scholarly journals PROPAGASI BALIK MENENTUKAN PREDIKSI PRODUKSI USAHA SONGKET SILUNGKANG KOTA SAWAHLUNTO

2018 ◽  
Vol 6 (2) ◽  
pp. 69
Author(s):  
Rima Liana Gema ◽  
Devia Kartika
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Small And Medium Enterprises ◽  
Cell System ◽  
City Government ◽  
Export Market ◽  
West Sumatra ◽  
Artificial Neural ◽  
The Government ◽  
Medium Enterprises

Artificial Neural Networks is a computational paradigm in which the way it works mimics the biological nerve cell system based on the characteristics of the function of the human brain. One method used in Artificial Neural Networks is a backpropagation algorithm that is widely used, especially in dealing with the problem of identification, prediction, recognition of complex patterns because this method is able to predict what will happen in the future based on patterns that existed in the past. Songket is one of the works of skilled hands of the original Silungkang craftsmen, Sawahlunto City, West Sumatra who have varied and unique patterns and motifs. Sawahlunto City Government, West Sumatra prioritizes the development of Silungkang songket craft business, which is a regional specialty, to enter the export market. At the initial stage, the regional government's priority is to increase the production of crafters by facilitating the development of micro, small and medium enterprises (MSMEs), especially those engaged in songket, to continue to be developed by improving quality and creativity. The city of Sawahlunto can help several parties such as the government, micro, small and medium enterprises in making good handling and decision making efforts to increase the production of Songket Silungkang MSMEs in Sawahlunto City.  

Analisis Dampak Toko Modern Terhadap Keberadaan Usaha Mikro, Kecil, Menengah Di Kota Padangsidimpuan

2021 ◽  
Vol 4 (1) ◽  
pp. 208
Author(s):  
Rahmat Kurniawan ◽  
Azhar Azhar
Keyword(s):  
Human Resources ◽  
Negative Impact ◽  
Positive Impact ◽  
Small And Medium Enterprises ◽  
City Government ◽  
Banking Institutions ◽  
The Government ◽  
Medium Enterprises ◽  
Role Of The Government

This research is to find out the perceptions of micro, small and medium enterprises to modern stores, MSME partnerships with modern stores, constraints, and the role of the government in overcoming the problems of modern shops and MSMEs in Padangsidimpuan City. This research is a descriptive qualitative study by conducting in-depth interviews. The results showed the perception of MSMEs towards modern stores had a negative and positive impact. The negative impact, the income of MSMEs has decreased. The positive impact, the presence of modern stores motivates MSMEs to evaluate themselves from modern stores. The partnership established by MSMEs with modern stores is the use of business locations provided by modern stores. The constraints of MSMEs are business capital, human resources, business legality, business permits and products, while the constraints of modern stores are business permits, human resources and partnerships with MSMEs. The role of the City Government of Padangsidimpuan is for modern stores, namely to give an appeal not to add to modern store outlets and to call for partnerships in terms of marketing local MSME products. For MSMEs, facilitate MSMEs with banking institutions in terms of providing venture capital, training and guidance to MSMEs, and making packaging houses.

PREDIKSI PERTUMBUHAN PENDUDUK PADA PROVINSI SUMATERA BARAT DENGAN MENGGUNAKAN METODE BACKPROPAGATION

2020 ◽  
Vol 7 (4) ◽  
pp. 216
Author(s):  
Hijrah Yanti Sitanggang ◽  
Vera Irma Delianti
Keyword(s):  
Neural Networks ◽  
Growth Rate ◽  
Artificial Neural Networks ◽  
Population Growth ◽  
Population Growth Rate ◽  
Backpropagation Neural Networks ◽  
West Sumatra ◽  
Artificial Neural ◽  
The City

The problem of population is one of the problems in the Province of West Sumatra, especially in the City of Padang, Kota Bukitinggi, and the City of Payakumbuh which has a very fast population growth rate, this occurs due to several factors such as births, deaths, residents who come, and residents who leave. The highest population growth occurred in Padang City in 2018 amounting to 939,112 residents and the smallest population growth occurred in the City of Bukitinggi in 2014 amounting to 120,491 residents. The purpose of this study is to predict population growth that will occur in 2019 in the cities of Padang, Bukittinggi and Payakumbuh. The method used in this research is descriptive correlational by applying backpropagation neural networks. The application used is Matlab. Based on the problems and methods obtained, the predicted results in 2019 in Padang City amounted to 124,7150, Bukittinggi numbered 126,8040 and Payakumbuh totaled 128.7830.  Keywords: Artificial Neural Networks, Backpropagation, Matlab.

