Judul: Analysis and Design of Mobile Application for Bottling Machine Maintenance Based on Association Rule Mining
Abstrak: Salah satu permasalahan dalam penerapan Total Quality Management (TQM) dan Six Sigma adalah panjangnya respon managerial dalam merespon kondisi yang ada dilapangan. Penelitian ini bertujuan untuk membantu perusahaan melakukan tindakan pengambilan keputusan berdasarkan kondisi yang ada guna mewujudkan perbaikan yang terarah serta lebih cepat. Penelitian ini menggabungkan metode perhitungan total defect, Sigma Value pada six sigma, dan perhitungan OEE untuk penentuan keputusan yang diambil oleh perusahaan. Kondisi tersebut kemudian diolah dengan Association Rule Mining (ARM). Penggunaan ARM bertujuan untuk membuat aturan yang menunjukkan asosiasi antara parameter Sigma Value dan juga OEE dengan tindakan keputusan yang dilakukan perusahaan. Hasil perhitungan Sigma Value untuk Lini Produksi PET menunjukkan Sigma Value sebesar 4.29 dan hasil perhitungan OEE untuk availability, performance dan quality sebesar 86%, 54% dan 98% dengan total nilai OEE sebesar 46%. Rule yang terbaik didapatkan dari minimal nilai support, confidence, bond sebesar 0.3, 0.35 dan 0.5. Rule didapatkan dari 3 set combination dengan hasil 32 rules terbaik dari total 13.777 rule. Design penentuan rule tersebut diaplikasikan dalam aplikasi berbasis android untuk mempercepat proses pengambilan keputusan.
Keyword: Association Rule Mining, Management y Improvement, Overall Equipment Effectiveness, Six sigma

Judul: Analisis dan Perancangan Sistem Predictive Maintenance Menggunakan Association Rule Mining pada Mesin Moulding PT X.
Abstrak: One of the challenges in the implementation of Total Productive Maintenance (TPM) in the manufacturing industry is a slow managerial decision-making to respond the condition in the factory. This research investigates the answers of these challenges by analyzing and modeling the equipment condition and the response of actions required in a wooden door manufacturing industry. TPM implementation in this company has deployed the Overall Equipment Effectiveness (OEE) measurement as an indicator of the equipment utilization and condition. Through an analysis and modeling of the OEE value obtained from the factory, the formulation of Association Rule Mining (ARM) aims to find a rule that shows the well computed relationship between measurable indicators of OEE with the response of action required to take in certain condition of machine utilization. Results obtained from ARM accelerate the decision to establish an appropriate TPM management strategy based on the rules. The generated dynamic rules form and facilitate the process of decision-making by related stakeholders. Furthermore, relying on these rules the action taken by the company induced to a higher reliable and increasing the effectiveness of response and efficiency of time and costs.
Keyword: Overall Equipment Effectiveness, Association Rule Mining, Data Mining, Total Productive Maintenance

Judul: Distribution and Diversity of Ectoparasite Mites on Geckos in Indonesia
Abstrak: Data on the diversity and dispersal of parasitic mites on house geckos in Indonesia are very scarce. In this work, the distribution and diversity of mites living on three species of house geckos, namely Cosymbotus platyurus, Hemidactylus frenatus, and H. garnotii collected throughout Indonesia, has been elaborated. Geckos and mites were captured and immediately preserved in 70% ethanol. Whole mount of the mites was prepared by clearing in lactophenol followed by mounting on polyvinyl lactophenol solutions. The SEM preparation was conducted to examine the detail morphological characters of the mites. The results showed that among 448 individuals of geckos, 221 geckos were infected by Geckobia mites. Prevalences of C. platyurus, H. frenatus, and H. garnotii infested by mites were 14.8%, 50.69%, and 79.6%, respectively. Three different spesies of Geckobia (G1, G2, and G3) could be differentiated; and based on similarities of their morphological characters to ones described in published literatures, Geckobia G2 is Geckobia glebosum and Geckobia G3 is Geckobia bataviensis while G1 could not be identified to the species level. The highest mean intensity of Geckobia G1 infestation was found on H. garnotii (I=7.0), G. glebosum infestation on H. frenatus (I=3.5), and G. bataviensis infestation on H. garnotii (I=11.8). In general, C. platyurus was infested by the least number of mites. Geckobia G1 were found living on the skin folds on the claws, G. glebosum were found mainly on the body and thigh, and G. bataviensis were found on almost all parts of the host’s body. Geckobia mites are distributed randomly throughout Indonesian Archipelago, following the pattern of distribution of their hosts. So it is concluded that Geckobia G1, G. glebosum, and G. bataviensis are sympatric.
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