Search

Vehicular networks are indistinguishable parts of a smart city condition because of a few applications that improve personal satisfaction, safety, and security. They additionally present a new scheme comprising a smart city structure that transmits data about traffic conditions that will assist the driver with making suitable choices. Cluster formation is achieved by utilizing the trust level of every vehicle and this trust degree is determined depending on the immediate and indirect trust level of every vehicle. Data of every vehicle is accumulated by the consequent cluster head (CH) in a cluster. This data is maintained by the Certificate Revocation List in the Certificate Authority. This procedure confines a vehicle in Smart Cities Transportation (SCT) as an attacked node if it has a lower trust degree than the limit trust worth and it negates the certificate of assaulted or revoked nodes. Prior to transmission, every vehicle in a cluster approves its certificate with the help of the Certificate Authority. After the approval, the other test of VANET, i.e., the proficient route, is set up with the goal of improving energy efficiency in OLSR routing protocol utilizing an artificial intelligence (AI)-based Particle Genetic Swarm (PGS) algorithm, as exhibited in this chapter. After the foundation of the proficient route, the vehicle sends a securable vehicle to vehicle or vehicle to roadside unit transmission. Simulation results demonstrated that the presentation of our proposed methodology beats the exhibition of existing work regarding energy efficiency.

The aim of this study is predicted 200.000 cases of Covid-19 in Spain. Covid-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 – 17 April 2020. The data from 01 March 2020 – 10 April 2020 using to fitting with data from 11 April – 17 April 2020. For the evaluation of the forecasting accuracy measures, we use mean absolute percentage error (MAPE). Based on the results of SutteARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 - 17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.

SutteARIMA to Forecast Artificial Data

This study aimed to predict the short-term of confirmed cases of covid-19 and IBEX in Spain by using SutteARIMA method. Confirmed data of Covid-19 in Spanish was obtained from Worldometer and Spain Stock Market data (IBEX 35) was data obtained from Yahoo Finance. Data started from 12 February 2020-09 April 2020 (the date on Covid-19 was detected in Spain). The data from 12 February 2020-02 April 2020 using to fitting with data from 03 April 2020 - 09 April 2020. Based on the fitting data, we can conducted short-term forecast for 3 future period (10 April 2020 - 12 April 2020 for Covid-19 and 14 April 2020 - 16 April 2020 for IBEX). In this study, the SutteARIMA method will be used. For the evaluation of the forecasting methods, we applied forecasting accuracy measures, mean absolute percentage error (MAPE). Based on the results of ARIMA and SutteARIMA forecasting methods, it can be concluded that the SutteARIMA method is more suitable than ARIMA to calculate the daily forecasts of confirmed cases of Covid-19 and IBEX in Spain. The MAPE value of 0.036 (smaller than 0.03 compared to MAPE value of ARIMA) for confirmed cases of Covid-19 in Spain and was in the amount of 0.026 for IBEX stock. At the end of the analysis, this study used the SutteARIMA method, this study calculated daily forecasts of confirmed cases of Covid-19 in Spain from 10 April 2020 until 12 April 2020 i.e. 158925; 164390; and 169969 and Spain Stock Market from 14 April 2020 until 16 April 2020 i.e. 7000.61; 6930.61; and 6860.62.

Dairy cattle milk cooperatives in East Java has been threatened to be failure in achieving the target of Milk Self-Capacity By 2020. The reason of this failure threat is low productivity among dairy cattle milk entrepreneurs. Productivity is closely related with performance of dairy cattle milk business units, but this performance is affected by factors such as organizational learning, market orientation and job satisfaction. The objective of this research is to understand the contribution of organizational learning and market orientation on business unit performance through mediation of job satisfaction. This research is designed to use quantitative approach. The causal relationship across research variables is examined with Structural Equation Modeling-Partial Least Squares (SEM-PLS). Research population is 52 dairy cattle milk cooperatives in East Java. Sampling method is simple random sampling, and after using this sampling to populaton, it results in a sample of 46 cooperatives. Data are collected through questionnaire. Questions on questionnaire are made and processed with Software SmartPLS Version 3.27. Research has given some results: (1) Organizational Learning and Market Orientation have a positive contribution to the increase of Job Satisfaction; (2) Organizational Learning and Market Orientation do not have a positive contribution to the increase of Business Unit Performance; and (3) Job Satisfaction has a positive contribution to the increase of Business Unit Performance at dairy cattle milk cooperatives in East Java.

