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All Journal Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Journal of Computing and Informatics Research Journal of Blockchain, Nfts and Metaverse Technology ADA Journal of Information System Research
Rima Tamara Aldisa
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science

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Penerapan Metode MOORA dan ROC Dalam Pemilihan Oli Mesin Terbaik Untuk Sepeda Motor Matic Serdina Feria Sidabutar; Rima Tamara Aldisa; Geofani Pasaribu
Bulletin of Computer Science Research Vol. 4 No. 2 (2024): Februari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i2.329

Abstract

As the use of automatic type of motorbike vehicles increases, the problem also increases in the automotive world because there are many users of automatic type motorcycle vehicles who do not understand how to care for and maintain the durability of their automatic motorbikes, especially the most important part of the motorbike, namely the the engine components. Machine maintenance is inseparable from lubricating oil which has a function in lubricating engine components so that they are maintained, durable, & away from rusting or even chipping because of friction between components one with another which results in damage to the motorbike engine so that their favorite motorbike has to be make repairs to the workshop. Moreover, the motorbike used is of the automatic type, where maintenance is much more complicated than other motorbikes, which are of the gear or clutch type. In determining the best engine oil for the best automatic motorbikes, starting from the contents of the package which are at least 1 liter, has a non-concentrated odor, and is able to keep the engine cool when the motorbike is used. Combination of the MOORA and ROC Methods in the selection of the best engine oil for the best automatic type motorcycle based on predetermined criteria for the “Evalube” brand alternative S5 oil with a preference value of 0.019 as the best engine lubricating oil for automatic type motorcycles. The application of the MOORA Method has a simple and easy-to-understand concept in selecting the best engine oil for automatic type motorcycles. The process of selecting the best engine oil for automatic type motorbikes using the MOORA and ROC methods, starts from determining the weight value of each criterion and then ranking the largest preference value as a consideration and aid in decision making.
Penerapan Metode Simple Additive Weighting (SAW) dan Rank Order Centroid (ROC) dalam Keputusan Pemberian Kredit Sepeda Motor Dwika Asrani; Rima Tamara Aldisa; Gunawan Siburian; Jannus Manik
Bulletin of Computer Science Research Vol. 4 No. 2 (2024): Februari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i2.330

Abstract

Motorcycle credit is a method of borrowing money from a financial institution, such as a bank or finance company, to buy a motorcycle. Naira Finance, as one of the leading finance companies in Indonesia, provides convenience for customers to own vehicles (both new and used motorcycles) of various brands. The job of a motorcycle loan manager is to decide whether or not to provide motorcycle loans to customers. To reduce the possibility of customer negligence in paying credit bills in the future, it is important to provide credit on time. As a supporting effort, credit managers should use a computer-based application known as a Decision Support System (DSS) to make credit granting decisions more accurate. A computer-based system known as SPK can assist managers in making both structured and unstructured decisions. Researchers try to combine the Rank Order Centroid (ROC) method and the Simple Additive Weighting (SAW) method when deciding to give credit or not to customers. In preference to the SAW method of calculation, it is intended that the weighting results of the ROC method are significant. the results of the decision from the application of the ROC and SAWt methods, there are 5 alternatives that are accepted to receive credit because they are considered feasible and meet the requirements criteria specified as customers who are entitled to receive credit while the other 5 alternatives are rejected so that they are declared unable to receive credit because they do not meet the customer requirements criteria.
Sistem Pendukung Keputusan Penilaian Kinerja Pada Siswa Magang dengan Metode Simple Additive Weighting (SAW) Nita Noptapia Sihombing; Rima Tamara Aldisa; Yudika Parulian Simatupang
Bulletin of Computer Science Research Vol. 4 No. 2 (2024): Februari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i2.331

