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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

Autoregressive Integrated Moving Average (ARIMA-Box Jenkins) Pada Peramalan Komoditas Cabai Merah di Indonesia Ridha Maya Faza Lubis; Zakarias Situmorang; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2927

Abstract

Chili is one of the main staples in making a dish and chili is one of the values in a commodity that has superior value, the price of chili often experiences price fluctuations or what is known as the price which is always changing. data taken from BPS (Central Bureau of Statistics) data nationally from January 2001 to December 2015 data, this study also aims to be able to predict national chili prices which will later be used in research, namely discussing the Autoregressive Integrated Moving Average (ARIMA) method. In this study, the identification of the model was carried out using two tests, namely the stationarity test and the correlation test. The stationarity test is the Augmented Dickey-Fuller (ADF) test, the Philips-Perron (PP) test and the Kwiatkowski-Philips-Schmidt-Shin (KPPS) test using Minitab 9.The chili commodity is a very important commodity in the Indonesian economy, because In terms of consumption, chilies have a very significant market share, which can be seen from data from the Central Statistics Agency (BPS) with an inflation weight value of 0.35%. From the research, it was found that for the selection of the best method, namely ARIMA (3,1,0) because it has the smallest MSE value and the forecasting results for the next 12 periods in January 2016 ranged from Rp. 11,868.2 to Rp. 28,315.5 and so on until December 2016.
Kombinasi Metode Simple Additive Weigthing dan Weigthed Product Untuk Seleksi Proposal Program Kreatifitas Mahasiswa Raden Aris Sugianto; Roslina Roslina; Zakarias Situmorang
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2929

Abstract

This Research aims to develop a decision support system that can facilitate the proposal selection process and provide an alternative ranking for the selection results of student creativity program proposal selection. This decision support system uses a combination calculation of the Simple Additive Weighting and Weigthted Product methods, hereinafter referred to as Modified SAW. The criteria used in this assessment refer to the 2020 Student Creativity Program Guidebook. The data used in this decision support system uses proposal selection data in the Student Creativity Development Unit of Muhammadiyah University of North Sumatra in 2019 for 2020. This system was developed by determining criteria and weight determination using the Simple Additive Weighting method and then make improvements to the weight and determine the preference value using the Weighted Product method. Each of the SAW and WP methods certainly has advantages and disadvantages. The advantages of SAW with a simple and simple ranking process, can be applied to decision-making cases such as in the recommendation of selecting proposals with various attributes. While the use of Weighted Product (WP) is often used because the weight is calculated based on the level of importance and can evaluate the set of attributes by multiplying all criteria with alternative results as well as the power between weights and alternative multiplication results. This WP method can also be used in assisting in recommendation of proposal selection based on what is needed by the University. By utilizing the advantages and disadvantages of each method, this combination is able to produce an accuracy of 91% for the SAW method, 97% for the accuracy using the WP and 99% for the accuracy value for the combination of the SAW and WP methods. This decision support system using MOD SAW can help facilitate the proposal selection process and provide alternative ranking results. Further research is suggested for the development of a decision support system for proposal selection using a combination of different methods between SAW and other methods.
Analisis Kinerja Support Vector Machine dalam Mengidentifikasi Komentar Perundungan pada Jejaring Sosial Ade Clinton Sitepu; Wanayumini Wanayumini; Zakarias Situmorang
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2923

Abstract

Cyberbullying is the same as bullying but it is done through media technology. Bullying has often occurred along with the development of social media technology in society. Some technique are needed to filter out bully comments because it will indirectly affect the psychological condition of the reader, morover it is aimed at the person concerned. By using data mining techniques, the system is expected to be able to classify information circulating in the community. This research uses the Support Vector Machine (SVM) classification because the algorithm is good at performing the classification process. Research using about 1000 dataset comments. Data are grouped manually first into the labels "bully" and "not bully" then the data divide into training data and test data. To test the system capability, data is analyzed using confusion matrix. The results showed that the SVM Algorithm was able to classify with an level of accuracy 87.75%, 89% precision and 91% Recal. The SVM algorithm is able to formulate training data with level of accuracy 98.3%
Analisis Ward and Peppard Model Pada Strategi Bisnis dan Perencanaan Strategis Sistem Informasi Daim Azhari Parinduri; Roslina Roslina; Zakarias Situmorang
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2977

Abstract

Muslim Nusantara Al-Washliyah University is a private university that already has information system technology and information technology as an effort to improve the competitiveness of higher education. However, the existence of the existing information system is still not perfect so that work becomes inefficient. Therefore, this research was conducted to make strategic planning of information systems so as to increase the competitiveness of higher education institutions. The model used in strategic planning in this study is the Ward and Peppard model. The strategic plan is drawn up for a timeframe of 2 phases. The process begins with Internal and External Business Analysis through SWOT Analysis, Value Chain Analysis, PEST Analysis and testing of strategy results using the Profile Matching method which is the choice to provide an assessment of recommended information system applications. There are three aspects in conducting the assessment and evaluation, namely new aspects, develop and continue.
Improvement Ranking Accuracy of Weighted Aggregated Sum Product Assessment With Lambda Variable Muhadi M. Ilyas Gultom; Erna Budhiarti Nababan; Zakarias Situmorang
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5280

Abstract

Conventional methods are still used in selecting  the best students in the various institutions depending on the subjectivity of each member of the assigned committee. In order to make an objective decision, it is necessary to have a method that can consider the criteria used to select the candidates to be elected. The decision-making method used in this study is Weighted Aggregated Sum Product Assessment(WASPAS). This study aims to analyze the increase in accuracy of the WASPAS method that occurs in the implementation of the lambda variable in the process of combining the Weight Product Method(WPM) and Weight Sum Method(WSM). This method is use because it is suitable for the case studied where the application of this method focuses on weighting criteria with a dynamic number of alternatives and low computational complexity providing good performance in handling large amounts of data.The application of this method uses data from students from Engineering Faculty of Universitas Islam Sumatera Utara which is tested on 10 students with criteria adapted from student data attributes that can be used as parameters for decision making. The results of this study show an increase for each alternative with an average value of 23.6% for each alternative. From this study it can be concluded that accuracy is highly dependent on variations in lambda values which are affected by the determinant operator in the equation used. Therefore it is possible to find an absolute equation to give optimal effect on a single value without variation by considering the bias of the effect of the WASPAS method on the lambda variable in future research.TRANSLATE with x EnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian //  TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster PortalBack//