Mathematical problem posing plays an important role in mathematics curriculum, since it encompasses the core of mathematics activities, among other things, with students’ activities to construct their own problems as the preliminary step to actual problem solving steps. This study aims at revealing the profile of students’ mathematical problem posing based on their cognitive styles in order to know and understand the learning of mathematics students. As a result of this study, students who have the cognitive style ‘field independent’ (FI) are able to propose a solvable mathematical problem and load new data, and also pose problems categorized as high-quality mathematical problems. Students who have the cognitive style of ‘field dependent’ (FD) are generally limited to solvable mathematical problems that do not contain new data, and mathematical problems of a moderate level. In this study, it is seen how student’s work mathematical problem posing using their cognitive style, resulting in a breakthrough in the process of learning to use students’ cognitive styles so as to increase the quality of learning outcomes.

This is a response to article by Dr. Ramadhan Tosepu and his colleagues entitled: “Correlation between the weather and the Covid-19 pandemic in Jakarta, Indonesia” in Science of The Total Environment, Vol. 725; and Dr. Muhammad Farhan Bashir and his colleagues entitled: “Correlation between the climate indicators and the Covid-19 pandemics in New York, USA.” in Science of The Total Environment, Vol. 728. We agree with the results of their research, but there are things that need to be clarified in relation to the selection of the Spearman-rank correlation as an analytical tool, because the selection of this analysis is without the normality test of the data. Spearman-rank correlation is useful for non-normally distributed continuous data; can be used for ordinal data; and is relatively robust for outliers.

The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of “A” on the Indonesia Stock Exchange (IDX or BEI) 29 November2006 until 20 September 2016 period. To see the performance of Sutte Indicator, other technical analysis are used as a comparison, Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). To see a comparison of the level of reliability prediction, the stock data were compared using the mean absolute deviation (MAD), mean of square error (MSE), and mean absolute percentage error (MAPE). The result of this research is that Sutte Indicator can be used as a reference in predicting stock movements, and if it is compared to other indicator methods (SMA and MACD) via MAD, MSE, and MAPE, the Sutte Indicator has a better level of reliability.

Economic growth is a process for change the economic condition a country or regional by continuously for the better condition as long as definite period. Economic growth in South Sulawesi for 2013-2016 have up and down because many factors have influence it. Like jobless, human capital index, regional revenue, expenditure, and total population. This research was conducted to determine the factors that influence economic growth in South Sulawesi by using data panel regression methods. Panel data regression is a regression by using panel data. Panel data is a statistics analysis method that combines between time series data and cross section data . The result indicates that the result if the regression analysis on the =5% show that the best panel data regression model is random effect model and human capital index variable have significant effect on economic growth with probability value about 0,0227. Meanwhile, jobless, regional revenue, expenditure, and total population no significant. Keywords : Panel Data Regression, Economic Growth, Common Effect Model, Fixed Effcet Model, Random Effect Model

