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Bulletin of Information System Research
Published by CV. Graha Mitra Edukasi
ISSN : -     EISSN : 29632455     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Bidang Kajian dari jurnal Bulletin of Information System Research (BIOS), pada bidang ilmu komputer diantaranya, yaitu: Sistem Pendukung Keputusan Kecerdasan Buatan Data Mining Sistem Informasi Manajemen Informatika Sistem Pakar Big Data Text Mining
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol 1 No 1 (2022): Desember 2022" : 5 Documents clear
Penerapan K-Means Clustering Dalam Menentukan Banyaknya Desa/Kelurahan Menurut Keberadaan dan Jenis Industri Kecil dan Mikro (Desa) Fira Fania; Agus Perdana Windarto; Dedy Hartama
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

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Abstract

Processing Industry is an economic activity that carries out activities to change a basic item mechanically, chemically, or by hand so that it becomes finished / semi-finished goods, and or goods of less value to goods of higher value, and which are closer to the end user. This study aims to model the grouping in determining the Number of Villages / Villages According to the Existence and Types of Small and Micro Industries (Villages). This research is a reference, especially for the government, so that the potential for employment in this industry group can continue to be developed and optimized. Government contributions can be realized through the creation of stable social, economic and political conditions and through the policy of determining the direction of business development of Micro and Small Industries. The data from this study were taken from a government statistical data provider website, BPS (Statistics Indonesia) www.bps.go .id. This research uses the K-Mens method and is tested with RapidMiner software to create 3 clusters, namely high, medium and low level clusters and see what the contents of the cluster are. From the research results obtained by high cluster data centroids namely ((2151.79), ( 1494.34), (1135.76), moderate clusters ((406.64), (525.06), (616,218), and low clusters ((455,361), (345,523), (1074.09), (176,434), (1410,34), (243,749), (295,151), (463,266), (5868,13), (9344.07), (170,925), (8818,85), (1031,65), (433,61), (5985,505), (1630,75), (367,928), (119,082), (560,907), (172,333), (545,342), (226,174), (776,643), (1880,857), (172,333), (545,342), (226,174), (776,643), (1880,853), (1880,853), (18,80,853), (1880,853), (1880,853), (1880,853), (1880,853), (1880,853) ), (1482.39), (115,573), (232,734), (187.04), (142,884), (455,674), (441,934) With this analysis expected to be input and information for the government of each region to pay more attention to regions micro / small industrial areas occupying low clushter (C1) positions in order to improve industrial quality in the region.
Implementasi Algoritma Winnowing Pada Aplikasi Ensiklopedia Alam Syaiful Syaiful
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

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Abstract

Encyclopedia is a summary that contains information on the field of science being discussed. Nature is everything that exists on this earth, be it geology or the living things in it. But in this modern era, there is still no special application that helps to access knowledge and information related to nature. Searching for information about nature through browsing has to go through different web pages, this is not very effective because it takes time and is certainly not efficient. The solution to the problem is with the Natural Encyclopedia search application which uses a string matching algorithm, which is an algorithm that can search for words (patterns) in a text sentence (string) to find a word and display a word found in the text. Winnowing algorithm is used in similarity detection using hashing function. Winnowing is an algorithm used to perform the document fingerprinting process.
Pendeteksi Untuk Tingkat Kemiripan Kata Pada Karya Tulis Ilmiah dengan Menggunakan Metode Nazief Adriani Arni Damayamti
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

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Abstract

Scientific writing is a written work that is used to solve problems with scientific methods in which it presents opinions, observations, facts, data, which will produce a written report carried out by a person or in a team by meeting ethical and scientific rules properly. and right. An essay or writing obtained in accordance with its scientific nature and based on the results of observation, review, research in a particular field, compiled according to a certain method with systematic writing in a polite language and its contents can be accounted for for its truth/scientific nature. With the development of communication and information technology that is increasingly rapidly causing the search for information and data is very easy and fast. However, with the development of this technology also causes various negative impacts such as word plagiarism. This study also aims to find the similarity of words or similarity to break words between the input word and the source word. The resemblance is not a synonym, but a word that is close to the actual word, Simmilarity is a very important issue in almost every field of knowledge. The function of Simmilarity is to look for word similarity and word dissimilarity between two observed objects. So with the Nazief-Adriani algorithm, which is used to find basic words in a sentence to be better, the Nazief-Adriani stemming algorithm produces better accuracy when compared to other algorithms because it is caused by various kinds of word variations and combinations of affixes that must be removed for the sake of to get the root word
Data Mining Sistem Stock Opname Bahan Baku Catering Makanan Sehat Menggunakan Metode Min Max Stock Chyntia Kesuma; Efori Buulolo; Hukendik Hutabarat
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

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Abstract

Competition in today's business world is increasing, there are more and more innovations made by every entrepreneur to increase sales of the products they make so that they can be accepted in the market and in the community. One of them is Healthy Food Medan, a company engaged in healthy food catering. In making healthy food, it is necessary to stock up on good raw materials, so that one day the company does not lack stock of raw materials. Healthy Food Medan itself will not be separated from the so-called stock taking of raw materials. Of course, it is very interesting to be used as research material. Because of this, a computer program was created to determine the stock of raw materials so that there is no shortage of raw materials. In the application with the Min-Max method, it is expected that the user will no longer have difficulties in terms of stock of raw materials. The Min-Max method itself is a method that determines the maximum amount of inventory and minimum inventory so that there are no shortages and excess goods. Aims to avoid excess and shortage of raw materials by calculating the amount of raw material inventory
Implementasi Algoritma K-Nearest Neighbor(K-NN) Dalam Klasifikasi Kredit Motor Efori Bu’ulolo; Irma Suryani Tampubolon; Christin Vebiola Nababan; Lulu Nurhidayanti Nasution
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

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Abstract

Determining the eligibility of applying for a motorbike loan to a leasing company is important, considering that if an error in decision making occurs it will have an impact on the loss of the FIF Group company. Therefore the authors created a Decision Support System using the K-nearest Neighbor method to determine the feasibility of applying for a motorcycle loan. The K-Nearest Neighbor (K-NN) algorithm is an algorithm in data mining to classify new objects based on the majority of the nearest neighbor categories. The K-NN clustering algorithm using data on income, employment, number of dependents and home ownership can group prospective new creditors to make it easier for staff to determine acceptance of prospective new motorcycle creditors

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