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GOOGLE MAPS AND MAPBOX API PERFORMANCE ANALYSIS ON ANDROID-BASED LECTURE ATTENDANCE APPLICATION Kurnia Saputra; Muhammad Furqan; Taufik Fuadi Abidin; Dalila Husna Yunadi
Jurnal Natural Volume 19 Number 3, October 2019
Publisher : Universitas Syiah Kuala

Attendance is an inseparable component from lectures. The current manual attendance process still has its weaknesses, such as the loss or broken attendance sheets, the easiness to conduct fraud on the attendance sheets, and other cases. The attendance system using fingerprint devices are also not available in other locations yet, such as lectures that are done on the field or outdoor, where fingerprint devices are not available. Because of that, an online lecture attendance system that makes use of Android-based smartphones is developed in order to tackle the problem. This online lecture attendance system has the main feature of recording students’ attendances in a radius of 300 metres from the lecturer. This application is named Lecture Attendance System is developed using Rapid Application Development (RAD) model, because it is an effective method to minimise errors in the application. There are two testing performed to the application. The first testing was functional testing of the application. This testing was carried out in order to make sure that all functionalities and features are performing well. The second testing carried out is the distance accuracy testing, to compare between the Google Maps and MapBox API distances. From this testing, it was found that the error percentage using Google Maps is 9.250% and 12.128% for MapBox. From these results, they show that in calculating the distance, using Google Maps API has higher accuracy compared to the MapBox API.

Pembaruan Aplikasi Paperless Office Universitas Syiah Kuala Taufik Fuadi Abidin; Fitra Riyanda; Rahmad Dawood
Jurnal Rekayasa Elektrika Vol 12, No 1 (2016)
Publisher : Universitas Syiah Kuala

Paperless Office (PLO) is a web-based application that was created to facilitate digital office communication such as sending memos, letters, and posting news. It was initially created by Bambang Prastowo from Universitas Gajah Mada. The goals of using PLO are to reduce paper usage, speed up internal communication, and to simplify the management of correspondence in digital form. Syiah Kuala University (Unsyiah) has implemented PLO since early 2013. This paper aims to analyze the level of activity and users satisfaction of the renew PLO. The renew is done by making the web application more responsive and adding new features that do not exist in the earlier version. The results show that users satisfaction level increases, observed from system quality, information, and services. Variables that affect the level of activity, based on Pearson and Spearman correlations, are X1, X13,X20,X33, X36,X38, andX43, while the variables that affect the level of users satisfaction are X42 and X44.

Pengenalan Karakter Plat Nomor Kendaraan Bermotor Menggunakan Zoning dan Fitur Freeman Chain Code Taufik Fuadi Abidin; Abbas Adam AzZuhri; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 14, No 1 (2018)
Publisher : Universitas Syiah Kuala

A license plate is one of the vehicle identities. It consists of alphabetic characters and numbers and represents provincial and area code where the vehicle is registered. This article discusses the character recognition of plate number using zoning and Freeman Chain Code (FCC). Zoning divides character image into several zones i.e. 4, 6, and 8, and then, the pattern of each character in the zone is extracted using FCC as the numerical features. The character is then classified using Support Vector Machines (SVM). It is a multi-class classification problem with 36 categories. The results show that FCC features with 8 zones give the best accuracy (87%) when compared to the other two zones.

Pengenalan Karakter Plat Nomor Kendaraan Bermotor Menggunakan Zoning dan Fitur Freeman Chain Code Taufik Fuadi Abidin; Abbas Adam AzZuhri; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 14, No 1 (2018)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v14i1.8932

A license plate is one of the vehicle identities. It consists of alphabetic characters and numbers and represents provincial and area code where the vehicle is registered. This article discusses the character recognition of plate number using zoning and Freeman Chain Code (FCC). Zoning divides character image into several zones i.e. 4, 6, and 8, and then, the pattern of each character in the zone is extracted using FCC as the numerical features. The character is then classified using Support Vector Machines (SVM). It is a multi-class classification problem with 36 categories. The results show that FCC features with 8 zones give the best accuracy (87%) when compared to the other two zones.

Pembaruan Aplikasi Paperless Office Universitas Syiah Kuala Taufik Fuadi Abidin; Fitra Riyanda; Rahmad Dawood
Jurnal Rekayasa Elektrika Vol 12, No 1 (2016)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v12i1.3246

Paperless Office (PLO) is a web-based application that was created to facilitate digital office communication such as sending memos, letters, and posting news. It was initially created by Bambang Prastowo from Universitas Gajah Mada. The goals of using PLO are to reduce paper usage, speed up internal communication, and to simplify the management of correspondence in digital form. Syiah Kuala University (Unsyiah) has implemented PLO since early 2013. This paper aims to analyze the level of activity and users satisfaction of the renew PLO. The renew is done by making the web application more responsive and adding new features that do not exist in the earlier version. The results show that users satisfaction level increases, observed from system quality, information, and services. Variables that affect the level of activity, based on Pearson and Spearman correlations, are X1, X13,X20,X33, X36,X38, andX43, while the variables that affect the level of users satisfaction are X42 and X44.