Ketersediaan air bersih sangat penting dikarenakan hampir seluruh aktivitas manusia sangat bergantung terhadap ketersediaan air bersih. Hal ini membuat faktor produksi dan ketersediaan air bersih selalu menjadi prioritas dalam pelayanan penyaluran air bersih sehingga penulis tertarik untuk mengkaji tentang peramalan jumlah penggunaan air bersih di PDAM Kota Makassar. Salah satu metode yang cocok untuk menangani kasus tersebut adalah metode Time Series. Metode Triple Exponential Smoothing atau biasa disebut dengan Winter Exponential Smoothing merupakan salah satu metode Time Series yang cocok untuk menangani data yang bersifat musiman seperti jumlah penggunaan air bersih di Kota Makassar. Adapun Langkah analisis dari metode Triple Exponential Smoothing adalah identifikasi model, estimasi parameter dengan trial and error, selanjutnya adalah perhitungan nilai awal dari pemulusan data, trend, dan musiman dengan panjang satu musim L=12 dan yang terakhir adalah menghitung nilai error dengan menggunakan MAPE dan RMSE. Model terbaik diperoleh dari kombinasi parameter α = 0,1; β = 0,1; dan γ=0,6 yang menghasilkan kesalahan peramalan terkecil menggunakan RMSE dengan nilai sebesar 168,175 dan MAPE dengan nilai sebesar 4,736. Dengan meggunakan model maka diperoleh peramalan jumlah penggunaan air bersih di PDAM Kota Makassar dari bulan januari – desember 2019 sebagai berikut: 2779,10; 2788,94; 2728,61; 2797,48; 2787,97; 2752,66; 2742,18; 2708,50; 2644,55; 2521,50; 2537,74; 2732,55. Dari hasil peramalan tersebut terlihat mendekati dan tidak terlalu jauh menyimpang dari data tahun sebelumnya sehingga dapat dijadikan acuan produktivitas air bersih di PDAM Kota Makassar agar produktivitas air dapat mencukupi semua kebutuhan masyarakat di Kota Makassar.Kata kunci: air, triple exponential smoothing, time series, peramalan.

Nearest neighbor analysis merupakan sebuah metode analisis yang dapat digunakan untuk menentukan suatu pola penyebaran, apakah berpola seragam ( uniform ), acak ( random ), atau mengelompok ( cluster ). Nearest neighbor analysis dalam perhitungannya mempertimbangkan jarak, jumlah titik lokasi penyebaran, dadn luas wilayah, hasil akhir analisis ini berupa indeks tetangga terdekat (T) yang nilainya berkisar antara 0 sampai 2.15. Untuk menentukan faktor-faktor yang mempengaruhi pola penyebaran hunian, pada penelitian ini menggunakan analisis korelasi (r). Hasil dari penelitian ini berdasarkan perhitungan nearest neighbor analysis yaitu pola penyebaran hunian di Kota Kendari secara keseluruhan memiliki pola penyebaran yang cenderung berpola acak artinya jarak antara titik-titik penyebaran hunian tidak memiliki jarak yang sama, dan hasil dari perhitungan korelasi diperoleh faktor-faktor yang mempengaruhi pola penyebaran hunian yang cenderung berpola acak. Faktor yang paling berpengaruh dengan hubungan positif yaitu faktor pertumbuhan penduduk, hal ini dapat dilihat pada hasil korelasi dimana faktor pertumbuhan penduduk memiliki nilai korelasi tertinggi yaitu 0.618 dan faktor yang paling berengaruh dengan hubungan negatif yaitu faktor fasilitas Pendidikan hal ini dapat dilihat pada hasil korelasi dimana faktor fasilitas Pendidikan memiliki nilai korelasi negatif tertinggi yaitu -0.526. Keywords: Nearest Neighbor Analysis, Pola Penyebaran.

Discriminant analysis is a method in multivariat statistic analysis that related with object which have separated into the defined group defined and see the accuracy of the formed group. In this research, clustera analysis is used for the first grouping, cluster analysis is a statistical analysis which aims to classify some objects based on the characteristics similarity among the object. Data for this study is HDI (Human Development Index) of indicator in south sulawesi in 2016. The result of this research are 1st cluster (lower HDI indicator) which have 21 city/ distric and the 2nd cluster (higher HDI indicator) which have 3 city/distric as the closeness value between the cluster that formed is 0.902 which shows the closeness between the cluster is high . Furthermore, the discriminant function that have formed explains that if the life expectancy increase, the HDI indicator in city/distric in south sulawesi province will decrease but if school expectation duration in school , average of duration in school, and parity of pur hasing power is increasing, the HDI indicator in city/distric in aouth sulawesi will also increase.Keywords: Cluster analysis, Discriminant analysis , Human development index indicator.

