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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Greenation International Journal of Engineering Science JIS Greenation International Journal of Engineering Science
Ximenes Guterres, Juvinal
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Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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 1 
Application of Environmentally Friendly Concepts in Sustainable Technology: A Conceptual Study as a Guide for Researchers Ximenes Guterres, Juvinal; Suprapto, Eko
Greenation International Journal of Engineering Science Vol. 2 No. 2 (2024): (GIJES) Greenation International Journal of Engineering Science (June - Agustus
Publisher : Greenation Research & Yayasan Global Resarch National

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijes.v2i2.205

Abstract

This study raises environmental and sustainability issues. This research consists of several parts. First, the literature review focuses on orientation towards the application of environmentally friendly concepts in the use of sustainable technology. Second, the research model and propositions developed in this study are based on a literature review of previous studies, such as the relationship between environmentally friendly orientation towards green innovation and green competitive advantage, as well as the relationship between green innovation. Furthermore, the application of environmentally friendly concepts is explored and linked to the use of sustainable technology. Where in the context of an environmentally friendly orientation strategy, companies have an important role in being aware and encouraged to produce environmentally friendly products to build sustainable competitive advantages in the long term. Thus, this study also shows that environmentally friendly product innovation and environmentally friendly competitive advantages are important strategies for reducing environmentally friendly organizational behavior.
Thesis Topic Modeling Study: Latent Dirichlet Allocation (LDA) and Machine Learning Approach Hairani, Hairani; Janhasmadja, Mengas; Tholib, Abu; Ximenes Guterres, Juvinal; Ariyanto, Yuri
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 3 No 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4375

Abstract

The thesis reports housed in the campus repository have yet to be analyzed to reveal valuable knowledge patterns. Analyzing trends in thesis research topics can facilitate the selection of research topics, aid in mapping research areas, and identify underexplored topics.Therefore, this research aims to model and classify thesis topics using Latent Dirichlet Allocation (LDA) and the Naïve Bayes and Support Vector Machine (SVM) methods. This study employs the LDA method for thesis topic modeling, while SVM and Naïve Bayes are used for classifying these topics. The research results show that LDA successfully modeled five of the most popular thesis topics, namely two related to computer networks, two on software engineering, and one on multimedia. For thesis topic classification, the SVM method demonstrated higher accuracy than Naïve Bayes, reaching 92.80% after the data was balanced using Synthetic Minority Oversampling Technique (SMOTE). The implication of this study is that the topic modeling approach using LDA is able to identify dominant thesis topics. In addition, the SVM classification results obtained better accuracy than Naïve Bayes in the thesis topic classification task.
Combination Forward Chaining and Certainty Factor Methods for Selecting the Best Herbs to Support Independent Health Azwar, Muhamad; Winarni Sofya, Sri; Malika, Riwayati; Hairani, Hairani; Ximenes Guterres, Juvinal
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 24 No 2 (2025)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4485

Abstract

The use of herbal medicine as an alternative treatment is increasingly popular due to its natural benefits and cultural significance. However, a lack of public knowledge about the effectiveness, appropriate dosages, and processing methods of herbal remedies poses a significant barrier to their proper utilization. This knowledge gap often leads to suboptimal or even unsafe usage of herbal medicines. To address this issue, this study proposes an application-based system combining the Forward Chaining and Certainty Factor methods to provide personalized recommendations for the best herbal remedies supporting self-health management. The research aims to enhance accessibility to reliable information on herbal treatments while ensuring accurate and user-specific recommendations. By utilizing the ForwardChaining and Certainty Factor method, this system identifies suitable herbal plants based on the type of disease, processing techniques, recommended dosages, and duration of treatment. Meanwhile, the Certainty Factor method calculates the level of certainty for each recommendation provided. The study’s results showed a validation rate of 90%, indicating that the combination of these two methods effectively bridges the gap between traditional herbal knowledge and modern health needs. This study concludes that the system offers a practical tool for individuals to select and use herbal treatments safely and effectively, promoting better health outcomes.
Application of Environmentally Friendly Concepts in Sustainable Technology: A Conceptual Study as a Guide for Researchers Ximenes Guterres, Juvinal; Suprapto, Eko
Greenation International Journal of Engineering Science Vol. 2 No. 2 (2024): (GIJES) Greenation International Journal of Engineering Science (June - Agustus
Publisher : Greenation Research & Yayasan Global Resarch National

