Generalized Model and Optimal Solution of Internet Pricing Scheme in Single Link Under Multiservice Networks

In this paper, we will analyze the internet pricing scheme under multi service network by generalizing the model into 9 services. The scheme is determined from the base price, quality premium and number of links to aid the internet service provider to maximize the profit and to serve better service to the customers. The objective function is generated by setting up the base price and quality premium as a constant or variable. We use nonlinear optimization model and solve it by using LINGO 11.0 to obtain the optimal solution. The results show that for each case by generalizing the model, the ISP obtains better solution by fixing the base price and fixing and varying the quality premium. ISP has a choice to adopt the model when ISP fixes the base price and also fix or vary the quality premium with maximum profit adopted by ISP is when fixing the base price and varying the premium quality

Generalized Model and Optimal Solution of Internet Pricing Scheme in Single Link under Multiservice Networks

In this paper, we will analyze the internet pricing scheme under multi service network by generalizing the model into 9 services. The scheme is determined from the base price, quality premium and number of links to aid the internet service provider to maximize the profit and to serve better service to the customers. The objective function is generated by setting up the base price and quality premium as a constant or variable. We use nonlinear optimization model and solve it by using LINGO 11.0 to obtain the optimal solution. The results show that for each case by generalizing the model, the ISP obtains better solution by fixing the base price and fixing and varying the quality premium. ISP has a choice to adopt the model when ISP fixes the base price and also fix or vary the quality premium with maximum profit adopted by ISP is when fixing the base price and varying the premium quality

Optimization of Wireless Internet Pricing Scheme in Serving Multi QoS Network Using Various Attributes

Pricing scheme in wireless networks were developed to provide maximum benefit to the internet service provider (ISP), where the given scheme can guarantee customer satisfaction and service providers who use such services. So that the proposed model should be able to attract consumer interest in applying such services. In this research we established wireless pricing model that involve QoS attributes then the model will be transformed into a model of optimization. Pricing models in wireless networks will be studied by looking at existing models as a nonlinear programming problem that can be solved optimally using LINGO 11.0. The solution is to maximize the total price for the connection based on the QoS parameters. Optimal results in the maximizing of pricing scheme is achieved when providers set the increase of price changes due to QoS changes and number of QoS value

PROFIL PENGRAJIN SONGKET DI DESA LIMBANG JAYA I KECAMATAN TANJUNG BATU KABUPATEN OGAN ILIR PROVINSI SUMATERA SELATAN

Tulisan ini bertujuan untuk menganalisis profil pengrajin songket di Desa Limbang Jaya I ditinjau dari faktor sosial demografi, pendapatan rata-rata per bulan, dan produktivitas pengrajin. Produktivitas yang diteliti meliputi rata-rata jumlah helai songket yang dihasilkan dalam 1 bulan, rata-rata lama waktu kerja (menenun) per hari, rata-rata lama pengerjaan 1 kain, dan jumlah motif songket yang dapat dibuat. Berdasarkan penelitian lapangan, pengrajin songket Desa Limbang Jaya I mayoritas berumur 28-41 tahun, berstatus menikah dengan suami mayoritas berprofesi sebagai pengrajin pandai besi. Pengrajin juga berpendidikan rendah dan sudah menjalani profesi sebagai pengrajin selama 21-30 tahun. Hasil tenunnya rata-rata 3-4 helai per bulan dengan jam kerja per hari 3-8 jam dan lama pengerjaan 1 kain rata-rata 7-10 hari. Pendapatan bersih per bulan dari pengrajin rata-rata kurang dari Rp 1.000.000,-. Hasil dari analisis biplot yang tingkat representatifnya sebesar 53,9% menunjukkan bahwa pendapatan pengrajin songket Desa Limbang Jaya I lebih dipengaruhi oleh jumlah kain yang dihasilkan, dan tidak/kurang dipengaruhi oleh kemahiran (penguasaan variasi motif), umur, pengalaman kerja sebagai penenun, jam kerja, dan tingkat pendidikan. Lama pengerjaan kain berpengaruh secara negatif terhadap pendapatan

Nonlinear Programming Approach of Wireless Pricing Models

The pricing for wireless networks is developed to obtain surplus from subscribers. The linearity factors, elasticity price, price factors are discussed. the new approach of wireless pricing model proposed by previous research are approached by considering the model as the nonlinear programming problem that can be solved optimally using LINGO 13.0.  The problem is considered to be nonlinear programming that can be solved using optimization tools. The solutions are expected to give some information about the connections between the acceptance factor and the price. The models attempt to maximize the total price for a connection based on QoS parameter. The maximum goal to maximum price is achieved when the provider set the increment of price change due to QoS change and amount of QoS value. The linearity parameter set up for most cases is obtained in ceiling value. Linear price factor ranges between the prescribed value especially cases when we increase the price change due to QoS change and increase the amount of QoS values

APPLICATION OF TWO GROUPS ANALYSIS AND CLUSTER ANALYSIS ON COMPARISON OF CHARACTERISTICS OF PAGARALAM COFFEE FARMERS CATEGORIES