In this study, modeling of mineral resources of underground water in karst mountain area of Maros-Pangkep, Indonesia was made by the Boltzmann lattice-gas automata method. This method was applied to solve the problem of groundwater flow by viewing them as a lattice gas. Simula tion models of groundwater flow in the form of 16 and 32 particle size with a barrier particles form a circle on the plate and different variations of time to reach steady its state. The simulation results showed that the greater the time duration, the mor e different fluid motion pattern. For the state of the karst region, this means that the heterogeneous medium karst very unstable and affect the movement of the particles. In addition, karstification process takes place in a relatively long time with adequate rainfall.

Authenticity of access in very information are very important in the current era of Internet-based technology, there are many ways to secure information from irresponsible parties with various security attacks, some of technique can use for defend attack from irresponsible parties are using steganography, cryptography or also use digital signatures. Digital signatures could be one of solution where the authenticity of the message will be verified to prove that the received message is the original message without any change, Ong-Schnorr-Shamir is the algorithm are used in this research and the experiment are perform on the digital signature scheme and the hidden channel scheme., 6 pages, Paper presented at the International Conference on Education and Technology (ICEduTech2017), Novotel Hotel, Balikpapan, Indonesia

This article reports on research that is aimed at developing and producing a self-learning model based on open-ended questions or the PMBST (accronym form Indonesian) model to increase students’ creativity in a calculus subject. The main product generated is a book on the PMBST model. It consists of: a) introduction; b) theoretical rationality; c) empirical rationality; d) supporting theories; e) components of the model; f) instructions for the model; and g) bibliography. Furthermore, to assess the quality of this model, the authors used product quality assessment criteria created by Nieveen, which covers hypothetical validity and practicality. The instrument, which is developed for supporting the PMBST model development cover: an assessment sheet of the PMBST model, and a validation format of the PMBST model assessment sheet. The subjects of the PMBST model in this research are Master’s programme students in the Mathematics Department at Universitas Negeri Makassar who have finished or are learning the calculus subject. The result of this research is the PMBST model developed with high theoretical rationality as indicated by experts’ assessments.

The purpose of this study was to develop Android-based teaching materials, which have qualities (valid, practical and effective) that can help to improve the quality of student learning outcomes and to motivate students to learn. The process of developing this material used the Plomp development model, which consists of a preliminary investigation phase, a design phase, a realisation/construction phase, a test, evaluation and revision phase and an implementation phase. To assess the quality of the learning device, the validity of the validator of experts was, then, tested in order to ensure that the teaching material is valid, practical and effective.

This study was a descriptive study using cross sectional design. The aims of this research were to examine the relationship between learning styles and learning outcomes by gender. The population in this study were all students in 1st year of SMAN 1 Galesong Selatan, Indonesia, in the 2014/2015 academic year. The instruments used in this research was the test of modalities learning styles (TMLS), to determine whether the students’ learning styles are visual, auditory and kinaesthetic (VAK), and documentation. The relationship between learning styles and learning outcomes were analysed with the chi-square test and two-way ANOVA. The results of this study showed that: 1) the learning styles of visual and auditory learning styles is dominated by women; and 2) there is no relationship between the variables of learning styles, genders and interaction of learning styles with genders to learning achievement.

Technical Indicator is an approach to analyze the movement of stock. Are this stock will decrease or increase in future? One new indicator that has been developed is Sutte Indicator. Sutte Indicator is an indicator used in Technical Analysis of Stock Market. Sutte Indicator developed by Ansari Saleh Ahmar in December 2015. Sutte Indicator helps in the decision making process for stock investors when they can make a buy or sale of stocks. Sutte Indicator has been implemented in several stocks such as Apple Inc., XL Axiata Tbk and Smartfren Telecom Tbk. To view the reliability in the prediction of Sutte Indicator then it compared with others Technical Analysis that is Simple Moving Average (SMA) and Moving Average Convergence / Divergence (MACD). From the results of this comparison, Sutte Indicator is obtained that has a level of accu-racy that is better than the SMA and MACD. To simplify the process of use of Sutte Indicator, then make a tools on Web-based platform and the named as SuIndiWeb. SuIndiWeb will be used in the process of pre-dicting stock movements.

