Pub Date : 2024-07-09DOI: 10.34148/teknika.v13i2.862
B. Yulianto, R. M. Atok
Pengoperasian pelabuhan secara dasar meliputi berbagai kegiatan pelayanan, salah satu proses pelayanan kegiatan di pelabuhan yaitu pelayanan pemanduan dan penundaan kapal. Salah satu langkah yang dibutuhkan dalam proses penetapan kapal tunda dalam pelayanan pemanduan dan penundaan kapal yaitu pemilihan konfigurasi Kapal Tunda. Penelitian ini menguji performa klasifikasi Support Vector Machine (SVM) dan Naïve Bayes Classifier (NBC) pada data Laporan Harian Gerakan Kapal (LHGK) di Pelabuhan Tanjung Priok selama periode 2021 untuk proses pemodelan dan evaluasi. Penelitian ini bertujuan untuk membuat modelan prediksi dalam penentuan konfigurasi Kapal Tunda, evaluasi hasil model prediksi untuk memilih konfigurasi kapal tunda di Pelabuhan Tanjung Priok. Dengan menerapkan model klasifikasi NBC dan SVM yang ditingkatkan dengan kernel Linier dan RBF, termasuk juga pemilihan fitur baik untuk SVM dan Naïve Bayes. Hasil uji perbandingan model prediksi antara SVM dan NBC menujukan bahwa klasifikasi SVM memberikan hasil yang paling optimal, yaitu menggunakan kernel linier pada nilai C=10, diperoleh akurasi sebesar 84,7%, recall sebesar 84,7%, F1-score sebesar 88,7%, dan akurasi sebesar 88,7%. Penelitian ini dimasa yang akan datang dapat dimanfaatkan dalam proses pengambilan keputusan dalam menentukan susunan konfigurasi Kapal Tunda oleh petugas pelabuhan.
{"title":"Algoritma Machine Learning Dalam Melakukan Prediksi Pemilihan Konfigurasi Kapal Tunda di Pelabuhan Tanjung Priok","authors":"B. Yulianto, R. M. Atok","doi":"10.34148/teknika.v13i2.862","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.862","url":null,"abstract":"Pengoperasian pelabuhan secara dasar meliputi berbagai kegiatan pelayanan, salah satu proses pelayanan kegiatan di pelabuhan yaitu pelayanan pemanduan dan penundaan kapal. Salah satu langkah yang dibutuhkan dalam proses penetapan kapal tunda dalam pelayanan pemanduan dan penundaan kapal yaitu pemilihan konfigurasi Kapal Tunda. Penelitian ini menguji performa klasifikasi Support Vector Machine (SVM) dan Naïve Bayes Classifier (NBC) pada data Laporan Harian Gerakan Kapal (LHGK) di Pelabuhan Tanjung Priok selama periode 2021 untuk proses pemodelan dan evaluasi. Penelitian ini bertujuan untuk membuat modelan prediksi dalam penentuan konfigurasi Kapal Tunda, evaluasi hasil model prediksi untuk memilih konfigurasi kapal tunda di Pelabuhan Tanjung Priok. Dengan menerapkan model klasifikasi NBC dan SVM yang ditingkatkan dengan kernel Linier dan RBF, termasuk juga pemilihan fitur baik untuk SVM dan Naïve Bayes. Hasil uji perbandingan model prediksi antara SVM dan NBC menujukan bahwa klasifikasi SVM memberikan hasil yang paling optimal, yaitu menggunakan kernel linier pada nilai C=10, diperoleh akurasi sebesar 84,7%, recall sebesar 84,7%, F1-score sebesar 88,7%, dan akurasi sebesar 88,7%. Penelitian ini dimasa yang akan datang dapat dimanfaatkan dalam proses pengambilan keputusan dalam menentukan susunan konfigurasi Kapal Tunda oleh petugas pelabuhan.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":"97 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.34148/teknika.v13i2.906
Aldrich Deril Christian Zebua, Dedy Yehezkiel Marbun, Felix Thedora, Mawaddah Harahap
Lung cancer has become one of the most frightening specters in the world of health, leading many people to death each year. Therefore, the classification of lung cancer types is very important to determine the appropriate treatment steps. Considering that lung cancer treatment in the early stages is far more effective and efficient, accurate classification is the key to improving survival rates. This research focuses on the classification of three common lung cancer types: Adenocarcinoma, Large Cell Carcinoma, and Squamous Cell Carcinoma. To achieve optimal results, this study utilizes the ResNet architecture, a deep neural network model that has demonstrated its capabilities in various fields. Before being used on the model, the dataset containing lung X-ray images of patients undergoes preprocessing. At this stage, each image is resized to 256x256 pixels to ensure uniformity and compatibility with the model. Furthermore, this research trains various ResNet models, ranging from ResNet50, ResNet101, to ResNet152, which is the model with the most parameters. By comparing the performance of each model, this study finds that all trained ResNet models are capable of producing good accuracy in classifying lung cancer types. Among these models, ResNet152 demonstrates the most superior performance with an accuracy of 89%. This result suggests that the ResNet architecture has great potential to be used as an aid in classifying lung cancer types with a high level of accuracy. This research makes a significant contribution to the effort to improve the diagnosis and treatment of lung cancer, paving the way for a brighter future for lung cancer patients.