Analisis Dampak Toko Modern Terhadap Keberadaan Usaha Mikro, Kecil, Menengah Di Kota Padangsidimpuan

2019 ◽  
Vol 4 (1) ◽  
pp. 208
Author(s):  
Rahmat Kurniawan ◽  
Azhar Azhar
Keyword(s):  
Human Resources ◽  
Negative Impact ◽  
Positive Impact ◽  
Small And Medium Enterprises ◽  
City Government ◽  
Banking Institutions ◽  
The Government ◽  
Medium Enterprises ◽  
Role Of The Government

This research is to find out the perceptions of micro, small and medium enterprises to modern stores, MSME partnerships with modern stores, constraints, and the role of the government in overcoming the problems of modern shops and MSMEs in Padangsidimpuan City. This research is a descriptive qualitative study by conducting in-depth interviews. The results showed the perception of MSMEs towards modern stores had a negative and positive impact. The negative impact, the income of MSMEs has decreased. The positive impact, the presence of modern stores motivates MSMEs to evaluate themselves from modern stores. The partnership established by MSMEs with modern stores is the use of business locations provided by modern stores. The constraints of MSMEs are business capital, human resources, business legality, business permits and products, while the constraints of modern stores are business permits, human resources and partnerships with MSMEs. The role of the City Government of Padangsidimpuan is for modern stores, namely to give an appeal not to add to modern store outlets and to call for partnerships in terms of marketing local MSME products. For MSMEs, facilitate MSMEs with banking institutions in terms of providing venture capital, training and guidance to MSMEs, and making packaging houses.

scholarly journals MODEL JARINGAN SYARAF TIRUAN MEMPREDIKSI PRODUKSI EKSPOR BATU BARA MENURUT NEGARA TUJUAN UTAMA DALAM MENDORONG LAJU PERTUMBUHAN EKONOMI

2019 ◽  
Vol 6 (2) ◽  
pp. 184
Author(s):  
Rafiqa Dewi ◽  
Sundari Retno Andani ◽  
Solikhun Solikhun
Keyword(s):  
Economic Growth ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Fossil Fuels ◽  
Agricultural Sector ◽  
General Definition ◽  
Architectural Models ◽  
Artificial Neural ◽  
Input Variables ◽  
The Government