The purpose of this study is to apply technical analysis e.g. Sutte Indicator in Stock Market that will assist in the investment decision-making process to buy or sell of stocks. This study took data from Apple Inc. which listed in the NasdaqGS in the period of 1 January 2008 to 26 September 2016. Performance of the Sutte Indicator can be seen with comparison with other technical analysis e.g. Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). Comparison of the reliability of prediction from Sutte Indicator, SMA, and MACD using the mean of square error (MSE), mean absolute deviation (MAD) and mean absolute percentage error (MAPE).

This research has a purpose to compare ARIMA Model and Holt-Winters Model based on MAE, RSS, MSE, and RMS criteria in predicting Primary Energy Consumption Total data in the US. The data from this research ranges from January 1973 to December 2016. This data will be processed by using R Software. Based on the results of data analysis that has been done, it is found that the model of Holt-Winters Additive type (MSE: 258350.1) is the most appropriate model in predicting Primary Energy Consumption Total data in the US. This model is more appropriate when compared with Holt-Winters Multiplicative type (MSE: 262260,4) and ARIMA Seasonal model (MSE: 723502,2).

Metode Vector Autoregressive adalah salah satu analisis yang digunakan untuk menganalisis data deret waktu (time series). Data deret waktu dapat dinyatakan dalam tahun, bulan, minggu, atau hari. Salah satu tujuan penelitian adalah untuk mengetahui pengaruh antara indeks perekonomian suatu negara khususnya pengaruh Kurs, Inflasi dan Suku Bunga terhadap Indeks Harga Saham Gabungan. Data yang digunakan dalam penelitian ini adalah data Kurs, Inflasi, Suku Bunga dan Indeks Harga Saham Gabungan dari bulan juli 2005 hingga juni 2016. Karena data tidak stasioner pada level maka dilakukan differencing terhadap data. Setelah stasioner selanjutnya dilakukan uji kointegrasi untuk mencaritau apakah terdapat kointegrasi antara peubah. Dengan karakteristik data yang Stasioner pada difference dan terdapat kointegrasi, sehingga memenuhi asumsi analisis VECM. Setelah dilakukan analisis VECM dilakukan analisis IRF dan VD. Adapun hasil analisisnya menunjukkan bahwa hanya Kurs yang secara signifikan berpengaruh lansung terhadap Indeks Harga Saham Gabungan.Kata Kunci: Analisis Time Series, VAR, Kurs, Suku Bunga, Inflasi, IHSG

This study studies that has the aim to apply Sutte Indicator to assist the investor to make the decision-making process of buying or selling of their stocks. The data of this study obtained from Stock of PT. Astra Agro Lestari Tbk. (AALI) on Yahoo Finance website. The period of data from 5 April 2001 to 20 September 2016. To check the performance of the predicting, it compare Sutte Indicator with other technical analysis: Moving Average Convergence/Divergence (MACD) and Simple Moving Average (SMA) and the check of the reliability using the mean absolute deviation (MAD), mean of square error (MSE), and mean absolute percentage error (MAPE).

α-Sutte Indicator (α-Sutte) was originally from the development of Sutte Indicator. Sutte Indicator can be used to predict the movement of stocks. As the development of science, Sutte Indicator is developed to predict not only the movement of stocks but also able to forecast the data on finance, insurance, and time series data. This method is called α-Sutte Indicator (α-Sutte). α-Sutte was developed by using the principle of the forecasting method of using the previous data. α-Sutte choose because it have best accuracy in forecasting. To implementation and check the accuracy of this method, the Consumer Price Index and Indices by Regions (Turkey) data used in this research. Data taken from January 2003 to June 2017. This data used because CPI data unstable and sometimes difficult to predict using other method. The data is divided into two parts, namely data training and testing. Data training starts from January 2003 to October 2016, and data testing starts from November 2016 to June 2017. To see the accuracy of α-Sutte, benchmark will be conducted from the results of forecasting with other forecasting methods e.g. Multiplicative Holt-Winters, Additive Holt-Winters, and Automatic Time Series Forecasting: The forecast Package for R (AutoARIMA) developed by Hyndman-Khandakar (2008) for the ARIMA/SARIMA model. The comparison of this accuracy is to compare the value of MSE, RMSE, and MAPE of forecasting the result on data training by using the data as reference data. The results are obtained that MSE value of Indicator of α-Sutte is smaller than other methods that is Multiplicative Holt-Winters, Holt-Winters Additive, and ARIMA (1,2,2)(0,0,2)12. Thereby the case for MAPE accuracy value Indicator of α-Sutte better than others method: Multiplicative Holt-Winters, Holt-Winters Additive, and ARIMA (1,2,2)(0,0,2)12.

