Judul: Kajian terhadap penggunaan anova dan ordinal logit dalam analisis data organoleptik
Abstrak: Selama ini analisis yang digunakan dalam uji organoleptik adalah metode A11ova (Aua/fJariance). Beberapa ahli statistik keberatan jika uji organoleptik menggunakan A11ova dalam ana1isisnya. Alasannya adalah karena tidak terpenuhinya syarat interval pada data yang digunakan daJam uji organoleptik. SeJain itu Anova merupakan salah satu metode analisis yang dalam penggunaannya didasari oleh asumsi-asumsi tenentu. Tidak terpenubinya asumsi tersebut dapat mempengaruhi taraf nyata dari kcpekaan uji. Apabila terjadi pe1anggaran asumsi maka harus dilakukan transformasi sampai seluruh asumsi tcrpenuhi. Dalain pcnclitian ini pendekatan yang digunakan adalah pendekatan Generalized Linier Model yaitu ordinaJ logit, dimana respon yang digunakan adalah respon ordinal atau peubah respon yang menunjukkan suatu peringkat. Bahan pene.litian berupa 47 data uji organolcptik yang terdiri dari uji hedonik dan uji skoring, yang diperoleh dari basil penclitian mahasiswa Teknolog; P""l!"ff dari Gm, IPB. Dari perl,andingan terhadap keputusan Anmu dan ordinal logit temadap 4 7 data uji organoleptik diketahui bahwa kemampuan A11ova dalarn meoolak Ho atau mcndeteksi perbedaan lebih tinggi dibanding ordinal logit. N81Dl1D hal tersebut tidak berarti AlkWtl lebih baik dibanding ordinal logit. Syarat pcnting dimana analisis secara parametrik minimal hams bcrupa data interval yang tidak dipenuhi oleh data uji organolcptik mcngakibatkan Anova cenderung melakukan kcsalahan jdlis L yaitu keputusan menolak H., padahal H.. benar. Perbandingan nilai-p 47 data uji organoleptik pada taraf nyata 1%, 5%, dan 100/4 memmjukkan kecenderungan dimana semakin kecil nilai taraf a maka galat jcnis I dari Anova akan semakin kecil. Menurunnya peluang galat jenis I diikuti oleh peningkatan galat jenis II. Peningkatan terhadap galat jenis II mengakibatkan penurunan terhadap puwer atau kuasa uji Anova. Dari hasil analisis pu1a dikc:tahui bahwa kesalahaA jenis I dan jeois U tidak dipengaruhi oleh atribut sensorinya. Seisin itu dari basil analisis memmjukkan bahwa untuk data-data organoleptik pemcnuhan terhadap asumsi-asumsi Anova tidak. berpeogaruh terhadap kesalahan jenis I atau jenis II. Se1ain karena tidak terpenuhinya syarat interval, upaya transfonnasi data sebenamya sudah merupakan suatu masalah terscndiri dalam analisis menggunakan AIIOWl, karena upaya transformasi tidak: mudah dilakukan dan transformasi tidak menjamin asumsi-asumsi Al1Qva terpenuhi. Pemenuhan terhadap sa1ah satu asumsi bisa menycbabkan asumsi lain menjadi terlanggar. Berdasarkan alasan­alasan tersebut maka ordinal logit dapat digunakan sebagai alternatif metode analisis yang lebih aman digunak:an dalam uji organoleptik dibandingkan A nova.
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Judul: Determination Of The Facial Foam Sensory  Attributes’ Optimum Value Using Ordinal  Logistic Regression Models
Abstrak: ANDINI DESITA EKAPUTRI. Determination of the Facial Foam Sensory Attributes Optimum Value Using Ordinal Logistic Regression Models. Under the supervision of KHAIRIL ANWAR NOTODIPUTRO and BAMBANG SUMANTRI. Market products have many characteristics to be maintained by the companies to fit the consumers’ preference. One of important characteristic s is sensory aspects. Sensory aspects are built by the five senses from the human body namely sight, sound, taste, touch and smell. However, the problem is the optimum value of each sensory attribute is still unknown. Preference attribute, which is the response variable is usually measured by an ordinal scale. As a result simple linear regression would not be appropriate. One of the alternatives is by using ordinal logistic regression, a model that takes rank ordering of the response variables into account. Using one of the ordinal logistic models, the proportional odds model, the optimum value will be obtained by searching the highest individual probability for the “like it” category of preference attribute for each category of performance attribute. The analysis for each of the attribute were treated differently depended on the brand product influence, named panel. If an attribute was influenced by the panel then the optimum value would be obtained for each panel. However, if all panels did not give any significant influences, than the analysis could be done entirely without considering the panels. The result showed that only three sensory attributes were affected by the panels, namely smoothness, thickness of foam during use and ease of rinsing at tributes. The optimum value of a product was based on the individual probability of the preference attribute. In other word the objective was to know how big was the probability to choose scale 4 of the preference attribute, which was the “like it category”, of each performance attribute’s category. For most of the performance attributes, scale 4 tended to have largest probability to be preferred. Only stickiness and sticky feel after rinsing had the largest probability on scale 1 which was “not sticky at all category ”. The last objectives was to find out the association among categories of performance attribute using odds ratio. An odds ratio that has value more than one means that the observed category is less preferred than the reference category. C onversely, an odds ratio that has value less than one means the observed category is more preferred than the reference category.
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Judul: Pengaruh Perubahan Luasan Glaciers Puncak Jaya Papua Indonesia Terhadap Kapasitas Panas dengan Menggunakan Citra Satelit TM/ETM+
Abstrak: Puncak Jaya glaciersis one of tropical glaciers in the earth that exists in Papua Island, Indonesia- Papua New Guinea. Glaciers have important function as phenomenon record, freshwater storage, and climate change indicator. Area, net radiation, and surface temperature of glaciers were measured by remote sensing method using landsat imagery data in 1989, 1997, 1999, 2000, 2004, 2007, and 2009. Glaciers area was measured by researcher using manual delination and using ArcGIS 9.3 to measure area. Glaciers volume was estimated using Bahr empirical formula, V = β A γ. The result showed total area loss in Puncak Jaya is 72,1% from 4,409 km2 in 1989 to 1,231 km2 in 2009. Total glaciers volume loss from 1989 to 2009 is 77,47%from 123,3 (10-3 km3) to 28,2 (10-3 km3). Nett radiation in glaciers area ranges from 107,5 W/m2 to 294,5 W/m2 with nett radiation mean per year per ice mass 206,2 W/m2. Glaciers albedo ranges from 0,19 to 0,53 with albedo mean per year per ice mass 0,37. Glaciers surface temperature ranges from -7,0oC to 7,0oC with surface temperature meanper year per ice mass -0,6oC. Heat capacity in glaciers area ranges from 0,30 (x 106 MJ K-1) to 110,37 (x 106 MJ K-1) from 1989 to 2009.
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