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijes.v2i2.205

Abstract

This study raises environmental and sustainability issues. This research consists of several parts. First, the literature review focuses on orientation towards the application of environmentally friendly concepts in the use of sustainable technology. Second, the research model and propositions developed in this study are based on a literature review of previous studies, such as the relationship between environmentally friendly orientation towards green innovation and green competitive advantage, as well as the relationship between green innovation. Furthermore, the application of environmentally friendly concepts is explored and linked to the use of sustainable technology. Where in the context of an environmentally friendly orientation strategy, companies have an important role in being aware and encouraged to produce environmentally friendly products to build sustainable competitive advantages in the long term. Thus, this study also shows that environmentally friendly product innovation and environmentally friendly competitive advantages are important strategies for reducing environmentally friendly organizational behavior.
Combination Forward Chaining and Certainty Factor Methods for Selecting the Best Herbs to Support Independent Health Azwar, Muhamad; Winarni Sofya, Sri; Malika, Riwayati; Hairani, Hairani; Ximenes Guterres, Juvinal
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4485

Abstract

The use of herbal medicine as an alternative treatment is increasingly popular due to its natural benefits and cultural significance. However, a lack of public knowledge about the effectiveness, appropriate dosages, and processing methods of herbal remedies poses a significant barrier to their proper utilization. This knowledge gap often leads to suboptimal or even unsafe usage of herbal medicines. To address this issue, this study proposes an application-based system combining the Forward Chaining and Certainty Factor methods to provide personalized recommendations for the best herbal remedies supporting self-health management. The research aims to enhance accessibility to reliable information on herbal treatments while ensuring accurate and user-specific recommendations. By utilizing the ForwardChaining and Certainty Factor method, this system identifies suitable herbal plants based on the type of disease, processing techniques, recommended dosages, and duration of treatment. Meanwhile, the Certainty Factor method calculates the level of certainty for each recommendation provided. The study’s results showed a validation rate of 90%, indicating that the combination of these two methods effectively bridges the gap between traditional herbal knowledge and modern health needs. This study concludes that the system offers a practical tool for individuals to select and use herbal treatments safely and effectively, promoting better health outcomes.
SISTEM KONTROL LAMPU RUANGAN BERBASIS VISUAL BASIC.NET DAN MICROKONTROLLER ATMEGA8535 ximenes guterres, Juvinal
Jurnal Informatika SIMANTIK Vol 4 No 2 (2019): Jurnal Informatika SIMANTIK
Publisher : Fakultas Sains dan Teknologi Universitas Panca Sakti Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perangkat elektronik lampu sangat dibutuhakan untuk memberikan cahaya pada malam hari dimana lampu mengubah energi listrik menjadi cahaya, penerangan sangat berhubungan erat dengan rasa nyaman, rasa tenang, dan ketenteraman. energi listrik tidak hanya untuk kebutuhan rumah tangga namun sangat penting bagi perusahaan maupun, instansi pemerintah, dan akademik. Menyalakan dan mematikan lampu terutama pada malam hari dan dioperasikan secara manual sebenarnya bukan masalah akan tetapi dengan ruangan yang banyak dan lampu yang digunakan pun dengan jumlah yang banyak maka menyalakan lampu pada malam hari dan mematikannya pada siang hari akan menjadi kendala yang besar. Oleh karen itu  penulis berniat untuk membangun sistem kontrol lampu rungan dengan mikrokontroller atmega8535 dan menggunakan komputer untuk mengontrol semua lampu dibeberapa ruangan dan tidak perlu mendatanggi setiap ruangan untuk mematikan dan menyalakan lampu
Combination of Smote and Random Forest Methods for Lung Cancer Classification Michael Lauw, Christopher; Hairani, Hairani; Saifuddin, Ilham; Ximenes Guterres, Juvinal; Maariful Huda, Muhammad; Mayadi, Mayadi
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 2 No. 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3333