This study aim to explore and review the literacy of tables and graphs for statistics students at Universitas Negeri Makassar. To obtain this aim, descriptive analysis conducted on the students results of table and graph literacy test. This study is importance for leading statistical learning tendency which emphasis on technical procedures with much mathematical formula. From this exploration, we can identify weaknesses that must be looked for solutions, particularly would improve learning of tables and graphs literacy to improve student's visualization and communication skills. Indicators of tables and graphs literacy have four domains, namely: (1) understanding tables and graphs concepts, (2) the ability of tables and graphs application, (3) skills of making table and graph, and (4) the accuracy of tables and graphs interpretations. The four domains are mapped according to grade of student. Mapping of table and graph literacy will be the basis of statistical learning strategies. Conclusion of the data analysis that the level of achievement scores of students in understanding the concept of the tables and graphs is still low (≤43%), the ability of tables application is still too low (41%), but for the ability of graphics applications is slightly higher (58%). Furthermore, the skills to make the table is still very low (25%), but for the skills to make the graph is slightly higher (59%). The general conclusion that the achievement score of statistics students of students batches 2013, 2014 and 2015 was still below the expectations. Thus, learning strategies need to be formulated to improve every aspect of learning in statistics courses.

Decision Support System is a system commonly used to assist management in assisting decision-making in top managerial sections, Multi-Criteria Decision Making (MCDM) is one of many decision-making methods that can be used to select the best alternative from a number of alternatives based on certain criteria, one of the methods that can be utilized is the Elimination Et Choix Traduisant la Realite (ELECTRE) method that works based on the concept of outranking using pairwise comparisons of each alternative based on appropriate criteria, this paper applies the ELECTRE method in a web based application that can be employed for input and output dynamic for alternative, criteria, user values and also a fast ranking process, the choice of web based application because there is many research about decision support system but only few that applied to application, and this research tries to applied ELECTRE method to web based application.

This type of research is a development research or it is known by the term of Research and Development (R & D). The focus of this research is to develop a logical reasoning ability measurement tool based on qualified Web and Android as a research instrument alternative solution. The implementation of this research is conducted on Statistics Department in the Faculty of Mathematics and Natural Sciences, Universitas Negeri Makassar. The subject of the study in question is the students of Statistics Department of Universitas Negeri Makassar. Measurement tool that will be developed is a Test of Logical Thinking (TOLT). The development of this information system using PHP programming language based on CodeIgniter Framework with MySQL database.

Long-term goal of this research is the development of a Research Management Information System at the Universitas Negeri Makassar that can be accessed by various parties related to research anytime and anywhere without any time and location limitation so that the disclosure of research management information can be done from the level of the study program to university level. Specific targets achieved from the development of this system is the creation of an information disclosure management situation both in terms of proposal entry, selection and review of proposals as well as progress reports and logbooks obtainment in reports of transparent and appropriate budget usage that is useful for the leadership of the University in taking policy related to the next research. To achieve these objectives, the information system development process will use the Plomp Development Model (1997) consisting of a preliminary investigation phase; design phase; phase realization/construction; test phase, evaluation and revision; and implementation. The development of this information system using PHP programming language based on CodeIgniter Framework with MySQL database.

Electronic learning based on Information and Communication Technology is one of the backbone behind the success of distance learning because it is actually able to save cost, time, and resources. To optimize the quality of this learning, more variety and interactive content with the support of multimedia elements (such as text, images, animations, sounds and video) is required. This research proposes a design of web-based lightweight interactive multimedia application combined with a game approach to support distance learning. This design employs web technologies based on pure HTML5, CSS3, and AJAX scripting that offer rich interactivity and lightweight performance. This research produces an interesting and fun learning application design that able to motivate students to self-learning.