{"title":"Classification of Lung Cancer with Convolutional Neural Network Method Using ResNet Architecture","authors":"Aldrich Deril Christian Zebua, Dedy Yehezkiel Marbun, Felix Thedora, Mawaddah Harahap","doi":"10.34148/teknika.v13i2.906","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.906","url":null,"abstract":"Lung cancer has become one of the most frightening specters in the world of health, leading many people to death each year. Therefore, the classification of lung cancer types is very important to determine the appropriate treatment steps. Considering that lung cancer treatment in the early stages is far more effective and efficient, accurate classification is the key to improving survival rates. This research focuses on the classification of three common lung cancer types: Adenocarcinoma, Large Cell Carcinoma, and Squamous Cell Carcinoma. To achieve optimal results, this study utilizes the ResNet architecture, a deep neural network model that has demonstrated its capabilities in various fields. Before being used on the model, the dataset containing lung X-ray images of patients undergoes preprocessing. At this stage, each image is resized to 256x256 pixels to ensure uniformity and compatibility with the model. Furthermore, this research trains various ResNet models, ranging from ResNet50, ResNet101, to ResNet152, which is the model with the most parameters. By comparing the performance of each model, this study finds that all trained ResNet models are capable of producing good accuracy in classifying lung cancer types. Among these models, ResNet152 demonstrates the most superior performance with an accuracy of 89%. This result suggests that the ResNet architecture has great potential to be used as an aid in classifying lung cancer types with a high level of accuracy. This research makes a significant contribution to the effort to improve the diagnosis and treatment of lung cancer, paving the way for a brighter future for lung cancer patients.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":"99 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.34148/teknika.v13i2.933
Liliana, Daniel Soesanto, Bambang Prijambodo, Jasti Ohanna
Companies increasingly adopt software as a Service (SaaS) as a project management tool. SaaS offers greater flexibility, availability, and accessibility than traditional information system software. In this study, SaaS is used as the basis for creating project management applications, including recording work plans, the progress of each user's performance, and meeting documentation. The stages of the literature study are carried out by looking at journals and books. The trial was carried out using black-box testing. Verification trials are carried out by involving a team of programmers to see the flow of the system algorithm. Validation trials are carried out by asking various users involved in project implementation to try the system and asking users to fill out questionnaires related to the ease of use of project management features. The two stages of the trial showed good results, as evidenced by 77.8% of users stating that the SaaS concept really helped them with the flexibility of system installation with a short waiting time. Meanwhile, 76.16% of users stated that the features provided and their configuration could help them in project management. The research results show that SaaS has great potential to help companies to manage projects effectively. In future research, various factors in different project management can be explored deeper, so that SaaS becomes more configurable and used by a wider variety of users.
