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Journal : Building of Informatics, Technology and Science

Implementation of the Simple Additive Weighting Method in Determining Recipients of Subsidized Food Materials for Poor Families Kusmanto, Kusmanto; Budi, Eko Setia; Samsir, Samsir; Hariska, Elvia; Ginting, Guidio Leonarde
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.804 KB) | DOI: 10.47065/bits.v3i3.1097

Abstract

In accordance with the rules that have been set from the Village Office so that the community gets subsidized food, it must comply with the specified criteria. The Village Office will determine who is selected to receive subsidized food and distribute it to poor families. As a tool that can be used to determine someone who is eligible to receive subsidized food, a decision support system is needed. In the decision support system there are several methods, one of which can be used is the SAW (Simple Additive Weighting) method. In this research
Implementation Naïve Bayes Classification for Sentiment Analysis on Internet Movie Database Samsir, Samsir; Kusmanto, Kusmanto; Dalimunthe, Abdul Hakim; Aditiya, Rahmad; Watrianthos, Ronal
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.705 KB) | DOI: 10.47065/bits.v4i1.1468

Abstract

A film review is a subjective opinion of someone who has different feelings about each film. As a result, film enthusiasts will struggle to assess whether the film meets their requirements. Based on these issues, sentiment analysis is the best way to fix them. Sentiment analysis, also known as opinion mining, is the study of assigning views or emotional labels to texts in order to determine if the text contains positive or negative thoughts. The Nave Bayes method was chosen because it can classify data based on the computation of each class's probability against objects in a given data sample. The best model was created utilizing data without lemmatization, 500 vector sizes, and Nave Bayes classification, with an accuracy of 78.96 percent and a f1-score of 78.81 percent. Changes in vector size affect the system's capacity to foresee positive and negative sentiments. The difference in accuracy and recall values shows that when vector size 300 is utilized, the precision and recall outcomes are lower than when vector size 500 is used.
Sistem Pendukung Keputusan Penilaian Kinerja Ketua Program Studi Menerapkan Metode WASPAS dengan Pembobotan ROC Nasution, Mhd Bobbi Kurniawan; Kusmanto, Kusmanto; Karim, Abdul; Esabella, Shinta
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (371.205 KB) | DOI: 10.47065/bits.v4i1.1619

Abstract

The head of the study program is a figure who plays an important role in the progress of each study program at a university. The head of the study program has a role in the decision-making process and in carrying out managerial policies. In addition, the head of the study program is also a person who is able to ensure the creation of a conducive atmosphere in the service process to students and also the scope of work in the study program. Therefore, awarding the head of the study program based on the performance shown is a form of appreciation for the performance given by the head of the study program. The process of evaluating the performance of the head of the study program is not only an assessment of the academic field but also an assessment of the managerial. In the process of evaluating the performance of the head of the study program, a computerized tool is needed or commonly called a Decision Support System. The decision support system also has several settlement methods that are used as a reference, one of the methods that can be used is the WASPAS method. In addition to the methods used to support decisions, there are also methods that can be used for weighting each assessment criteria such as the ROC method. In this research, we will use the ROC weighting method on the assessment criteria and the process of evaluating the performance of the head of the study program using the WASPAS method. The results achieved in the research are to obtain an objective and accountable process of evaluating the performance of the study program leader. In the research that has been carried out, it is found that the Head of the Study Program who gets the reward is the Head of the Study Program with alternative A2 and the preferred value is 0.958
Sistem Pendukung Keputusan Dalam Rekomendasi Kelayakan nasabah Penerima Kredit Menerapkan Metode MOORA dan MOOSRA Kusmanto, Kusmanto; Nasution, Mhd Bobbi Kurniawan; Suryadi, Sudi; Karim, Abdul
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2610

Abstract

In selecting credit recipients, it is necessary to have a recipient selection system that can overcome the problem of bad credit that often occurs (loans that are not repaid by the debtor). Based on this problem, a decision support system is needed that helps identify the wrong recipient. The method used in this study is the Moora method and the Moosra method, namely the method for determining priorities. A decision support system is a computer-based system consisting of interacting components: a language system component, a knowledge system component, and a problem-handling system component, and uses data and decision-making models to create semi-structured problems. It solves structured problems and semi-structured problems. and assist in decision making. Structured and unstructured problems, this system helps you get information about your customers, the results are more accurate and on target
Penerapan Metode Teorema Bayes Dalam Mendiagnosa Penyakit Autoimun Karim, Abdul; Esabella, Shinta; Kusmanto, Kusmanto; Suryadi, Sudi; Purba, Elvitrianim
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3407

Abstract

Autoimmune diseases are caused by the failure of the immune system to attack the body itself. According to data from the US Department of Health and Human Services, more than 23.5 million Americans have an autoimmune disease, which is difficult to diagnose because of the variety of symptoms it presents. Therefore, the development of mechanisms to identify autoimmune disorders is essential. One of the developing technologies in this field is the use of expert systems in diagnosing diseases. An expert system is a system developed by experts using science-based technology. In order to use it effectively, proper methods are needed, such as the Bayes Theorem approach, described by Thomas Bayes, a priest. The Bayes Theorem approach explains the relationship between the probability of event A and event B based on available information. This study attempts to facilitate the diagnosis of autoimmune diseases by using an expert system and Bayes' Theorem technique. With a confidence level of 0.57 or 57%, the examination results show that the patient suffers from an autoimmune disease of the type Hemolytic Anemia (HA) based on the patient's input
Clusterisasi Tingkat Pengangguran Terbuka Menurut Provinsi di Indonesia Menggunakan Algoritma K-Medoids Karim, Abdul; Esabella, Shinta; Kusmanto, Kusmanto; Suryadi, Sudi; Mardinata, Erwin
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6198

Abstract

The Open Unemployment Rate (OER) in Indonesia decreased in February 2024 to 4.82%, showing an improvement compared to February 2023. Despite the decline in TPT, there are still regions with TPT reaching 7.02%, which could potentially lead to negative consequences such as increased crime. Efforts to address TPT include increasing economic growth, developing the quality of education and training. This research utilises clustering in data mining. The number of clusters formed was 3 clusters with a DBI value of -1.685. This study uses K-Medoids clustering to group 38 provinces based on TPT. Of the 38 data, there is incomplete data so preprocessing is done using the "filter example" operator in rapidminer to eliminate incomplete data so that there are 34 data that will be used in this study (after preprocessing). The results show 4 provinces with the highest TPT (Riau Islands, DKI Jakarta, West Java, and Banten) with a percentage of 11.76%.