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A Decision Support System For The Selection Of Exemplary Students With AHP Method At SMP IT Generasi Rabbani Of Bengkulu City Junizar, Wansa S; Suranti , Dewi; Alamsyah , Hendri
Jurnal Komputer, Informasi dan Teknologi Vol. 2 No. 1 (2022): Juni
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v2i1.788

Abstract

To increase the enthusiasm of the students of SMP IT Generasi Rabbani Bengkulu, the school gave awards to exemplary students. By making an assessment of Morals, Academics and Worship. However, to determine the model students of SMP IT Generasi Rabbani Bengkulu, so far, they still use the manual calculation method which takes a lot of time and the risk of calculation errors is large. One method that can be used to solve the problem is the Analytical Hierarchy Process (AHP) method, because the AHP method is able to solve multicriteria problems with the stages of determining the priority of elements, making a pairwise comparison matrix of criteria and sub-criteria, normalizing the matrix, as well as ranking and decision results. This study aims to build a decision support system application for selecting exemplary students using Visual Basic. Net and SQL Server 2008r2 Database at SMP IT Generasi Rabbani Bengkulu therefore it can help the school to determine and select prospective exemplary students quickly and accurately based on predetermined criteria. From the results of functional testing carried out on the application, it is found that some of the functions contained in the application can run well. And the results of the comparison show that there are differences in the value of each student and are able to provide a ranking order of student scores from the highest to the lowest score. Based on the results of research conducted, the AHP method is able to provide convenience in the decision-making process quickly and precisely for the selection of exemplary students therefore the highest score is 0.53 and the lowest value is 0.24.
Application of the Multiple Linear Regression Method in Forecasting the Amount of Drug Supply at the Health Center Ternando, Riki; Wahyudi , Jusuf; Suranti , Dewi
Jurnal Komputer, Informasi dan Teknologi Vol. 2 No. 2 (2022): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v2i2.1043

Abstract

Sukamerindu Health Center is one of the health centers in the city of Bengkulu. Drug management at the puskesmas has utilized an office application package, namely excel, but this utilization has not been fully implemented, because there is still a manual process where drug data collection is filled in through the books that have been provided, then only recapitulated at the end of the month. This sometimes makes it difficult for the puskesmas to manage the availability of drugs at the puskesmas. The application for forecasting the amount of drug supply at the UPTD Sukamerindu Health Center in Bengkulu City was made using the Visual Basic .Net programming language by applying the Multiple Linear Regression Method for the forecasting process. In determining the results of the forecast for the following month and year, there are 3 supporting variables used, namely demand, use, and supply of drugs in the previous month and year. Based on data on the 500 mg Amoxicillin Capsule, where there were 36 data analyzed from January 2019 to December 2021, the prediction results for the number of drug supplies in January 2022 using the Multiple Linear Regression Method were 13066, with a prediction error rate of 7.10%. . Based on testing the application for forecasting the amount of drug inventory at the UPTD Puskesmas Sukamerindu, Bengkulu City, it was found that the functionality of the application ran according to expectations .
Application Of Fuzzy Logic In Umkm Recommendations Upgrade Using The Sugeno Method At The Cooperative Office Of The City Of Bengkulu Ristika, Ristika; Suranti , Dewi; Suryana , Eko
Jurnal Komputer, Informasi dan Teknologi Vol. 3 No. 2 (2023): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v3i2.1489

Abstract

The application of fuzzy logic in the recommendation of MSMEs to upgrade at the Bengkulu City Cooperative Office can help provide assessment results for MSMEs based on assessment criteria so that MSMEs are obtained that are upgraded feasible or not feasible. The Sugeno method will analyze MSME assessment data by looking at the number of workers, capital, and turnover of each MSME which will then calculate the z value in each rule where there are 54 rule compositions used so that the final value for each MSME can be known. Based on the blackbox testing that has been carried out, it is found that the functionality of the MSME recommendation application for upgrading at the Bengkul City Cooperative Service runs well as expected and is able to analyze MSME assessment data through the Sugeno Fuzzy Method to determine recommendations for MSME eligibility for upgrading..
Application of the Naive Bayes Method in Expert Systems for Diagnosing Gingivitis Fernando, Rendy; Suranti , Dewi; Suryana , Eko
Jurnal Komputer Indonesia Vol. 1 No. 2 (2022): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v1i2.24

