar. Namun sering kali data yang tersin~pan belum dimanfaatkan secara maksimal sehingga terjadi penumpukan data. Kasus ini terjadi di Panitia Penerimaan Mahasiswa Barn Institut Pertanian Bogor (PPMB WB). Penelitian ini bertujuan untuk mengimplementasikan algoritma k-histogram dalam clustering data kategorik, dan unruk mendapatkan karakteristik data dari hasil clzrstering. Data yang digunakan adaIah data kategorik pelamar tahun 2004 dengan pilihan pelrama program sarjana di Fakultas Pertanian, IPB. Data tersebut meliputi data asal pelamar, pilihan pertama pelamar, kategori sekolah pelamar, dan keputusan, sebanyak 1899 baris dan 4field yditu: Propinsi, Pilihanl, Putusanl, dan Kategori. Penentuan inisialisasi nilai awal k-histogram dilakukan dengan memilih nilai k record pertama. Proses ciusfering dilakukan untuk 2 sampai dengan 10 ukuran cluster , dengan batasan iterasi 50 kali untuk setiap ukuran cluster. HasiI clustering dari algoritma k-histogram dievaluasi menggunakan nilai cohesion dm distinctness dari setiap hasil cluster. Penelitian menunjukkan bahwa hasil clustering yang terbaik berada pada ukuran cluster 10 dengan 1 kali iterasi, dengan nilai cohesion 1.2455000 dan distinctness 0.0652344, dengan penyebaran yang tidak merata di setiap ciusternya. tJntuk setiap cluster, dilakukan pengamatan terhadap niiai cohesion yang menunjukkan keberagaman objek di dalarn cltrster tersebut dan distinctness yang menyatakan ketidakmiripan objek antar-cluster. Nilai cohesion yang lebih keciI menunjukkan keberagamnya objek di dalam cluster tersebut semakin besar. Semakin besar niIai cohesion, keragaman, semakin besar nilainya, maka sernakin besar ketidakmiripan (dissimilar) antar-cluster (intercluster). Kata Icunci: Clustering, Data Kategorik, K-Histogram, Cohesion, Distinctness
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Judul: Clustering menggunakan self organizing maps studi kasus:data PPMB IPB
Abstrak: Perkembangan teknologi mengakibatkan meningkatnya data dalam jumlah besar. Data berukuran besar yang sudah disimpan tidak digunakan secara optimal karena manusia seringkali tidak memiliki waktu dan ilmu yang cukup untuk mengelolanya. Kasus ini terjadi di Panitia Penerimaan Mahasiswa Baru Institut Pertanian Bogor (PPMB IPB). Penelitian ini bertujuan untuk mengimplementasikan Algoritma Self Organizing Maps (SOM) dalam clustering data, dan untuk mendapatkan karakteristik data dari hasil clustering.
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Judul: Production and formulation of methyl ester sulfonate-based surfactant from palm olein for enhanced oil recovery application
Abstrak: The remaining oil in a reservoir that cannot be produced using the natural driving force (primary recovery) is about 50 to 80% of the initial oil volumes (IOIP). A secondary recovery technique such as waterflooding can only increase the recovery as much as 5 to 20% of the IOIP. Therefore, a method known as Enhanced Oil Recovery (EOR) has to be implemented in the reservoir in the effort to recover much more oil. One of the EOR methods is surfactant injection. The injection of surfactant solution is aimed to significantly reduce the capillary forces in the reservoir by lowering the oil-water interfacial tension within the pore spaces. Once the capillary force is diminished, the reservoir oil is much easier to be displaced and moved toward the production wells. This is an excellent opportunity to develop a type of vegetable oil-based surfactants. One of potential surfactant types to develop is methyl ester sulphonate surfactant (MES). This study was aimed at producing MES surfactant and formula-based methyl ester sulfonate surfactant from palm olein to be applied for in the process of improving oil recovery using carbonate formation fluids. Results of the study showed that the best condition was achieved in a sulphonation process done in 3-4 hours with the flowrate of dry air of 1.8 kg/hour and a purification performed without the addition of methanol in a pH of 8. The best MES surfactant-based formula for EOR applications on the formation of carbonate was the one with the composition of 0.3% MES surfactant, 0.3% Na2CO3, and 15,000 ppm salinity. MES surfactant produced from this formula had more heat resistance, higher salinity, and higher hardness than the commercial surfactants did. Results of the performance test of surfactant-based formula showed that the MES surfactant formula was compatible with formation water and injection water. The formed phase was a lower phase which was relatively stable on a heating up to day 77 (reservoir temperature of 70 and 112 °C) with a range of interfacial tension of 10-2 dynes/cm. The adsorption reached 152.86 μg active matter/g core and the incremental oil recovery using synthetic core of 8-19% and using native core of 9.1%. Surfactant solution coreflooding test with bottom-up flow direction resulted in a greater oil recovery (16%) than that with top-down flow direction. This was caused by the influence of gravity.
Keyword: Palm Olein