Abstract

The apprenticeship program is a learning activity in the field that aims to introduce and develop students' skills in a real work environment. Students who will take part in internships need to prepare as well as possible, not just focusing on the academic competencies they learn at school. On the other hand, they must also have experience, knowledge, and insight into a wide world of work. So far, appraising the performance of apprentice students is primarily based on disciplinary criteria. However, there are actually several other criteria that can also be taken into consideration in assessing the performance of apprentice students, such as Discipline, Performance, Creativity, Teamwork, Adaptation and Mastery of Work Materials. To conduct a more comprehensive assessment of the performance of apprentice students, a decision support system is needed. In this study, the method used is Simple Additive Weighting (SAW). The choice of this method is due to its ability to handle assessments by considering the priority values or weights that have been assigned to each criterion. The results of this study indicate that Alternative A4, represented by "Rezka," is the best alternative with a Vi value of 0.9472.
Penerapan Metode Multi-Arttribute Utilily Theory (MAUT) Dan Rank Order Centroid (ROC) Dalam Pemilihan Bidan Terbaik Puskesmas Dedi Verianto Laia; Rima Tamara Aldisa
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1732

Abstract

Midwives are professional health workers who have graduated from midwife education and have been registered in accordance with statutory provisions. In practice, midwives have undergone special training to be able to provide services in the form of midwifery care and in the form of caring for women during pregnancy, childbirth and after they give birth. Apart from that, midwives can also help guide mothers to breastfeed and care for newborns for up to six weeks afterward. So, apart from being able to carry out their own midwifery practice, midwives can also practice in various health facilities, one of which is a hospital. A midwife is a health professional who has an important role in caring for women during pregnancy, childbirth and postpartum. The conclusion is that the determination of the recommendation for selecting the best midwife at the health center using the MAUT method from 7 midwives with 5 criteria and the weight value obtained using the ROC method with the highest result can be alternative A1 with a value of 0.715 and the lowest value is A7 with a value of 0. With the implementation of MAUT and ROC methods in recommending midwives at community health centers using the criteria of skill/expertise, service, responsibility, attitude, age and experience. From the results of calculations using the MAUT method and the criteria weighting values ??using the ROC method, a value of 0.715 was obtained for the main priority order.
Sistem Pendukung Keputusan Pemilihan Leader Terbaik Menerapkan Menggunakan Metode Multi-Atribute Utility Theory (MAUT) Sylvia Situmorang; Rima Tamara Aldisa
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1733

Abstract

Leaders are people who have skills and strengths, including skills in a field, that can influence others to do certain jobs together to achieve a goal. A leader has an important role in influencing employee performance to increase the amount of profit the company can get. The process of selecting the best leader is one of the activities that must be carried out regularly by the company to improve the quality of its employees on an ongoing basis. Thus, the company needs a decision support system (SPK) in order to facilitate the company in carrying out the best leader selection activities in terms of time and obtaining more effective and efficient results. The method used by the author in this SPK is the Multi-Atribute Utility Theory (MAUT) method. The criteria used in this study are having the soul of a leader, high creativity, attractive appearance, loyalty, and having work experience in this field. The result of the Best Leader Selection research that deserves to be the best leader is alternative A3 with a final utility value of 1.2066058 on behalf of "Jessica Oktavia."
Sentiment Analysis on Twitter Using Naïve Bayes and Logistic Regression for the 2024 Presidential Election Alisya Mutia Mantika; Agung Triayudi; Rima Tamara Aldisa
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i1.267

