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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Masyarakat Informatika Bulletin of Electrical Engineering and Informatics Kreano, Jurnal Matematika Kreatif-Inovatif Sainteknol : Jurnal Sains dan Teknologi International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Abdimasku : Jurnal Pengabdian Masyarakat Unnes Journal of Mathematics Education Unnes Journal of Mathematics Journal of Community Empowerment Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Recursive Journal of Informatics Kreano, Jurnal Matematika Kreatif Inovatif Jurnal Dharma Indonesia Jurnal Abdi Negeri Recursive Journal of Informatics
Riza Arifudin
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Recursive Journal of Informatics

 1 
Application of Fuzzy Logic in Visual Novel Evaluation System Using Unity 3D Epafraditus Memoriano; Riza Arifudin
Recursive Journal of Informatics Vol. 3 No. 1 (2025): March 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v3i1.1158

Abstract

Purpose: Visual novels, narrative-driven games focused on character interaction, commonly employ point-based evaluation systems that struggle to represent the inherent complexity and uncertainty of player choices. This research introduces a novel approach: integrating fuzzy logic into visual novel evaluation systems using Unity 3D. Fuzzy logic addresses the limitations of point-based systems by accounting for the "fuzzy" nature of player choice and its varied impact on story progression and character relationships. Methods/Study design/approach: A visual novel game was developed in Unity 3D, incorporating a fuzzy logic evaluation system for scoring player choices and assessing route progress. Fuzzy sets and membership functions were defined for key aspects like emotional response, character alignment, and plot development. These aspects were dynamically evaluated based on player dialogue selection, and individual scores were aggregated to generate a final route evaluation. Result/Findings: Testing demonstrated seamless integration of the fuzzy logic system within the game engine. Evaluation of conversation choices and route progression yielded accurate and nuanced scores, reflecting the varying weight of each decision based on narrative context and character interaction. Fuzzy logic facilitated the interpretation of "fuzzy" player choices, translating them into meaningful information for story progression and character relationships. Novelty/Originality/Value: This research presents a novel and promising approach to visual novel evaluation by leveraging the strengths of fuzzy logic. It overcomes the limitations of traditional point-based systems, capturing the complexity and dynamism of player choices within the narrative. The dynamic and responsive evaluation results enhance player engagement and provide a more immersive gaming experience.
Implementation of the Term Frequency-Inverse Document Frequency Method for Mental Health Classification Using Algorithm Support Vector Machine Ilfa Minatika; Riza Arifudin
Recursive Journal of Informatics Vol. 3 No. 2 (2025): September 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v3i2.1921

Abstract

Abstract. Mental health is a person's emotional, social and psychological condition. A person's mental health level can be influenced by emotional experiences, behavior, environment and family educational background. A person's psychological well-being can be influenced by a person's behavior, where they live, the education they receive, and their emotional experiences. It is important not to underestimate the existence of mental health disorders because the number of cases is currently increasing. Purpose: Using SVM algorithm and TF-IDF method can produce good accuracy for classification text. Therefore this research aims to determine the implementation of the use of the TF-IDF method and the SVM algorithm in mental health classification and to determine the accuracy results of using these methods. Study Method/Design/Approach: The methods used in the research this for the mental health classification is Term Frequency-Inverse Document Frequency used in the vectorization process to convert text into a numerical representation, as well as using the Support Vector Machine algorithm in modeling. The dataset used is the Mental Health Corpus dataset obtained from the Kaggle website. This dataset consists of two classes containing text and labels totaling 27,977 data. Before applying the model, preprocessing is carried out first, namely cleaning the text using stopword removal and stemming. After cleaning the text, the next process is vectorization using CountVectorizer and TF-IDF. Results/Findings: In this study the SVM algorithm was used four kernels, namely the linear kernel, the RBF kernel, the polynomial kernel, and the later sigmoid kernel get the best accuracy results on the RBF kernel if compared to with other kernels. Accuracy results obtained _ of 92.62%, value precision of 92.64%, value recall 92.62%, and value f1-score 92.62%. Novelty/Originality/Value: So, it can be concluded that the application of the SVM algorithm and the TF-IDF method is possible used for classification mental health results mark high accuracy.
Implementation of Raita Algorithm in Manado-Indonesia Translation Application with Text Suggestion Using Levenshtein Distance Algorithm Novanka Agnes Sekartaji; Riza Arifudin
Recursive Journal of Informatics Vol. 2 No. 2 (2024): September 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/pkvgtg90

