Judul: Dasar-Dasar Matematika untuk Big Data
Abstrak: Karya ilmiah ini menelaah dasar matematika yang digunakan dalam big data dan teori logika fuzzy untuk big data. Dasar matematika untuk big data yang diperoleh dalam penelitian ini meliputi definisi-definisi dan teorema-teorema tentang pencarian yang dilakukan seseorang dalam suatu website. Pencarian yang dilakukan seseorang dalam suatu website dimodelkan ke dalam fungsi pencarian. Fungsi pencarian tersebut menunjukkan bahwa pencarian yang dilakukan seseorang dalam website terbatas (dalam nilai atribut), sedangkan informasi yang terdapat dalam website tidak terbatas. Selain itu, untuk menghitung kardinalitas big data dapat diwakili oleh nilai atribut, karena salah satu karakteristik yang dimiliki big data adalah sifat tak hingga. Sifat tak hingga big data juga dapat dimodelkan ke dalam logika fuzzy. Pemodelan menggunakan logika fuzzy dilakukan dengan cara menentukan fungsi keanggotaan “big” dari suatu himpunan fuzzy.
Keyword: big data, fungsi pencarian, kardinalitas, logika fuzzy

Judul: Pemodelan Berbasis Fuzzy Regression
Abstrak: Terdapat beberapa metode yang bisa digunakan dalam membuat model matematika, salah satunya adalah fuzzy regression models. Tujuan dari penelitian ini adalah menelaah penggunaan pendekatan fuzzy regression models untuk memodelkan beberapa masalah real. Fuzzy regression models dapat diterapkan pada beberapa bidang terapan di antaranya pada kasus pertama berupa model harga rumah dan harga kue yang ditulis oleh Alper Basaran et al. 2010 yang bisa dikombinasikan dengan metode lain yaitu dengan metode partial least square. Kasus kedua yaitu model pasokan energi yang ditulis oleh Hikmayangkara et al. tahun 2012 adalah model fuzzy regresi Tanaka yang diperluas oleh Chang dan Ayyub. Model pasokan energi tersebut diharapkan mampu meramalkan pasokan energi di tahun mendatang. Kasus ketiga yaitu model status diabetes membantu pakar kesehatan dalam menyatakan status diabetes seseorang. Secara umum, ketiga kasus pada bidang terapan berbeda tersebut memiliki urutan pengerjaan yang sama dalam menentukan koefisien fuzzy. Fuzzy regression models menjadi salah satu metode alternatif yang bisa digunakan untuk membangun sebuah model dari sebuah masalah.
Keyword: Model, Fuzzy, Fuzzy Regression Models

Judul: Improvement The Quality of Vanilla Trought Continued Sweating On The Drying Process Solar Dryer
Abstrak: Vanilla (Vanilla planifolia ) is one of the country's foreign exchange sources. Indonesia became the second largest vanilla producer in the world after Madagascar with a total production of 2,119 tons. Indonesia is also one of the vanilla exporter countries in the world whose export volume and value continues to grow. In 2019, the value of Indonesian vanilla export volume act to 261 tons with a sales value of S$ 69,610,000. Vanilla is exported to various countries in the form of whole, piece and ground (powder). The most vanilla export destination countries are USA, Canada, Japan, Australia and some of Europian countries such as Germany, France, Italy, and Netherlands. The problem faced in Indonesian vanilla exports is that there is a high difference in quality at the exporter level. This is caused by many factors, including harvesting age, curing process and the drying method. The curing and drying process determines the quality of vanilla. In the curing process, biochemical processes occur that cause quality changes in vanilla pod. The curing process in each vanilla producing country is developed in different ways, but in general the vanilla processing consists of four stages, namely killing, sweating, drying and conditioning, however this research is focused on the stage of sweating. In Indonesia, the drying process is done by sun drying, which takes a long time and produces low quality vanilla. Drying with a mechanical dryer (Green House Effect Solar Dryer) has been done so it can shorten the drying time, but the quality of the vanilla still does not meet SNI. Therefore, a proper curing process using a GHE dryer is required in order to obtain vanilla quality that meets SNI. This study aims to analyzed the effect of the sweating continued on the drying process with GHE drying method on the quality of vanilla. Vanilla that has been harvested as much as 30 kg was carried out killing process by soaking in the water at 60-65°C for 2 minutes. And then continued with the initial sweating process namely vanilla were wrapped in black clothes and stored in the styrofoam boxes for sweating process in the room temperature for 48 hrs. After that, the drying process was carried out with three different treatments namely GHE dryer with no sweating process (P1), drying with GHE dryer combined with sweating in the first two nights (P2), drying with GHE dryer combined with sweating in the first four nights (P3), and drying with sun drying of farmers produce (control). The quality parameters tested include size, weight loss, organoleptic tests (aroma and color), moisture content and vanillin content. Curing process treatment with sweating continued in the drying process using the green house effect solar dryer had a significant effect on weight loss, aroma and vanillin content but had no significant effect on color. Continued addition of sweating during the first nights of drying provides the best quality in vanillin content, color and aroma. Drying with green house effect solar dryer provided better quality results than traditional drying with a shorter drying time of 12 days, while traditional drying is
Keyword: quality, postharvest, sweating, drying, vanilla