{"title":"Exploration of Software as a Service (SaaS) as a Project Management Tools","authors":"Liliana, Daniel Soesanto, Bambang Prijambodo, Jasti Ohanna","doi":"10.34148/teknika.v13i2.933","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.933","url":null,"abstract":"Companies increasingly adopt software as a Service (SaaS) as a project management tool. SaaS offers greater flexibility, availability, and accessibility than traditional information system software. In this study, SaaS is used as the basis for creating project management applications, including recording work plans, the progress of each user's performance, and meeting documentation. The stages of the literature study are carried out by looking at journals and books. The trial was carried out using black-box testing. Verification trials are carried out by involving a team of programmers to see the flow of the system algorithm. Validation trials are carried out by asking various users involved in project implementation to try the system and asking users to fill out questionnaires related to the ease of use of project management features. The two stages of the trial showed good results, as evidenced by 77.8% of users stating that the SaaS concept really helped them with the flexibility of system installation with a short waiting time. Meanwhile, 76.16% of users stated that the features provided and their configuration could help them in project management. The research results show that SaaS has great potential to help companies to manage projects effectively. In future research, various factors in different project management can be explored deeper, so that SaaS becomes more configurable and used by a wider variety of users.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":"119 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141665293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-06DOI: 10.34148/teknika.v13i2.881
Asfa Dhevi Azzumzumi, M. Hanafi, W. M. P. Dhuhita
COVID-19 dan penyakit paru-paru telah menjadi faktor utama penyebab kematian manusia di seluruh dunia. Kematian pasien dipengaruhi oleh keterlambatan deteksi dini. Sebagian besar profesional medis menggunakan gambar untuk mengidentifikasi kondisi paru-paru. Namun, para ahli yang dapat me-diagnosis dengan gambar sangat terbatas. Diagnosis gambar mendiagnosa menggunakan penglihatan manusia secara konvensional. Klasifikasi penyakit paru-paru sangat bervariasi. Masalah yang disebutkan di atas menunjukkan bahwa deteksi penyakit paru-paru dengan Artificial Intelligence (AI) yang efektif telah ditetapkan. Namun, sebagian besar hasil penyakit paru-paru salah didiagnosis. Bagi pasien, masalah ini menjadi masalah besar. Bertujuan untuk menangani klasifikasi penyakit paru-paru dengan deteksi kesalahan yang tinggi, kami menggunakan beberapa teknik pre-processing gambar dan menerapkan model pembelajaran mendalam dalam EfficientNet. Model Pre-processing termasuk augmentasi, peningkatan white balance, dan peningkatan kontras. Berdasarkan penelitian sebelumnya, mayoritas proses analisa gambar medis mengalami kualitas gambar yang rendah. Berdasarkan laporan eksperimen, model yang kami usulkan mencapai hasil yang signifikan dalam mengurangi kesalahan deteksi pada klasifikasi penyakit paru-paru. Dimana hasil F1 score-nya 0,97, recallnya 0,98, presisinya 0,96, dan akurasinya 0,97. Kami mempertimbangkan untuk menggunakan model yang kami usulkan dalam klasifikasi multi-class. Kami mengevaluasi model yang kami usulkan menggunakan evaluation metric dan AUC Curve.
{"title":"Klasifikasi Penyakit Paru-Paru Berdasarkan Peningkatan Kualitas Kontras dan EfficientNet Menggunakan Gambar X-Ray","authors":"Asfa Dhevi Azzumzumi, M. Hanafi, W. M. P. Dhuhita","doi":"10.34148/teknika.v13i2.881","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.881","url":null,"abstract":"COVID-19 dan penyakit paru-paru telah menjadi faktor utama penyebab kematian manusia di seluruh dunia. Kematian pasien dipengaruhi oleh keterlambatan deteksi dini. Sebagian besar profesional medis menggunakan gambar untuk mengidentifikasi kondisi paru-paru. Namun, para ahli yang dapat me-diagnosis dengan gambar sangat terbatas. Diagnosis gambar mendiagnosa menggunakan penglihatan manusia secara konvensional. Klasifikasi penyakit paru-paru sangat bervariasi. Masalah yang disebutkan di atas menunjukkan bahwa deteksi penyakit paru-paru dengan Artificial Intelligence (AI) yang efektif telah ditetapkan. Namun, sebagian besar hasil penyakit paru-paru salah didiagnosis. Bagi pasien, masalah ini menjadi masalah besar. Bertujuan untuk menangani klasifikasi penyakit paru-paru dengan deteksi kesalahan yang tinggi, kami menggunakan beberapa teknik pre-processing gambar dan menerapkan model pembelajaran mendalam dalam EfficientNet. Model Pre-processing termasuk augmentasi, peningkatan white balance, dan peningkatan kontras. Berdasarkan penelitian sebelumnya, mayoritas proses analisa gambar medis mengalami kualitas gambar yang rendah. Berdasarkan laporan eksperimen, model yang kami usulkan mencapai hasil yang signifikan dalam mengurangi kesalahan deteksi pada klasifikasi penyakit paru-paru. Dimana hasil F1 score-nya 0,97, recallnya 0,98, presisinya 0,96, dan akurasinya 0,97. Kami mempertimbangkan untuk menggunakan model yang kami usulkan dalam klasifikasi multi-class. Kami mengevaluasi model yang kami usulkan menggunakan evaluation metric dan AUC Curve.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":" 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141672569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-06DOI: 10.34148/teknika.v13i2.857