<p><em>Prediction is a process for estimating how many needs in the future. This study aims to predict the amount of coal exports according to the country the main goal in driving the pace of economic growth. The role of the agricultural sector in the national economy is very important and strategic. Coal is one of the fossil fuels. The general definition is a sedimentary rock that can burn, formed from organic deposits, mainly the remains of plants and formed through the process of pembatubaraan. The main elements consist of carbon, hydrogen and oxygen. Domestic production makes the government continue to implement coal export policies according to the state's main goal in driving the pace of economic growth in Indonesia. By using Artificial Neural Networks and backpropagation algorithms, architectural models will be sought to predict the amount of coal exports according to the state's main goal in driving the pace of economic growth to determine steps to assist the government in exporting coal based on the main destination country. This study uses 12 input variables with 1 target. Using 4 architectural models to test the data to be used for prediction, namely models 12-8-1, 12-16-1, 12-32-1 and 12-64-1. The best architectural model results obtained are 12-16-1 architectural models with 100% truth accuracy, the number of epoch 2602 and MSE is 0.0032. By using this model, predictions of coal exports are in accordance with the main destination countries with 100% accuracy.</em></p><p><em></em><strong><em>Keywords: </em></strong><em>Coal, Exports, predictions, backpropagation, Artificial Neural Networks</em> </p><p><em>Prediksi adalah proses untuk memperkirakan berapa banyak kebutuhan di masa depan. Studi ini bertujuan untuk memprediksi jumlah ekspor batubara menurut negara tujuan utama dalam mendorong laju pertumbuhan ekonomi. Peran sektor pertanian dalam ekonomi nasional sangat penting dan strategis. Batubara adalah salah satu bahan bakar fosil. Definisi umum adalah batuan sedimen yang dapat terbakar, terbentuk dari endapan organik, terutama sisa-sisa tanaman dan terbentuk melalui proses pembatubaraan. Unsur utama terdiri dari karbon, hidrogen, dan oksigen. Produksi dalam negeri membuat pemerintah terus menerapkan kebijakan ekspor batubara sesuai dengan tujuan utama negara dalam mendorong laju pertumbuhan ekonomi di Indonesia. Dengan menggunakan Jaringan Saraf Tiruan dan algoritma backpropagation, model arsitektur akan dicari untuk memprediksi jumlah ekspor batubara sesuai dengan tujuan utama negara dalam mendorong laju pertumbuhan ekonomi untuk menentukan langkah-langkah untuk membantu pemerintah dalam mengekspor batubara berdasarkan negara tujuan utama . Penelitian ini menggunakan 12 variabel input dengan 1 target. Menggunakan 4 model arsitektur untuk menguji data yang akan digunakan untuk prediksi, yaitu model 12-8-1, 12-16-1, 12-32-1 dan 12-64-1. Hasil model arsitektur terbaik yang diperoleh adalah model arsitektur 12-16-1 dengan akurasi 100%, jumlah zaman 2602 dan MSE adalah 0,0032. Dengan menggunakan model ini, prediksi ekspor batubara sesuai dengan negara tujuan utama dengan akurasi 100%</em>.</p><p><strong><em>Kata kunci:</em></strong><em> Batubara, Ekspor, prediksi, backpropagation, Jaringan Syaraf Tiruan</em></p>

scholarly journals Development of GIS for Buildings in the Customary Village of Minangkabau Koto Gadang, West Sumatra, Indonesia

2020 ◽  
Vol 9 (6) ◽  
pp. 365 ◽  
Author(s):  
Surya Afnarius ◽  
Masril Syukur ◽  
Eri Gas Ekaputra ◽  
Yolanda Parawita ◽  
Ridho Darman
Keyword(s):  
Literature Review ◽  
Software Development ◽  
Small And Medium Enterprises ◽  
Residential Buildings ◽  
Aerial Photographs ◽  
It Services ◽  
West Sumatra ◽  
The Government ◽  
Medium Enterprises ◽  
The Village

Indonesia aims to strengthen its local regions and villages. This has led to the encouragement of smart village development through several forms of assistance, including Information Technology (IT) services from the government. Koto Gadang, one of the many Minangkabau customary villages in West Sumatra, has been used as a model for the development of an IT service that can support tourism known as a Web- and mobile-based geographic information system (GIS) for buildings (GB) in order to map and visualize buildings and their inhabitants. This paper reports the development of the GB. This study takes the form of a literature review, a survey, data collection, and software development. The results of the literature review and survey were used as the basis for software development. Aerial photographs of micro, small, and medium enterprises (MSMEs), mosques, offices, schools, and health service centers, as well as residential buildings, were taken using a drone, while attribute data were collected directly by visiting the buildings. The users of the GB were divided into two groups: visitors and village officers. Moreover, there confidentiality was maintained for all the data provided, so the visitors were only allowed to search for buildings (MSMEs, offices, mosques, schools, and health centers) based on certain criteria, view locations, found information, and survey routes, while village officers were allowed to collect data on residents, buildings, and houses, and also search people’s homes. Furthermore, in situations where a visitor needs to find a resident’s house, the village officers are required to provide this assistance. These provisions were applied in the GB and implemented using the PostgreSQL/PostGIS database, PHP, CSS Bootstrap, jQuery, and Basic4Android, created according to the needs of the Koto Gadang smart customary village. The GB allows the village officers to better understand and monitor all the buildings, houses, and residents in the village and could also encourage many travelers to visit and see historic buildings and shop for embroidery and silver crafts.

