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All Journal International Journal of New Media Technology International Journal Of Science, Technology & Management (IJSTM) International Journal Science and Technology (IJST) Ceddi Journal of Information System and Technology (JST) The Indonesian Journal of Computer Science
Adline Twince Tobing, Fenina
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Implementation Of Fuzzy Multi-Criteria Decision Making To Design An Expert System For Prediction Of Digestive Diseases At Dogs Tisna Kusuma, Irene; Kusnadi, Adhi; Adline Twince Tobing, Fenina
Ceddi Journal of Information System and Technology (JST) Vol. 2 No. 2 (2023): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v2i2.50

Abstract

A dog is a kind of animal that is often looked after at home. Except for being known as a human's friend, a dog is also able to be trained to do many things. The age of the dog depends on the type of race. If it's fed well, exercises, and visits the doctor regularly, a dog can live longer. Dogs are very sensitive to certain diseases; one of them is intestinal disease. An expert system of a dog's digestion is built for the dog's lover so that they know exactly what's disease, which relies on the appearance of the symptoms. The symptoms of the different intestinal diseases look almost similar. For this reason, we need an appropriate method to get a precise result. Fuzzy multiple-criteria decision-making can help make the right decision that has some consideration points. This method is also equipped with optimal ultimate selections, which leads to a very precise result. The goal of this application is to know the right kind of disease and its therapy. This study has been validated by matching the results of the application with the doctor's diagnosis. The compatibility level is 80%.
Implementation of Vikor Algorithm in Web-Based Recommendation System for Obstetrician Selection Andrew, Richard; Adline Twince Tobing, Fenina; Kusnadi, Adhi
International Journal of Science, Technology & Management Vol. 4 No. 5 (2023): September 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i5.915

Abstract

The process of childbirth is a natural event for women; with the increase in birth rates, selecting a suitable obstetrician becomes essential. However, many couples find it challenging to choose the right obstetrician, from consultations to hospital births. This study aims to develop an obstetrician recommendation system to overcome decision-making challenges that involve many criteria. The method used is VIseKriterijumska Optimizacija Kompromisno Resenje (VIKOR), which is one of the best methods in Multiple Criteria Decision Making (MCDM) for ranking and selecting alternatives. This method involves several steps, including determining the weight of the criteria, normalizing the matrix, calculating the Utility Measure and Regret Measure, and calculating the VIKOR index. Testing was carried out through scenario tests and user survey tests using the USE questionnaire. The scenario test results show the successful implementation of VIKOR in this system. The results of the user survey test indicated a high level of satisfaction with a score of 83.34%, which fulfilled the four variables in the USE questionnaire: usability (79.76%), ease of use (84.81%), ease of learning (84.81), and satisfaction (83.31%). The results of this study have important implications for increasing the effectiveness of decision-making in selecting the right obstetrician. By incorporating the VIKOR method into an application, this research provides a valuable contribution to developing a VIKOR-based recommendation system. It emphasizes the importance of applying this method in complex decision-making environments.
Men's Perfume Recommendation System Using Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Method Adline Twince Tobing, Fenina; Kusnadi, Adhi; Endariahna Surbakti, Eunike; Rayhan Harsono, William; Ivan Wijaya, Aurelius; Dinarta, Farrel; Irelynn, Maecyntha; Paskah, Richard
International Journal of Science, Technology & Management Vol. 4 No. 6 (2023): November 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i6.1002

Abstract

Perfume has been a product used for thousands of years by human civilization. Rapid growth of perfume products creates a problem especially for men to choose the best perfume to fit their personality. This research aims to help men find out which perfume suits each individual's personality by inputting a comparison of four main criteria, namely quality, price, aroma and durability. In this research, the research team built a perfume recommendation system specifically for men using the application of the Analytic Hierarchy Process (AHP) & Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The research resulted in an 89.17% usefulness score, 89.34% ease of use, 89.34% ease of learning, and 91.61% satisfaction, resulting in an overall score of 90.07%. The research results demonstrate that the AHP and TOPSIS algorithm can assist men in choosing appropriate perfume through its implementation in the system built by the research team, which was tested using a questionnaire
Implementation of Naïve Bayes Algorithm in Sentiment Analysis of Twitter Social Media Users Regarding Their Interest to Pay the Tax Wahyu Andrian, Bagas; Adline Twince Tobing, Fenina; Zuhdi Pane, Ivransa; Kusnadi, Adhi
International Journal of Science, Technology & Management Vol. 4 No. 6 (2023): November 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i6.1015