Kelvin Ferdinand, Kevin Jonathan JM, Darius Andana Haris
This study investigates the design and development process of “Super Journey”, a 2D platformer mobile game aimed at enhancing user engagement and satisfaction through innovative game mechanics and design. Utilizing the Agile methodology, the development stages included conceptualization, design, implementation using the Unity game engine, and iterative testing and evaluation based on user feedback. This development process involved crafting a detailed game design document, creating initial sketches and prototypes, and integrating graphical elements, animations, and game mechanics. The game features 3 levels with simple controls, visually appealing pixel art, and progressively challenging levels. A survey conducted with 20 participants revealed high overall satisfaction (4.15 out of 5), with particular praise for level design (4.25) and game mechanics (4.2). Feedback indicated areas for improvement, such as balancing difficulty levels and incorporating more diverse obstacles and enemies. The findings underscore the importance of agile, user-centered design in game development and provide insights for future iterations to further enhance the gaming experience. “Super Journey” exemplifies the effective integration of classic platformer elements with modern innovations, highlighting its potential in the competitive mobile gaming market. The results of this research are expected to serve as a reference and inspiration for other game developers to create superior products by combining innovative technology and thoughtful design.
{"title":"Innovative Approach of 2D Platformer Mobile Game Development “Super Journey”","authors":"Kelvin Ferdinand, Kevin Jonathan JM, Darius Andana Haris","doi":"10.34148/teknika.v13i2.857","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.857","url":null,"abstract":"This study investigates the design and development process of “Super Journey”, a 2D platformer mobile game aimed at enhancing user engagement and satisfaction through innovative game mechanics and design. Utilizing the Agile methodology, the development stages included conceptualization, design, implementation using the Unity game engine, and iterative testing and evaluation based on user feedback. This development process involved crafting a detailed game design document, creating initial sketches and prototypes, and integrating graphical elements, animations, and game mechanics. The game features 3 levels with simple controls, visually appealing pixel art, and progressively challenging levels. A survey conducted with 20 participants revealed high overall satisfaction (4.15 out of 5), with particular praise for level design (4.25) and game mechanics (4.2). Feedback indicated areas for improvement, such as balancing difficulty levels and incorporating more diverse obstacles and enemies. The findings underscore the importance of agile, user-centered design in game development and provide insights for future iterations to further enhance the gaming experience. “Super Journey” exemplifies the effective integration of classic platformer elements with modern innovations, highlighting its potential in the competitive mobile gaming market. The results of this research are expected to serve as a reference and inspiration for other game developers to create superior products by combining innovative technology and thoughtful design.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-06DOI: 10.34148/teknika.v13i2.854
Nicholas Hiu, Yana Erlyana
The rapid growth of the e-commerce industry, driven by technological advancements and increased internet access, has intensified competition for attracting and retaining customers. In Indonesia, the shift from desktop computers to smartphones has made mobile commerce (m-commerce) increasingly dominant. PT Datascrip, a leading Indonesian company, launched Datascripmall, a B2C and B2B e-commerce marketplace, in August 2020. Despite initial success, a decline in mobile app users indicated a need for an improved user interface (UI) and user experience (UX). This research underscores the urgent need to redesign the Datascripmall mobile app's UI using the User-Centered Design (UCD) methodology, focusing on user needs and preferences. The study employed questionnaires to identify the need for clearer explanations and a more consistent interface. Adding smart features and shortcuts for experienced users was found to boost efficiency and satisfaction. Interviews with the Datascripmall manager confirmed the necessity of a UI/UX redesign to enhance mobile app user numbers. The UCD process involved understanding the context of use, specifying user requirements, designing solutions, and evaluating them against these requirements. The study highlights the benefits of a redesigned UI/UX, enhancing the user experience with greater intuitiveness and engagement. Both qualitative and quantitative data support recommendations for creating a user-friendly interface and increasing overall user engagement. The result of this redesign is a prototype framework developed using Figma, which encompasses page structure, features, and content, providing a comprehensive view of the Datascripmall application UI design. This redesign aims to enhance user satisfaction and increase user numbers, leading to a more comfortable and engaging shopping experience.
