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Abstrak :
Generalized Assignment Problem (GAP) adalah masalah penugasan sejumlah berhingga tugas pada sejumlah berhingga agen, dimana sebuah tugas harus dikerjakan oleh satu agen, tetapi satu agen dapat mengerjakan lebih dari satu tugas. Setiap agen mempunyai kapasitas dan setiap tugas mempunyai bobot, yang mungkin berbeda untuk setiap agen. Pada skripsi ini akan dilihat kinerja dari algoritma MAX-MIN Ant System (MMAS) dengan Local Search dalam menyelesaikan GAP, yang diukur berdasarkan kedekatan solusi yang didapatkan dengan best known solution. MMAS adalah pengembangan dari Ant System Algorithm, yaitu algoritma yang diinspirasikan oleh perilaku semut-semut di dunia nyata. Dalam algoritma ini terdapat parameter ??, Q, ??, dan p0 yang harus ditentukan, yang diambil menurut rekomendasi St??tzle dan Hoos. Lalu nilai dari parameter Q, ??, dan p0 akan diubah untuk mengetahui pengaruhnya terhadap kinerja algoritma MMAS dengan Local Search. Masalah pengujian diambil dari OR-Library. Berdasarkan simulasi, disimpulkan bahwa kinerja algoritma MMAS dengan Local Search dalam menyelesaikan GAP cukup baik dengan error relatif cukup kecil, yaitu tidak lebih dari 0.04 dan perubahan nilai parameter dapat membawa perbaikan pada solusi.

Abstrak :
Search computing, which has evolved from service computing, focuses on building the answers to complex search queries by interacting with a constellation of cooperating search services, using the ranking and joining of results as the dominant factors for service composition. The field is multi-disciplinary in nature and takes advantage of contributions from other research areas such as knowledge representation, human-computer interfaces, psychology, sociology, economics, and legal sciences. The book has been divided into four parts focussing on extraction and integration, query and visualization paradigms, exploring linked data, and games, social search and economics.

Abstrak :
The study analyzed the behavior of the labor force participation in the labor market, and the impact of occupational mismatch to the decision of workers continued to. Job search even they have employed by using The Job Search Model. However, the application of the Job Search Model to deal with the characteristics of labor market today, i.e. the highly of disguised unemployment, the gap in labor market, the increasing mobility of workers from informal to. Formal sector the education attainment of job searchers increased rapidly, and some phenomena's of the occupational mismatch and on-the job-search. The raw data in the study used the data SUPAS 1985 (Intercensal Population Survey 1985) was conducted by Biro Pusat Statistik (Central Statistic Bureau) especially for South Sulawesi province. The labor force in this sample amount 23,967 and out of these only 9,982 employed and remains still unemployed. In The Job Search Model or Search Theory argued that to analyzed individual decision to participate in the labor market or to analyzed the returns could be obtain during job searching process could be measured by using the reservation wage they received after deducted from the expenses they spend during job searching activities. Empirically, the reservation wage was influenced by the individual characteristic and the other factors that engage in labor market. The decision of job searchers whether they will accept or rejected each job that offered to them it will be influenced by individual characteristic and another factors as mentioned above. Since the data above not available in the Intercensal Population Survey 1985, this study will emphasize on job searching which influences by individual characteristic (namely, education level, marital and migrant status, age and residence) and labor market characteristic. The types of occupation, which a proxy of wage, categorized into professional, white collar, blue collar and others. For analysis purposes, all the categorized was assume "stratum". It's means that the workers who have job searching, will be consider a higher job levels or at least at the same level only. By-using Multinomial Logit Model, it's conclude that the higher level of education workers, the probability to achieved blue collar and others tend to decrease, while probability to achieved white collar and professional tend to increase. The average probability to keep engage in this job concentrated more on farmer and menial workers (others). Another conclusion, which have participated in the same job category, the probability of higher education workers to get higher or the same of job level was higher if compared to lower education workers.

Abstrak :
Proses penjadwalan kuliah merupakan proses yang cukup rumit karena komponen-komponen yang dijadwalkan saling berkaitan dan memiliki kondisi yang berbeda-beda. Biasanya penjadwalan mata kuliah dilakukan secara manual. Namun prosesnya akan memakan waktu yang cukup lama, dan penyesuaian kendala yang cukup sulit. Beberapa metode penyelesaian penjadwalan yang telah digunakan yaitu Algoritma Genetik, Algoritma Tabu Search dan gabungan dari keduanya yaitu Algoritma Hybrid Genetic-Tabu Search. Dalam penelitian ini akan dicari hasil perbandingan Algoritma Tabu Search dan Algoritma Hybrid Genetic-Tabu Search dalam penyelesaian masalah penjadwalan mata kuliah. Data yang digunakan berupa data dummy. Berdasarkan hasil simulasi, Algoritma Hybrid Genetic-Tabu Search memiliki konvergensi menuju solusi optimal lebih cepat dengan memberikan nilai fitness yang lebih baik dibandingkan dengan Algoritma Tabu Search dalam menyelesaikan masalah penjadwalan kuliah. ......The course scheduling process is a fairly complicated process because the components scheduled are related and have different conditions. Usually the scheduling of courses is done manually. But the process will take a long time, and the adjustment of obstacles is quite difficult. Several scheduling settlement methods that have been used are Genetic Algorithm, Tabu Search Algorithm and a combination of the two, Hybrid Genetic-Tabu Search Algorithm. In this study, the results of the comparison of Tabu Search Algorithm and Hybrid Genetic-Tabu Search Algorithm in solving the problem of scheduling courses. The data used in simulation is dummy data. Based on the simulation results, Hybrid Genetic-Tabu Search Algorithm has convergence to an optimal solution faster by providing better fitness values compared to Tabu Search Algorithm in solving university course scheduling problems.