Abstract

The number of program activities at the Beringin Raya Health Center in Bengkulu City is sometimes not proportional to the number of doctors in the puskesmas, so not all patients can have health consultations, especially about gingivitis. Gingivitis is a disease caused by a bacterial infection which causes the gums to swell due to inflammation. Therefore we need an application that can help the process of diagnosing gingivitis based on the symptoms experienced by the patient, so that the initial diagnosis experienced by the patient can be known. The expert system for diagnosing gingivitis at the Beringin Raya Nursing Health Center in Bengkulu City was made using the PHP programming language and MySQL database, which can be accessed online via the https://sistempakargingivitis.my.id/ link. The expert system for diagnosing gingivitis in the treatment of Beringin Raya, Bengkulu City, has implemented the Naive Bayes Method to represent, combine, and propagate uncertainty, which has several intuitive characteristics according to the way of thinking of an expert. The training data used is 11 data which is used as the basis for the probability value of each symptom in the disease to carry out a consultation diagnosis. Based on the consultation with the selected symptoms, namely G1, G2, G3 and G4, the diagnosis of Nonvital Teeth disease (Dead Teeth) was obtained with a bayes value of 0.2045454541875. Based on the system testing that has been done, it can be concluded that the functionality of the application has been running well and this expert system can provide consulting results based on the symptoms selected by the user through the stages of the Naive Bayes method
Expert System Application to Diagnose Degenerative Diseases Using Methods Certainty Factor Imansyah, Dwi; Suranti , Dewi; Suryana , Eko
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.2097

Abstract

Degenerative diseases are diseases that cause damage or destruction to body tissue or organs that arise due to a decrease in the function of one or more of the body's organs which are very susceptible to elderly people. Considering the large negative impact of degenerative diseases, it is necessary to prevent or seriously treat the dangers of degenerative complications. Efforts to minimize this danger can be made by increasing public awareness about things that can cause degenerative diseases. Therefore, we need a system that can help as an alternative to consulting a doctor for the general public. Therefore, this expert system was built using the Certainty Factor method which can be used as a solution in using an expert system to diagnose this Degenerative disease. In its application, the certainty factor method can provide a percentage level of confidence in a disease, if the user has or selects symptoms so that they can determine the type of disease they are suffering from. Based on the tests carried out, it can be concluded that this expert system application can be used by users to make an early diagnosis of degenerative diseases. This expert system can be accessed at the link www.sp_ Degenerative.com. Making it easier for users to consult.
Penerapan Algoritma C4.5 Dalam Memprediksi Tingkat Kelulusan Siswa Pada SMPN 06 Bengkulu Tengah Wahidi, Agus Rahman; Maryaningsih, Maryaningsih; Suranti , Dewi
Jurnal Komputer Vol 1 No 2 (2023): Januari-Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v1i2.55

Abstract

SMPN 6 Central is a junior high school educational institution in Central Bengkulu. This school has a lot of data related to academic activities, for example student graduation data. These data have not been utilized as fully as possible, for example to predict student graduation, so that action can be taken to maximize preparation for the final exam. This research was conducted to design an application system using a classification technique that can process large amounts of data to find patterns that occur in student data. The data processing is used to predict student graduation. The classification technique used is the decision tree with the implementation of C4.5 algorithm. The input used is in the form of attributes from student data including semester from semester 1 to 6, skills scores and National Standard School Examination scores (USBN). Therefore, to make it easier to predict the graduation rate, an application testing uses data on students who have graduated from 2019 to 2020, totaling 100 students and the results of testing from 2021 to 2022, totaling 81 students. The knowledge gained from the results of the application training is expected to be utilized by the management of SMPN 6 Central Bengkulu as a more effective decision-making tool in planning and preparing for students' final exams. Based on the results of the tests carried out, it can be concluded that this application can predict student graduation at SMPN 6 Central Bengkulu.
Sistem Pakar Mendiagnosa Penyakit Appendisitis Menggunakan Metode Certainty Factor Feryra, Stivano; Suranti , Dewi; Yupianti
Jurnal Komputer Vol 2 No 1 (2023): Juli-Desember
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v2i1.64

Abstract

Health is an important asset in carrying out activities so it needs to be maintained and considered properly, therefore it is important to equip yourself with knowledge and maintain a healthy lifestyle in order to avoid various diseases. One of the diseases that attack humans and is often found in hospitals is appendicitis. The lack of knowledge and socialization to the community about this disease Appendicitis (Inflammation of the Appendix), resulting in the community considering this disease as trivial or ordinary, in fact according to the information of doctors this disease which if not treated properly will cause death. Therefore, to help the community and medical personnel in providing knowledge, consultation and socialization about the disease Appendicitis (Inflammation of the Appendix) is to design and build an expert system application by applying the Certainty Factor method. The Certainty Factor method has the advantage of being able to measure something whether it is certain or uncertain, for example in diagnosing a disease.The final result of this research is an expert system to diagnose Appendicitis (Inflammation of the Appendix) along with the confidence value of the diagnosed disease, which shows the system's level of confidence in the disease.