{"title":"Redesigning User Interface of Datascripmall Mobile Apps Using User Centered Design Method","authors":"Nicholas Hiu, Yana Erlyana","doi":"10.34148/teknika.v13i2.854","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.854","url":null,"abstract":"The rapid growth of the e-commerce industry, driven by technological advancements and increased internet access, has intensified competition for attracting and retaining customers. In Indonesia, the shift from desktop computers to smartphones has made mobile commerce (m-commerce) increasingly dominant. PT Datascrip, a leading Indonesian company, launched Datascripmall, a B2C and B2B e-commerce marketplace, in August 2020. Despite initial success, a decline in mobile app users indicated a need for an improved user interface (UI) and user experience (UX). This research underscores the urgent need to redesign the Datascripmall mobile app's UI using the User-Centered Design (UCD) methodology, focusing on user needs and preferences. The study employed questionnaires to identify the need for clearer explanations and a more consistent interface. Adding smart features and shortcuts for experienced users was found to boost efficiency and satisfaction. Interviews with the Datascripmall manager confirmed the necessity of a UI/UX redesign to enhance mobile app user numbers. The UCD process involved understanding the context of use, specifying user requirements, designing solutions, and evaluating them against these requirements. The study highlights the benefits of a redesigned UI/UX, enhancing the user experience with greater intuitiveness and engagement. Both qualitative and quantitative data support recommendations for creating a user-friendly interface and increasing overall user engagement. The result of this redesign is a prototype framework developed using Figma, which encompasses page structure, features, and content, providing a comprehensive view of the Datascripmall application UI design. This redesign aims to enhance user satisfaction and increase user numbers, leading to a more comfortable and engaging shopping experience.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":" 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.34148/teknika.v13i2.897
Kent Vin Lievianto, Yana Erlyana
Indonesia is one of the largest archipelagic countries in the world. Indonesia has very rich biodiversity but is facing serious threats. Many endemic species are threatened with extinction due to factors such as climate change, habitat loss, illegal trade and poaching. This research highlights the urgent need for education about endangered animals, with a focus on the Javan Rhinoceros (Rhinoceros Sondaicus) which is categorized as Critically Endangered by the International Union for Conservation of Nature (IUCN). This research was created for Animalium, a research facility under the National Research and Innovation Agency (BRIN), which still lacks interactive Virtual Reality media for education. The main aim of this research is to design a 3D VR animation about the Javan Rhino to increase education and awareness about its conservation. Interviews with educators at Animalium revealed the need for such a medium to prevent damage to physical replicas and to engage visitors, especially children, in a more immersive and interactive learning experience. Observations showed that there were no 3D VR-based educational tools in the facility. The implementation of VR technology has the potential to significantly increase visitor engagement and experiences regarding the conservation of endangered species, in line with Sustainable Development Goals (SDGs) related to terrestrial ecosystems. This research highlights the potential of VR to provide immersive and interactive educational experiences, increase public awareness, and support wildlife conservation efforts, especially the Javan Rhino. The result of this design is an Unreal Engine project file that can be used in Animalium to create an immersive and interactive educational experience, increase public awareness, and support wildlife conservation efforts, especially the Javan Rhino.
