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PENERAPAN METODE FUZZY TSUKAMOTO DALAM PENENTUAN JUMLAH PRODUKSI ROTI (STUDI KASUS: DWI JAYA BAKERY KUPANG) Yunni Alvionita Adoe; Kornelis Letelay; Emerensye Sofia Yublina Pandie
JURNAL DIFERENSIAL Vol 4 No 1 (2022): April 2022
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v4i1.6790

Abstract

Dwi Jaya Bakery is a private business engaged in the production of food and bread. There are 4 types of bread in production that is: Small Chocolate Bread, Mocca Small Bread, Large Chocolate Fried Bread and Large Abon Bread. In this study the author applies the fuzzy tsukamoto method to determine the amount of bread production with 3 calculation stages is defining variables, inference and affirmation (defuzzification). The input variables used are demand and stock as well as the output variable is the amount of production. Production data obtained from Dwi Jaya Bakery industry is data from September 2018 - February 2019. For testing, the data used are 28 data for each type of bread is on the 1st to the 28th of february 2019, which has been added to the transformation equation and tested using the MAPE (Mean Absolut Percentage Error) where the error value will be searched for data on each type of bread. The error value obtained by applying the testing MAPE test method that has been added to the transformation equation for the type of small chocolate bread is 1,936786%, mocca small bread is 6,209643%, large chocolate fried bread is 3,886071% and large abon bread is 6,646429%.
Implementasi Algoritma K-Means untuk Mengenali Pola Jemaat dalam Kegiatan Pelayanan Gereja Emerensye Sofia Yublina Pandie; Tiwuk Widiastuti; Adi Sebastianus Molla; Bertha Selviana Djahi
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 2 (2019): Oktober 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i2.1679

Abstract

Gereja adalah sebuah institusi yang tidak hanya mengelola kerohanian jemaatnya, namun juga merupakan wadah organisasi yang mengayomi dan melindungi jemaat serta menjamin keberlangsungan kehidupan sosial masyarakat jemaatnya. Data statistik juga menunjukkan jumlah pemeluk agama Kristen Protestan di kota Kupang mencapai angka 209.438 orang atau sebanyak 61,08% dari jumlah total penduduk di kota Kupang. Jumlah gereja Kristen Protestan sebanyak 150 gereja sehingga diasumsikan setiap gereja memiliki jemaat rata-rata 1.396 jemaat per gereja. Data mining merupakan proses yang mempekerjakan satu atau lebih teknik pembelajaran komputer (machine learning) untuk menganalisis dan mengekstrasi pengetahuan sehingga didapat pola tertentu. Penelitian ini akan mengimplementasikan algoritma data mining K-Means Clustering untuk mengenali pola jemaat yang menjadi salah satu target kegiatan pelayanan gereja yaitu jemaat yang belum dibaptis padahal sudah melewati usia baptis pada umumnya sebanyak . Luaran utama yaitu berupa rumusan/pola jemaat dan hasil rumusan itu akan dipakai oleh pihak gereja untuk melakukan pendekatan kepada jemaat dengan ciri/pola tersebut.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN LOKASI LAHAN PERTANIAN UNTUK BUDIDAYA TANAMAN JERUK KEPROK MENGGUNAKAN FUZZY MULTI ATRIBUTE DECISSION MAKING (FMADM) DAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) Leonardus Naben; Kornelis Letelay; Emerensye Sofia Yublina Pandie
J-Icon : Jurnal Komputer dan Informatika Vol 8 No 2 (2020): Oktober 2020
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v8i2.2884

Abstract

In commodity, oranges is one fruits that have benefit to be organized. The agribusiness of orange could increase farmers’ prosperity if it organized wholeheartedly. Besides, it is not only expand thereigional economic matters but also increasing the national emolument. Nowadays, the determining area of cultivation of oranges in TTS regency still did in manual way. occasionally, the farmers constrain the land utilizing of citrus fruit. The exposure of the land in the inappropriate area can lead the costs to be more expensive than the percentage agricultural commodities in the future. The Agriculture Department still estabish the location manually, so the information of decission support system of ariculture area is less accurate. That is why the use of FMADM decission support system and SAW method very precise to implement in this case. This research use 7 criteria rain, temperature, drainae, pH H2O, texture of land, and slope. The comparing of manual computation and system computation by examination system. The results are same but the outcome of the system is better than manually. In measuring the importance of weight use sensititifity examine of weight repair with 10 data location that found by the researcher in BPTP East Nusa Tenggara. The result found the more sensitive criteria is slope which has sensitive levels 60%. Finally, after the system result add 0.5 and 1, show contrast result of rank of the data. The data analyze found the system extend better result.
PEMBOBOTAN DINAMIS BERBASIS POSISI PADA APPROXIMATE STRING MATCHING Sebastianus A S Mola; Meiton Boru; Emerensye Sofia Yublina Pandie
J-Icon : Jurnal Komputer dan Informatika Vol 9 No 2 (2021): Oktober 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i2.5149

Abstract

Written communication in social media that emphasizes the speed of information dissemination, the phenomenon of using non-standard language often occurs at the level of sentences, clauses, phrases and words. As a source of data, social media with this phenomenon presents challenges in the process of extracting information. Normalization of non-standard language into standard language begins in the word normalization process where non-standard words (NSW) are normalized to standard forms (standard words (SW)). The normalization process using edit distance has limitations in the process of weighting the static mismatch, match, and gap values. In calculating the mismatch value, statida weighting cannot provide a weight difference due to incorrect keystrokes on the keyboard, especially adjacent keys. Due to the limited edit distance weighting, this research proposes a dynamic weighting method for mismatch weights. The result of this research is that there is a new method of dynamic weighting based on the position of the keyboard keys that can be used to normalize NSW using the approximate string matching method.