scholarly journals Decision on Halal Certification of Food and Beverage Products Processed by UMKM Products in Tangerang City - Study of Religiosity, Regulation, and Branding

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Aulia Ramadhan ◽  
Edy Yusuf Agung Gunanto
Keyword(s):  
Manufacturing Industry ◽  
Service Sector ◽  
Small And Medium Enterprises ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
City Government ◽  
Primary Data ◽  
Food And Beverage ◽  
The Government ◽  
Medium Enterprises

The city of Tangerang with the motto akhlakul karimah and the majority of the population is Muslim, which is 1,587,270 or 88.25%, so it pays great attention to the halalness of the products in circulation. The government requires that every product that enters, circulates, and is traded in the territory of Indonesia must be halal certified, including products of Micro, Small, and Medium Enterprises (MSMEs). There are 11,746 MSMEs in Tangerang City and the leading sectors that can be developed are the service sector and manufacturing industry. This study aims to determine the effect of economic factors, religiosity, socio-culture, regulation, and branding on the decision of MSMEs to carry out halal certification. This study uses primary data with a data collection method in the form of a questionnaire. The population in this study is UMKM which has been halal certified with the facilitation of the Tangerang City Government in 2019. The population is 100 MSMEs and 80 MSMEs are sampled. This study uses multiple linear regression analysis is processed using SPSS version 22. The results of the analysis of this study indicate that the most dominant variable partially has a positive and significant effect on the decision of MSMEs to carry out halal certification is branding. This proves that the halal label can be used as a good image for MSMEs to consumers. The variables that partially have a positive and significant effect on the decision of MSMEs to carry out halal certification, then, are religiosity and regulation. Meanwhile, the socio-culture and economy partially do not affect the decision of MSMEs to carry out halal certification. Simultaneously, the results obtained are that economy, religiosity, socio-culture, regulation, and branding affect the decision of MSMEs to carry out halal certification.

scholarly journals Analisis Perbandingan Metode LVQ Dan Backpropagation dalam Penentuan Keaslian Uang Kertas Rupiah Berbasis Parameter HSV

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
I Gusti Ayu Agung Diatri Indradewi ◽  
I Ketut Widhi Adnyana
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Color Space ◽  
Neural Network Learning ◽  
Hsv Color Space ◽  
The Public ◽  
Paper Money ◽  
Technological Developments ◽  
Artificial Neural ◽  
The Government

The high demand of the community for money that causes crime is the circulation of fake paper money. Counterfeit money if shared has the same physical as the original money issued by Bank Indonesia. To avoid the public accidentally transacting using counterfeit money, the government has actually socialized the 3D method (Seen, Diraba, and Diterawang). However, along with technological developments, the technique of making counterfeit money will also require the development of alternative techniques that can be used to help save fake money. Determining the authenticity of Rupiah banknotes can be done using pattern classification methods, one of which can be accommodated by artificial neural networks. LVQ neural network (Learning Vector Quantization) and Backpropagation are two types of artificial neural networks that do supervised learning. Extraction of features that show the authenticity of banknotes can be done using the HSV color space. This color space consists of components H (Hue), S (Saturation), and V (Value). This is the background of the topic chosen for analysis choosing the LVQ and Backpropagation methods in determining the authenticity of Rupiah banknotes based on HSV parameters. Evaluation analysis taken from the level assessment The evaluation results using the composition of the test data consisting of 10 original money images and 8 original money images obtained results both LVQ and Backpropagation networks were able to classify real and fake money images with 100% acquisition rates. However, when viewed from the MSE value, the LVQ network has a better performance with the supporting MSE value being 0. The test results from the preparation time, the Backpropagation network requires a shorter time compared to the LVQ network.

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