印度尼西亚是世界上最大的群岛国家之一。印尼拥有非常丰富的生物多样性，但也面临着严重的威胁。由于气候变化、栖息地丧失、非法贸易和偷猎等因素，许多特有物种濒临灭绝。这项研究强调了开展濒危动物教育的迫切需要，重点关注被世界自然保护联盟（IUCN）列为极度濒危的爪哇犀牛（Rhinoceros Sondaicus）。这项研究是为国家研究与创新局（BRIN）下属的研究机构 Animalium 制作的，该机构仍然缺乏用于教育的交互式虚拟现实媒体。这项研究的主要目的是设计一个关于爪哇犀牛的三维虚拟现实动画，以提高教育水平和保护意识。与动物馆教育工作者的访谈显示，需要这样一种媒体来防止实体复制品受到损坏，并让游客（尤其是儿童）获得更加身临其境的互动学习体验。观察结果表明，该设施没有基于 3D VR 的教育工具。根据与陆地生态系统有关的可持续发展目标（SDGs），实施 VR 技术有可能大大提高游客在保护濒危物种方面的参与度和体验。这项研究强调了 VR 在提供沉浸式互动教育体验、提高公众意识和支持野生动物保护工作（尤其是爪哇犀牛）方面的潜力。本设计的成果是一个虚幻引擎项目文件，可用于 Animalium，以创建身临其境的互动教育体验，提高公众意识，支持野生动物保护工作，尤其是爪哇犀牛。
{"title":"The Design of 3D Virtual Reality Animation of Javan Rhino for Educational Media of Endangered Animals in Indonesia","authors":"Kent Vin Lievianto, Yana Erlyana","doi":"10.34148/teknika.v13i2.897","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.897","url":null,"abstract":"Indonesia is one of the largest archipelagic countries in the world. Indonesia has very rich biodiversity but is facing serious threats. Many endemic species are threatened with extinction due to factors such as climate change, habitat loss, illegal trade and poaching. This research highlights the urgent need for education about endangered animals, with a focus on the Javan Rhinoceros (Rhinoceros Sondaicus) which is categorized as Critically Endangered by the International Union for Conservation of Nature (IUCN). This research was created for Animalium, a research facility under the National Research and Innovation Agency (BRIN), which still lacks interactive Virtual Reality media for education. The main aim of this research is to design a 3D VR animation about the Javan Rhino to increase education and awareness about its conservation. Interviews with educators at Animalium revealed the need for such a medium to prevent damage to physical replicas and to engage visitors, especially children, in a more immersive and interactive learning experience. Observations showed that there were no 3D VR-based educational tools in the facility. The implementation of VR technology has the potential to significantly increase visitor engagement and experiences regarding the conservation of endangered species, in line with Sustainable Development Goals (SDGs) related to terrestrial ecosystems. This research highlights the potential of VR to provide immersive and interactive educational experiences, increase public awareness, and support wildlife conservation efforts, especially the Javan Rhino. The result of this design is an Unreal Engine project file that can be used in Animalium to create an immersive and interactive educational experience, increase public awareness, and support wildlife conservation efforts, especially the Javan Rhino.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141678412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.34148/teknika.v13i2.876
Raenald Syaputra, Taghfirul Azhima Yoga Siswa, Wawan Joko Pranoto
Banjir merupakan salah satu bencana alam yang sering terjadi di Indonesia, termasuk di Kota Samarinda dengan 18-33 titik desa terdampak dari tahun 2018-2021. Penggunaan machine learning dalam mengklasifikasi bencana banjir sangat penting untuk memprediksi kejadian di masa mendatang. Beberapa penelitian sebelumnya terkait klasifikasi data banjir dalam 3 tahun terakhir telah dilakukan. Namun, dari beberapa penelitian tersebut memunculkan masalah terkait dengan dataset high dimensional yang dapat menurunkan performa model klasifikasi dan menyebabkan overfitting. Selain itu, masalah lain juga muncul dalam