Land care is one of the factors that must be considered in the sustainability of coffee production. A small number of Pagaralam coffee farmers know and apply reductant herbicide in weed control. This study aims to compare the characteristics of Pagaralam coffee farmers based on the use of reductant herbicide by using two groups analysis and cluster analysis. The characteristics of the farmers studied included 17 variables on 165 respondents who were selected by purposive sampling. The variables studied include land productivity and farmers' income. Respondents were divided into 2 categories, namely users and non-users of reductant herbicide. The initial stages of data processing in the form of descriptive statistics, hypothesis testing by mean difference test, correlation between variables, Principal Component Analysis, and biplot analysis. According to the results of the two groups analysis and cluster analysis, the variables dominantly tend to characterize the similarity in comparison between the categories of non-users and users are the variables that join into one cluster, namely land area, number of trees, coffee bean production, estimated yield, total harvest, Gross income, and Net income. While the variables that dominantly characterize the dissimilarity between the two categories are the variables that form 5 separate clusters, namely the clusters of plantation productivity, respondent identity, education, tree age, and length of harvest period

REGRESSION MODEL ON PAGARALAM COFFEE FARMERS’ INCOME WITH THE INFLUENCE OF THE USE OF HERBICIDE REDUCTANT VARIABLE

The existence of weeds in coffee fields will become competitors for coffee plants, so that they can be economically and ecologically detrimental. Inappropriate use of chemical herbicides can have a negative impact. Herbicide reductants made from organic are used in weed control. This study aims to analyze the variables that affect the net income of Pagaralam coffee farmers using multiple linear regression analysis. One of these variables is a qualitative variable in the form of categories of respondents based on the use of herbicide reductants. The data used was obtained from  the results of questionnaires on 56 respondents who are users and 80 respondents who are not users of herbicide reductants. The results of the hypothesis test of mean difference found that the net income of the two respondent categories is not different. The regression analysis also resulted that there was no significant difference in net income between the two respondent categories. Variables that had a significant effect on net income included gross income, farming maintenance costs, estimated yields, and tree age. Several models also contain variables of land area, length of time in coffee farming, number of trees, and frequency of organic fertilizers used. Old coffee trees should be treated better with the use of organic fertilizers and also wise weed control techniques

CORRESPONDENCE ANALYSIS PADA HUBUNGAN FAKTOR-FAKTOR YANG MEMPENGARUHI PENDAPATAN PETANI KOPI PAGARALAM

Pagaralam is one of the coffee-producing districts in South Sumatra (Sum-Sel). Pagaralam coffee farming is a hereditary business, where the majority of land processing is still traditional. This is related to working capital and farmers' income. This study aims to analyze the factors that affect the income of Pagaralam coffee farmers by using correspondence analysis. There are 30 variables or factors studied. Each variable is divided into several categories. The categories of each variable are described graphically with the categories of income variable. Primary data were obtained from 196 respondents who were selected based on purposive sampling technique. There are 13 factors that affect the income of respondents, namely: number of dependents, number of trees, age of the trees, number of female workers from outside the family, frequency of fertilization, frequency of herbicide application, production of harvest, production outside of harvest, gross income, minimum price of coffee beans, the maximum price of coffee beans, economic status and land productivity. There are 8 of the 13 factors that predominantly characterize the profile of net income level of Pagaralam coffee farmers.  In general, the factor that must be considered in coffee farming is land productivity which is also related to production costs in land processing and crop production, as well as external factors regarding the market price of coffee

Analisis Cluster terhadap Tingkat Pencemaran Udara pada Sektor Industri di Sumatera Selatan

Analisis cluster merupakan suatu teknik yang dipergunakan untuk mengklasifikasikan objek ke dalam kelompok yang relatif homogen. Analisis cluster terbagi atas dua metode, hirarki dan non-hirarki. Penelitian ini dibahas pengelompokan 10 jenis industri yang ada di Sumatera Selatan berdasarkan jenis polutan yang dihasilkan dan mengetahui ciri-ciri setiap kelompok industri. Berdasarkan hasil analisis cluster metode hirarki, ada 3 kelompok industri (cluster). Cluster pertama yaitu industri karet, industri sawit, industri pengalengan ikan, industri listrik, industri pertambangan dan industri semen. Cluster kedua terdiri dari industri migas, industri minyak goreng dan industri makanan. Cluster ketiga yaitu industri pupuk. Pada metode non-hirarki, cluster pertama yaitu industri yang memiliki rata-rata polutan yang lebih besar dari pada cluster kedua, dapat digolongkan menjadi kelompok industri dengan tingkat pencemaran tinggi. Anggotanya adalah industri migas, industri minyak goreng, industri makanan dan industri pupuk. Cluster kedua yaitu industri yang memiliki rata-rata polutan yang lebih kecil dari pada cluster pertama, dapat digolongkan menjadi kelompok industri dengan tingkat pencemaran rendah. Anggotanya adalah industri karet, industri sawit, industri pengalengan ikan, industri listrik, industri pertambangan dan industri semen

Binary Logistic Regression Modeling on Net Income of Pagar Alam Coffee Farmers

Pagar Alam Coffee is a Besemah coffee originating from the Smallholder Plantation in South Sumatra, Indonesia. The majority of Pagar Alam coffee farming is a hereditary business. Coffee farmers' income is very dependent on coffee production, production costs, and coffee prices. This study aims to obtain a probability model of Pagar Alam coffee farmers income based on the factors that influence it. The independent variables studied were the number of dependents, economic conditions, number of trees, age of trees, frequency of fertilizer used, frequency of pesticide used, production at harvest time, production outside harvest time, number of women workers outside the family, minimum price of coffee, maximum price of coffee, farmers' gross income, and land productivity. Modeling used binary logistic regression method on 179 respondents. There were three methods used, i.e. enter method, forward and backward methods. The model using enter method results the greatest prediction accuracy which is 87.7%. The factors that have a significant influence on the net income of Pagar Alam coffee farmers are gross income, land productivity, and the number of women workers from outside the family. The most influential variable is gross income