Abstract

Abstract. Manado City is one of the multidimensional and multicultural cities, possessing assets that are considered highly potential for development into tourism and development attractions. The current tourism assets being developed by the Manado City government are cultural tourism, as they hold a charm and allure for tourists. Hence, a communication tool in the form of a translation application is necessary for facilitating communication between visiting tourists and the native community of North Sulawesi, even for newcomers who intend to reside in North Sulawesi, given that the Manado language serves as the primary communication tool within the community. This research employs a combination of the Raita algorithm and the Levenshtein distance algorithm in its creation process, along with the confusion matrix method to calculate the accuracy of translation results using the Levenshtein distance algorithm with a text suggestion feature. The research begins by collecting a dataset consisting of Manado language vocabulary and their translations in Indonesia language, sourced from literature studies and original respondents from North Sulawesi, which have been validated by a validator to prevent translation data errors. The subsequent stage involves preprocessing the dataset, converting the entire content of the dataset to lowercase using the case folding process, and removing spaces at the start and end of texts using the trim function. Next, both algorithms are implemented, with the Raita algorithm serving for translation and the Levenshtein distance algorithm providing text suggestions for typing errors during the translation process. The accuracy results derived from the confusion matrix calculations during the translation process of 100 vocabulary words, accounting for typing errors, indicate that the Levenshtein distance algorithm is capable of effectively translating vocabulary accurately and correctly, even in the presence of typing errors, resulting in a high accuracy rate of 94,17%. Purpose: To determine the implementation of the Levenshtein distance and Raita algorithms in the process of using the Manado-Indonesian translation application, as well as the resulting accuracy level. Methods/Study design/approach: In this study, a combination of the Raita and Levenshtein distance algorithms is utilized in the translation application system, along with the confusion matrix method to calculate accuracy. Result/Findings: The accuracy achieved in the translation process using text suggestions from the Levenshtein distance algorithm is 94.17%. Novelty/Originality/Value: This research demonstrates that the combination of the Raita and Levenshtein distance algorithms yields optimal results in the vocabulary translation process and provides accurate outcomes from the use of effective text suggestions. This is attributed to the fact that nearly all the data used was successfully translated by the system, even in the presence of typographical errors.
Fruit Freshness Detection Using Android-Based Transfer Learning MobileNetV2 Irfan Fajar Muttaqin; Riza Arifudin
Recursive Journal of Informatics Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/e9h75682

Abstract

Abstract. Fruit is an important part of the source of food nutrition in humans. Fruit freshness is one of the most important factors in selecting fruit that is suitable for consumption. Fruit freshness is also an important factor in determining the price of fruit in the market. So it is very necessary to detect fruit freshness which can be done by machine. Take apples, bananas, and oranges as samples. The machine learning algorithm used in this study uses MobileNetV2 with transfer learning techniques. MobileNetV2 introduces many new ideas aimed at reducing the number of parameters to make it more efficient to run on mobile devices and achieve high classification accuracy. Transfer learning is used so that data does not need training from the start, so it only takes several networks from MobileNetV2 that have previously been trained and then retrained with a different purpose to improve accuracy results. Then the models that have been created are inserted into the application using Android Studio. Software testing is done through black box testing. Purpose: The purpose of this research is to design a machine-learning model to detect fruit freshness and then apply it to application Android smartphones. Methods/Study design/approach: The algorithm used in this study uses MobileNetV2 with transfer learning techniques. Models that have been created are inserted into the application using Android Studio. Result/Findings: The training results using MobileNetV2 transfer learning obtained an accuracy of 99.62% and the loss results obtained were 0.34%. The results of the application after testing using the black box testing method required improvements to the application and the machine learning model so that it can run optimally. Novelty/Originality/Value: Machine learning models that have been created using transfer learning MobileNetV2 are applied to Android applications so that they can be used by the public.
Stock Return Prediction Using Voting Regressor Ensemble Learning Ramadhan Ridho Arrohman; Riza Arifudin
Recursive Journal of Informatics Vol. 1 No. 2 (2023): September 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ntg4dt04