hal imbalance data yang menyebabkan bias terhadap kelas mayoritas dan representasi yang tidak akurat. Oleh karena itu, permasalahan dataset high dimensional dan imbalance data merupakan tantangan spesifik yang harus diatas dalam klasifkasi data banjir Kota Samarinda. Penelitian ini bertujuan mengidentifkasi fitur-fitur yang diperoleh dari seleksi fitur Genetic Algorithm (GA) yang memiliki pengaruh terhadap akurasi klasifikasi data banjir Kota Samarinda menggunakan algoritma Support Vector Machine (SVM), serta meningkatkan akurasi klasifikasi data banjir di Kota Samarinda dengan mengimplementasikan algoritma SVM yang dikombinasikan dengan metode Synthetic Minority Oversampling Technique (SMOTE) untuk oversampling, seleksi fitur dengan GA dan optimasi menggunakan Particle Swarm Optimization (PSO). Teknik validasi yang digunakan adalah 10-fold cross validation dan evaluasi performa menggunakan confusion matrix. Data yang digunakan berasal dari BPBD (Badan Penanggulangan Bencana Daerah) dan BMKG (Badan Meteorologi, Klimatologi, dan Geofisika) Kota Samarinda pada tahun 2021-2023 terdiri dari 11 fitur dan 1.095 record. Hasil penelitian menunjukkan bahwa fitur-fitur penting yang terpilih melalui GA adalah temperatur maksimum, kecepatan angin maksimum, arah angin maksimum, arah angin terbanyak, lamanya penyinaran matahari dan kecepatan angin rata-rata. Dengan kombinasi metode SVM, SMOTE, GA dan PSO, akurasi klasifikasi data banjir mencapai 82,28%. Namun, penelitian ini juga menghadapi tantangan seperti kontradiksi hasil dengan penelitian lain terkait penggunaan SMOTE dan variasi hasil akibat karakteristik dataset serta metode pembagian data yang berbeda. Hasil penelitian ini dapat digunakan oleh pemerintah daerah dan badan penanggulangan bencana daerah Kota Samarinda untuk memprediksi kejadian banjir dengan lebih akurat, serta memungkinkan tindakan pencegahan yang lebih efektif. Penerapan hasil penelitian ini dapat meningkatkan efektivitas dalam mitigasi bencana banjir Kota Samarinda.
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Pub Date : 2024-07-01DOI: 10.34148/teknika.v13i2.875
Ari Ahmad Dhani, Taghfirul Azhima Yoga Siswa, Wawan Joko Pranoto
Stunting terus menjadi isu kesehatan masyarakat yang kritis di Indonesia, khususnya di Kota Samarinda yang mencatat prevalensi sebesar 25,3% pada tahun 2022, menjadi yang tertinggi kedua di Provinsi Kalimantan Timur. Di tengah prioritas nasional untuk riset 2020-2024, penggunaan data mining untuk klasifikasi stunting memperlihatkan potensi yang signifikan namun tetap menghadapi tantangan dalam menangani data berdimensi tinggi dan ketidakseimbangan kelas. Penelitian ini bertujuan untuk meningkatkan akurasi klasifikasi stunting menggunakan metode Random Forest (RF) yang diintegrasikan dengan seleksi fitur ANOVA dan teknik SMOTE untuk menyeimbangkan kelas. Data yang digunakan dalam penelitian ini bersumber dari Dinas Kesehatan Kota Samarinda, meliputi 26 Puskesmas dengan 21 atribut dan total 150.466 record. Teknik validasi yang dipakai adalah cross-validation k =10. Hasil menunjukkan peningkatan akurasi dari 98,83% menjadi 99,77% naik sebesar 0,94% setelah penerapan seleksi fitur ANOVA. Fitur ZS TB/U, ZS BB/U, dan BB/U diidentifikasi sebagai yang paling berpengaruh. Peningkatan ini menunjukkan efektivitas integrasi metode dalam mengatasi masalah stunting pada dataset yang kompleks dan tidak seimbang, ini diharapkan dapat mendukung kebijakan dan intervensi kesehatan lebih lanjut di kawasan tersebut.