Keeping the data intact without changing becomes an important factor in a communication, the data itself has many forms such as text data, audio data, image data and for secure every form data an algorithm Base64 are needed, Base64 algorithm is used as data format to transmit data due to the result of base64 itself, but Base64 algorithm is not safe enough because it is easy to decoding and get the original form data, therefore need additional security and in this research combined with Hashing Variable Length (HAVAL) algorithm, HAVAL algorithm has a way work secures and compresses plaintext, so the encoding result from Base64 is re-secured and compressed using HAVAL algorithm with length of hashing 32 bit or 4 bytes so when data transmission process will not take many bytes of data compared with Base64 algorithm

In 2006, Kemendiknas RI have done big enough investment in developing national computer network, called Jardiknas. Based on observation, there are quite a lot unproductive ICT center, is previously established in vocational schools. The study aims to find the suitable model of ICT management for Vocational High School (VHS). The model is expected to give the cultural contribution on the quality of education.

The selection of the bridge is fundamental thing to Sei Anak Muara Bulan 2 Bridge Planning. After knowing the results of capacity analysis of land and pile support capacity, ease of implementation, determine the selection of foundation planning decisions. The results of AHP implementation indicate that the aspects of land and pile carrying capacity are the main priority criteria with the amount 61.7% as the reason to determine the choice of bridge foundation and the result of alternative is the foundation of equal to 42,2%

In everyday life, seasonal events are common, seasonal behavior is common in various periods, such as daily, weekly or monthly. business, economics and financial cases for example, we often encounter a seasonal phenomenon, namely data that repeated over the same period. However, this seasonal test is only accurate For stationary Seasonal time series data. So, in this research we apply exact identification for multiplicative time series data from generated data. Performance of this test is determined by the percentage of fit identification. We apply this Periodogram Analysis to real data, AirPassengers and UKgas data. All simulation and real data analysis were done by open source Software R (OSSR). It is observed that in all model for Period 12, accuracy of detection seasonal models under 50%. However, for P=6, The algorithm was accurate enough to detect multiplicative-seasonal models, 70% of seasonal model can be detected by the algorithm.

The Consumer Price Index is an index which calculates the average change in prices over a period, of a set of goods and services consumed by the population/households within a specific time. In this paper will be discussed about the forecasting of consumer price index of Indonesia using forecast package with R Software. The forecasting process this data using algorithms popularized by Rob J. Hyndman and Yeasmin Khandakar in 2008. By using this method, it is obtained a suitable ARIMA model to forecast CPI data Indonesia. The model most suitable time series is ARIMA (1,0,0).

Decision Support System is a system commonly used to assist management in assisting decision-making in top managerial sections, Multi-Criteria Decision Making (MCDM) is one of many decision-making methods that can be used to select the best alternative from a number of alternatives based on certain criteria, one of the methods that can be utilized is the Elimination Et Choix Traduisant la Realite (ELECTRE) method that works based on the concept of outranking using pairwise comparisons of each alternative based on appropriate criteria, this paper applies the ELECTRE method in a web based application that can be employed for input and output dynamic for alternative, criteria, user values and also a fast ranking process, the choice of web based application because there is many research about decision support system but only few that applied to application, and this research tries to applied ELECTRE method to web based application.

The purpose of this study is to apply the α-Sutte Indicator in forecasting data. α-Sutte Indicator is a new forecasting method that was developed in 2017 by Ansari Saleh Ahmar. To see the accuracy of these methods, the forecasting results of the α-Sutte Indicator will be forecasting methods compared to other items, namely: ARIMA and HoltWinters. Based on the results of forecasting, it is found that α-Sutte Indicator has MSE and MAPE values that are lower than other methods (ARIMA and HoltWinters). This is supported by MSE data from α-Sutte Indicator smaller than ARIMA(2,2,2) and HoltWinters i.e. 0.03; 3.06; and 3.15.