Abstract

Since 2008, tax revenue has failed to reach the target set in the State Budget each year. Until 2021, tax revenue managed to reach the target that had been targeted in the 2021 state budget. In the midst of improving tax revenue, towards the end of February 2023, a case involving the son of a Directorate General of Taxes (DGT) that made the father called by the Corruption Eradication Commission (CEC) to be asked for an explanation of his assets. After the case, there were many calls in the community to stop paying taxes, which was assessed by Tauhid Ahmad as Executive Director of Indef as a form of decreased trust in tax collecting institutions. This can affect the amount of revenue from taxes because trust in the government is one of the factors that tend to affect public compliance in paying taxes. Which can affect the amount of revenue from taxes because trust in the government is one of the factors that tend to affect public compliance in paying taxes. One of the crowded calls is the pros and cons of the tax boycott movement on Twitter. With the pros and cWith the pros and cons of the movement that can affect tax revenues on Twitter social media, an assessment based on sentiment analysis is needed which is divided into positive, neutral, or negative categories. Sentiment analysis in this research is carried out using three variations of Naïve Bayes assisted by the TF-IDF word weighting model, namely Gaussian Naïve Bayes, Multinomial Naïve Bayes, and Bernoulli Naïve Bayes. Then Confussion Matrix is used to evaluate the model by obtaining the accuracy, precission, recall, and f1-score values and the use of Synthetic Minority Oversampling Technique (SMOTE) to handle unbalanced data. The results of this study on unbalanced data, the implementation of Bernoulli Naïve Bayes using the SMOTE technique on a dataset comparison of 80:20 resulted in better performance than the variations of Gaussian and Multinomial Naïve Bayes with accuracy results of 91.03%, precision, 71.11%, recall 71.43%, and f1-score of 71.18%.
IMPLEMENTATION OF SIMPLE ADDITIVE WEIGHTING (SAW) METHOD FOR DESIGN AND BUILD DECISION SUPPORT SYSTEM OF LAPTOP SELECTION (Case Study: IT Store) Hariyanto Setiadi, Gregorius; Adline Twince Tobing, Fenina; Nainggolan, Rena
International Journal Science and Technology Vol. 2 No. 3 (2023): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v2i3.999

Abstract

Laptop is a small computer that is easy to carry anywhere, which makes everyone want to have one because of its convenience. However, the laptops currently available have various specifications, so users feel confused about choosing and buying the laptop they want. Therefore, this research was conducted to build a web-based decision-support system. The method used in this decision support system is simple additive weighting as a criterion for calculating laptop recommendations. The SAW method is a weighted addition method to determine the weighted sum to determine ranking. User satisfaction test results using a questionnaire using the End User Computing Satisfaction (EUCS) method The results of the calculation of the user satisfaction test obtained a result of 85.66%, which means that the system built can be useful for users in providing laptop recommendations.
Implementation of Octalysis-Based Gamification Method Cross-Platform For Design of Time Management Application Christopher, Kurnia; Adline Twince Tobing, Fenina
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3568

Abstract

Time management is an important skill in college. The greater the student's skill in managing his time, the greater the student's academic performance. However, there are students who do not have these skills and almost drop out of college. Therefore, application design and development are carried out.time management using the Octalysis framework gamification method, which is cross-platform-based so it can be accessed anywhere. The application has been completed and has been evaluated by 31 respondents using the Unified Theory of Acceptance and Use of Technology Model (UTAUT), amounting to 83.20%. From the results of this evaluation, it can be concluded that the time management application was well received by students
E-Commerce Product Review Sentiment Analysis: A Comparative Study of Naïve Bayes Classifier and Random Forest Algorithms on Marketplace Platforms Hassolthine, Cian Ramadhona; Haryanto, Toto; Adline Twince Tobing, Fenina; Ikhwani Saputra, Muhammad
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v12i1.4246

Abstract

Achieving customer satisfaction and trust is a major challenge for success in the business world. Entrepreneurs must identify problems that arise from reviews given by customers. However, reading and sorting each review is time-consuming and considered inefficient. In order to overcome this, a study was conducted that aims to analyze sentiment on products sold in the Shopee marketplace using the Naïve Bayes Classifier and Random Forest algorithms. The focus of this study is on product reviews from XYZ Store. The main objective of this study is to determine a more accurate and efficient algorithm in classifying review sentiment, which can help companies in marketing strategies and product development. The results of this study can provide insight for companies about consumer responses to marketed products, so that they can be used as a basis for making strategic decisions to improve the quality of services and products. The results of the Random Forest method classification produce superior predictions compared to the Naïve Bayes Classifier method with an accuracy value of 92.5%, precision of 93%, Recall of 92.5% and F1-Score of 90%.
Co-Authors Christopher, Kurnia Cian Ramadhona Hassolthine Dinarta, Farrel Endariahna Surbakti, Eunike Hariyanto Setiadi, Gregorius Irelynn, Maecyntha Ivan Wijaya, Aurelius kusnadi, adhi Muhammad Ikhwani Saputra Nainggolan, Rena Paskah, Richard Rayhan Harsono, William Richard Andrew Tisna Kusuma, Irene Toto Haryanto Wahyu Andrian, Bagas Zuhdi Pane, Ivransa