{"title":"Perbaikan Akurasi Random Forest Dengan ANOVA Dan SMOTE Pada Klasifikasi Data Stunting","authors":"Ari Ahmad Dhani, Taghfirul Azhima Yoga Siswa, Wawan Joko Pranoto","doi":"10.34148/teknika.v13i2.875","DOIUrl":"https://doi.org/10.34148/teknika.v13i2.875","url":null,"abstract":"Stunting terus menjadi isu kesehatan masyarakat yang kritis di Indonesia, khususnya di Kota Samarinda yang mencatat prevalensi sebesar 25,3% pada tahun 2022, menjadi yang tertinggi kedua di Provinsi Kalimantan Timur. Di tengah prioritas nasional untuk riset 2020-2024, penggunaan data mining untuk klasifikasi stunting memperlihatkan potensi yang signifikan namun tetap menghadapi tantangan dalam menangani data berdimensi tinggi dan ketidakseimbangan kelas. Penelitian ini bertujuan untuk meningkatkan akurasi klasifikasi stunting menggunakan metode Random Forest (RF) yang diintegrasikan dengan seleksi fitur ANOVA dan teknik SMOTE untuk menyeimbangkan kelas. Data yang digunakan dalam penelitian ini bersumber dari Dinas Kesehatan Kota Samarinda, meliputi 26 Puskesmas dengan 21 atribut dan total 150.466 record. Teknik validasi yang dipakai adalah cross-validation k =10. Hasil menunjukkan peningkatan akurasi dari 98,83% menjadi 99,77% naik sebesar 0,94% setelah penerapan seleksi fitur ANOVA. Fitur ZS TB/U, ZS BB/U, dan BB/U diidentifikasi sebagai yang paling berpengaruh. Peningkatan ini menunjukkan efektivitas integrasi metode dalam mengatasi masalah stunting pada dataset yang kompleks dan tidak seimbang, ini diharapkan dapat mendukung kebijakan dan intervensi kesehatan lebih lanjut di kawasan tersebut.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":"51 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141712309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.34148/teknika.v12i3.693
Muhammad Amfahtori Wijarnoko, Edwin Pramana, Joan Santoso
This research is a systematic literature review of factors that influence repurchase intention. Repurchase intention is important for companies because it will shape customer behavior to become loyal, customers usually tend to have an interest in buying products or services repeatedly so that the company will benefit from products or services that have been sold. The aim of this research is to provide insights into the research trends and issues in the studies of Repurchase Intention. The literature search focused on finding journals published between 2018 and 2023. Only English-language journals with the keyword Repurchase Intention were used in this research. Researchers found 80 journals that matched these keywords but after reading the collected articles thoroughly and removing duplicate and irrelevant articles, the authors produced 50 articles to be used in this research. The findings highlight key drivers for increasing sales: Satisfaction, Trust, Perceived Value, Price, and Word of Mouth. Additionally, 14 moderating factors were identified, with Age being the most prominent in four articles. Korea, India, and Indonesia lead research contributions, each with six articles. Structural Equation Modeling (SEM) is the prevailing measurement method, while other approaches persist. Companies are recommended to prioritize these core factors for consumer engagement. Future research should delve into unexplored moderating factors and alternative measurement methods, enriching our understanding of this vital field.
{"title":"Factors That Influence Repurchase Intention: A Systematic Literature Review","authors":"Muhammad Amfahtori Wijarnoko, Edwin Pramana, Joan Santoso","doi":"10.34148/teknika.v12i3.693","DOIUrl":"https://doi.org/10.34148/teknika.v12i3.693","url":null,"abstract":"This research is a systematic literature review of factors that influence repurchase intention. Repurchase intention is important for companies because it will shape customer behavior to become loyal, customers usually tend to have an interest in buying products or services repeatedly so that the company will benefit from products or services that have been sold. The aim of this research is to provide insights into the research trends and issues in the studies of Repurchase Intention. The literature search focused on finding journals published between 2018 and 2023. Only English-language journals with the keyword Repurchase Intention were used in this research. Researchers found 80 journals that matched these keywords but after reading the collected articles thoroughly and removing duplicate and irrelevant articles, the authors produced 50 articles to be used in this research. The findings highlight key drivers for increasing sales: Satisfaction, Trust, Perceived Value, Price, and Word of Mouth. Additionally, 14 moderating factors were identified, with Age being the most prominent in four articles. Korea, India, and Indonesia lead research contributions, each with six articles. Structural Equation Modeling (SEM) is the prevailing measurement method, while other approaches persist. Companies are recommended to prioritize these core factors for consumer engagement. Future research should delve into unexplored moderating factors and alternative measurement methods, enriching our understanding of this vital field.","PeriodicalId":52620,"journal":{"name":"Teknika","volume":" 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135291435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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