Abstract

Abstract. The value of return on stock prices is often used in predicting profits in the process of buying and selling shares based on the calculation of the return on investment. The calculation of the value of return on stock prices can be predicted automatically at certain periods, both weekly and daily Purpose: The problem faced is determining a good algorithm for making predictions due to fluctuating data on stock prices making it difficult to predict. Methods: The stages carried out by the researcher include the data preprocessing stage and then proceed to the Exploratory Data Analysis (EDA) stage to get a pattern from the data, followed by the modeling stage on the data. This research was developed using the Python programming language where the models used to make predictions can be obtained in real-time. Result: The results obtained in this study show that the Voting Regressor has the best model with an error rate of 0.032523 using Root Mean Square Error (RMSE). The results of this study can be further developed to automatically predict stock return values in the future.
Co-Authors Abas Setiawan Adha, Nugraha Saputra Adhitiya, Ervan Nur Adi Nur Cahyono Aditya, Rozak Ilham Aji Saputra Aji, Septiko Al Hakim, M. Faris Alamsyah - Alfatah, Abdul Muis Alfatah, Abdul Muis Amalia Fikri Utami Amin Suyitno Anggita, Anggita Anggyi Trisnawan Putra Ardhi Prabowo Arief Agoestanto Arief Broto Susilo Arif Widiyatmoko, Arif Ariska, Mega Arka Yanitama Arrohman, Ramadhan Ridho Asih, Tri Sri Noor Atikah Ari Pramesti, Atikah Ari Budi Prasetiyo, Budi Chakim, Muhamad Nur Choirunnisa, Rizkiyanti Clarissa Amanda Josaputri, Clarissa Amanda Damayanti, Angreswari Ayu Damayanti, Tiara Desy Fitria Astutianingtyas Devi, Feroza Rosalina Devi, Feroza Rosalina Dewi, Nuriana Rachmani Dian Tri Wiyanti Dwijanto Dwijanto, Dwijanto Endang Sugiharti, Endang Epafraditus Memoriano Faozi, Faozi Farkhan, Feri Fata, Muhamad Nasrul Fata, Muhamad Nasrul Fitriana, Jevita Dwi Habaib, Taufik Nur Hakim, M. Faris Al Hani'ah, Ulfatun Hardi Suyitno Hardianti, Ririn Dwi Hariyanto, Abdul Hidayat, Kukuh Triyuliarno Hidayat, Kukuh Triyuliarno Hikmah, Al Hikmawati, Zahra Shofia Hikmawati, Zahra Shofia Ichsan, Nur Ilfa Minatika Irfan Fajar Muttaqin Jumanto Jumanto, Jumanto Jumanto Unjung Kumalasari, Putri Laksita Kuncoro, Rizki Danang Kartiko Larasati, Ukhti Ikhsani Larasati, Ukhti Ikhsani Mashuri Mashuri Masrukan Masrukan Maulana, Bagus Surya Melissa Salma Darmawan Mohammad Asikin Much Aziz Muslim Mudzakir, Amat Muhammad Fariz Muttaqin, Irfan Fajar Novanka Agnes Sekartaji Nugroho, Ari Yulianto Nugroho, Muhammad Andi Nugroho, Prisma Bayu Pramadita, Anjar Aditya Putriaji Hendikawati Rachmawati, Eka Yuni Rachmawati, Eka Yuni Rahmanda, Primana Oky Rahmanda, Primana Oky Ramadhan Ridho Arrohman Ratna Dewi, Novi Rizki Nor Amelia Rochmad - Rofik Rofik, Rofik S.Pd. M Kes I Ketut Sudiana . Safri, Yofi Firdan Safri, Yofi Firdan Sasongko, Andry Scolastika Mariani Sekartaji, Novanka Agnes Setiawan, Danang Aji Stephani Diah Pamelasari Subarkah, Agus Subhan Subhan Sukmadewanti, Irahayu Sukmadewanti, Irahayu Susanto, Febri Trihanto, Wandha Budhi Trihanto, Wandha Budhi Utami, Hamdan Dian Jaya Rozi Hyang Utami, Hamdan Dian Jaya Rozi Hyang Wibowo, Eric Adie Widyawati, Kharisa Yahya Nur Ifriza Yulianto, Muhamad Maulana Yulianto, Muhamad Maulana Zaenal Abidin Zulfikar Adi Nugroho, Zulfikar Adi