Abstract

In accordance with the notion of democracy which is the basis of the state of Indonesia, general elections will be held in 2024. In the implementation of the General Election there is a campaign to lead the public vote to choose the best candidate according to public opinion. Twitter social media is one of the media to voice opinions as well as share information to become one of the indirect campaigning platforms. Social media also does not escape negative issues, community rumors, and even the digital footprint of presidential candidates which can be a very important consideration in campaigning. This research aims to see the public's response to the 2024 presidential candidates. This research is conducted based on public opinion on presidential candidates, then public opinion data taken from Twitter social media will go through a pre-processing process to clean the data before the data is classified into Naive Bayes and Linear Regression modeling. The two classification models are then sought for the highest performance accuracy value and confusion matrix with 80:20 splitting data. The results showed that the Naive Bayes classification model had a higher accuracy value than the Logistic Regression classification model, which was 63% for Anies Baswedan candidate, 77% for Ganjar Pranowo candidate, and 44% for Prabowo Subianto. The highest accuracy value was obtained by the sentiment data of 2024 presidential candidate Ganjar Pranowo, which was 77%.
Implementation of the Simple Additive Weighting (SAW) Method in Selection of Students Recipients of Single Tuition Fee Assistance Riki Sulistio; Ahmad Fahreza Nasution; Muhammad Tawaf Akbar; Rima Tamara Aldisa; Bister Purba
Journal of Computing and Informatics Research Vol 3 No 2 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i2.1202

Abstract

Higher education in Indonesia, including at Budi Darma University, continues to be committed to creating an inclusive and equitable learning environment for all students. In line with this determination, Budi Darma University is implementing the Single Tuition Assistance (BUKT) program to support educational accessibility. Obstacles in the selection process, which is subjective and lacks a structured framework, can lead to inequality in the distribution of aid. This can result in students who should receive greater support being overlooked, while those who may need less may receive greater aid. In the BUKT selection process, there are a number of requirements that must be met, such as parents' income, PKH card ownership, completeness of documents, parents' dependents and home ownership. It is hoped that the use of a decision support system can be a solution to overcome this challenge. Decision Support Systems (DSS) integrate computer technology, mathematical models, and data to provide structured and organized support within a decision-making framework. The Simple Additive Weighting (SAW) method is a multi-criteria decision making method that allows relative weighing between criteria to determine the final score for each alternative. By applying SAW in the selection of BUKT recipient students, it is hoped that more objective and data-based decisions can be obtained. The research results produced the best alternative with a value of 100.00 in the alternative with code A5 in Fitri's name, so that Fitri was declared entitled to receive single tuition assistance.
Penerapan Metode WP dan ROC dalam Pemilihan Siswa Peserta Olimpiade Sains Dwika Asrani; Telaumbanua, Delis Marnyu; Aldi Chandra Maulana; Rima Tamara Aldisa
ADA Journal of Information System Research Vol. 1 No. 2 (2024): February 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i2.33

Abstract

The organizers of the National Science Olympiad (OSN) aim to find talent, interest and learn to compete, increase knowledge in the field of science which is carried out once a year. The process of selecting prospective OSN participants who pass the selection is not an easy thing because the school has to select one student at a time. So that a decision support system for selecting prospective OSN participants is needed using the Weighted Product WP method to efficiently select prospective OSN participants. To select students who will take part in OSN using the Weighted Product WP and Rank Order Centroid ROC methods, use the criteria for subject scores (containing 6 subject matter) or those related to subject matter in OSN, academic achievement, OSN experience. The results obtained with the WP and ROC methods the school can efficiently recommend prospective participants who will take part in OSN because there is no need to select students one by one. . In this study, the highest ranking results were given to Alternative 2 named Bagas with a value of 0.261.
Co-Authors Agung Triayudi Ahmad Fahreza Nasution Ahmad Farhan Mahesa Ahmad Rifqi Aldi Chandra Maulana Alisya Mutia Mantika Anggi Annur Septia Arman Prasojo Sugiyarto Bister Purba Dedi Verianto Laia Dwika Asrani Erza Muhammad Randi Frenda Farahdinna Geofani Pasaribu Gunawan Siburian Handoko Pangestu Girsang Iqbal Arif Budiman Jannus Manik Moh. Iwan Wahyuddin Mohammad Aldinugroho Abdullah Muhammad Naufal Rifqi Muhammad Tawaf Akbar Nita Noptapia Sihombing Puspa Ayu Sholeha Raihansa Romadhon Riki Sulistio Serdina Feria Sidabutar Sylvia Situmorang Telaumbanua, Delis Marnyu Yudika Parulian Simatupang