Abstract

Lung cancer is a network of cells that grow abnormally in the lungs. Lung cancer has four severity levels, namely stages 1 to 4. If lung cancer is not treated quickly, it is at risk of causing death. This research aimed to combine Synthetic Minority Over-sampling (Smote) and Random Forest methods for lung cancer classification. The method used was a combination of Smote and Random Forest. Smote was used to balance the data, while Random Forest was used to classify lung cancer data. The results showed that the combination of Smote and Random Forest methods obtained an accuracy of 94.1%, sensitivity of 94.5, and specificity of 93.7%. Meanwhile, without Smote, the accuracy is 89.1%, sensitivity is 55%, and specificity is 94.5%. The use of Smote can improve the performance of the Random Forest classification method based on accuracy and sensitivity. There was an increase of 5% in accuracy and a 39% increase in sensitivity.
Exploring Customer Purchasing Patterns: A Study Utilizing FP-Growth Algorithm on Supermarket Transaction Data Hairani, Hairani; Ximenes Guterres, Juvinal
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 3 No. 1 (2024): March 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i1.3874

Abstract

The need to analyze consumer purchasing patterns using association techniques also lies in the increasingly fierce competition in the retail market. Supermarkets face the challenge of understanding their customers' buying patterns. By utilizing association techniques, supermarkets can identify customer buying trends and quickly and appropriately adjust their strategies. Thus, analyzing consumer purchasing patterns using association techniques is no longer an option but an urgent need for supermarkets that want to survive and thrive in a changing market. Therefore, this study aimed to analyze purchasing patterns in supermarkets using the FP-Growth method to understand purchasing behavior and identify relevant patterns from transaction data. The method used in this research was the FP-Growth association method to create association rules from customer transaction data. The findings of this research were the use of the FP-Growth method in analyzing supermarket customer purchasing patterns, which obtained 10 association rules for 2 itemsets and 11 association rules for 3 itemsets based on a minimum Support value of 30% and a minimum Confidence of 70%. The association rules generated by the FP-Growth method on 2 itemsets and 3 itemsets simultaneously bring up items often purchased by customers with the same pattern, namely Cooking Oil, Eggs, Flour, and Candy. This research concludes that the association rules formed can be used as a benchmark by supermarkets in preparing stock items and making strategies to increase sales for more profit.
Thesis Topic Modeling Study: Latent Dirichlet Allocation (LDA) and Machine Learning Approach Hairani, Hairani; Janhasmadja, Mengas; Tholib, Abu; Ximenes Guterres, Juvinal; Ariyanto, Yuri
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 3 No. 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4375

Abstract

The thesis reports housed in the campus repository have yet to be analyzed to reveal valuable knowledge patterns. Analyzing trends in thesis research topics can facilitate the selection of research topics, aid in mapping research areas, and identify underexplored topics.Therefore, this research aims to model and classify thesis topics using Latent Dirichlet Allocation (LDA) and the Naïve Bayes and Support Vector Machine (SVM) methods. This study employs the LDA method for thesis topic modeling, while SVM and Naïve Bayes are used for classifying these topics. The research results show that LDA successfully modeled five of the most popular thesis topics, namely two related to computer networks, two on software engineering, and one on multimedia. For thesis topic classification, the SVM method demonstrated higher accuracy than Naïve Bayes, reaching 92.80% after the data was balanced using Synthetic Minority Oversampling Technique (SMOTE). The implication of this study is that the topic modeling approach using LDA is able to identify dominant thesis topics. In addition, the SVM classification results obtained better accuracy than Naïve Bayes in the thesis topic classification task.
Co-Authors Abu Tholib Eko Suprapto, Eko Hairani Hairani Janhasmadja, Mengas Maariful Huda, Muhammad Malika, Riwayati Mayadi, Mayadi Michael Lauw, Christopher Muhamad Azwar, Muhamad Saifuddin, Ilham Sri Winarni Sofya Winarni Sofya, Sri Yuri Ariyanto