GOOGLE MAPS AND MAPBOX API PERFORMANCE ANALYSIS ON ANDROID-BASED LECTURE ATTENDANCE APPLICATION Kurnia Saputra; Muhammad Furqan; Taufik Fuadi Abidin; Dalila Husna Yunadi
Jurnal Natural Volume 19 Number 3, October 2019
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v19i3.14459

Attendance is an inseparable component from lectures. The current manual attendance process still has its weaknesses, such as the loss or broken attendance sheets, the easiness to conduct fraud on the attendance sheets, and other cases. The attendance system using fingerprint devices are also not available in other locations yet, such as lectures that are done on the field or outdoor, where fingerprint devices are not available. Because of that, an online lecture attendance system that makes use of Android-based smartphones is developed in order to tackle the problem. This online lecture attendance system has the main feature of recording students’ attendances in a radius of 300 metres from the lecturer. This application is named Lecture Attendance System is developed using Rapid Application Development (RAD) model, because it is an effective method to minimise errors in the application. There are two testing performed to the application. The first testing was functional testing of the application. This testing was carried out in order to make sure that all functionalities and features are performing well. The second testing carried out is the distance accuracy testing, to compare between the Google Maps and MapBox API distances. From this testing, it was found that the error percentage using Google Maps is 9.250% and 12.128% for MapBox. From these results, they show that in calculating the distance, using Google Maps API has higher accuracy compared to the MapBox API.

Kemampuan Komunikasi Matematis dan Metakognitif Siswa SMP Pada Materi Lingkaran Berdasarkan Gender Diandita, Elly Rizki; Johar, Rahmah; Abidin, Taufik Fuadi
Mathematics Education Journal Vol. 11 No. 2 (2017): Jurnal Pendidikan Matematika
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

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

The purpose of this research is to find the mathematical and metacognitive communication skills of junior high school students by gender. This research is a quantitative research. The population of this research is all students of class VIII SMP Negeri 1 Banda Aceh, SMP Negeri 9 Banda Aceh, and SMP Negeri 13 Banda Aceh with sample each 1 (one) class from each school. The data collection used is the test of mathematical communication ability and metacognitive questionnaire as well as interview from metacognitive question result. To find the difference of mathematical and metacognitive ability of students used T-test. The results of this study indicate that 1) there is no difference in mathematical communication ability of junior high students on gender-based material circle in the research sample; 2) there is no difference in mathematical communication ability of junior secondary students in gender-based circle material in each school being the research sample; 3) there was no difference in metacognitive ability of junior high school students in gender-based material circles in the study sample; 4) there is no difference in metacognitive ability of junior high school students in gender-based material circles in each school to be a research sample; 5) there is a strong relationship between mathematical communication ability with student’s metacognitive ability.

Incorporation of IndoBERT and Machine Learning Features to Improve the Performance of Indonesian Textual Entailment Recognition Tandi, Teuku Yusransyah; Abidin, Taufik Fuadi; Riza, Hammam
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.173-186

Background: Recognizing Textual Entailment (RTE) is a task in Natural Language Processing (NLP), used for question-answering, information retrieval, and fact-checking. The problem faced by Indonesian NLP is based on how to build an effective and computationally efficient RTE model. In line with the discussion, deep learning models such as IndoBERT-large-p1 can obtain high F1-score values but require large GPU memory and very long training times, making it difficult to apply in environments with limited computing resources. On the other hand, machine learning method requires less computing power and provide lower performance. The lack of good datasets in Indonesian is also a problem in RTE study. Objective: This study aimed to develop Indonesian RTE model called Hybrid-IndoBERT-RTE, which can improve the F1-Score while significantly increasing computational efficiency. Methods: This study used the Wiki Revisions Edits Textual Entailment (WRETE) dataset consisting of 450 data, 300 for training, 50 for validation, and 100 for testing, respectively. During the process, the output vector generated by IndoBERT-large-p1 was combined with feature-rich classifier that allowed the model to capture more important features to enrich the information obtained. The classification head consisted of 1 input, 3 hidden, and 1 output layer. Results: Hybrid-IndoBERT-RTE had an F1-score of 85% and consumed 4.2 times less GPU VRAM. Its training time was up to 44.44 times more efficient than IndoBERT-large-p1, showing an increase in efficiency. Conclusion: Hybrid-IndoBERT-RTE improved the F1-score and computational efficiency for Indonesian RTE task. These results showed that the proposed model had achieved the aims of the study. Future studies would be expected to focus on adding and increasing the variety of datasets. Keywords: Textual Entailment, IndoBERT-large-p1, Feature-rich classifiers, Hybrid-IndoBERT-RTE, Deep learning, Model efficiency

Integration of machine learning and climate data for enhanced dengue hemorrhagic fever (DHF) prediction: A case study in Banda Aceh Puspitasari, Rizka; Gan, Connie Cai Ru; Yani, Muhammad; Zahrina, Zahrina; Abidin, Taufik Fuadi
International Journal of Disaster Management Vol 8, No 2 (2025)
Publisher : TDMRC, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/ijdm.v8i2.47069

The increasing impact of climate change, including rising average temperatures and altered precipitation patterns, has led to changes in the prevalence and distribution of climate-sensitive diseases (CSDs), such as Dengue Hemorrhagic Fever (DHF). DHF remains a significant public health concern in Indonesia, particularly in Banda Aceh, due to its high incidence. The burden on healthcare systems is substantial, contributing to increased morbidity and mortality, especially among vulnerable populations. This study aimed to integrate climate data with machine learning methods to develop predictive models for DHF incidence. Data from 2010 to 2023 included DHF case counts and monthly climate variables such as humidity, rainfall, temperature, and wind speed. The predictive models employed Gradient Boosting, Support Vector Regression (SVR), Random Forest, and Linear Regression algorithms. Model performance was evaluated by comparing prediction accuracy using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) metrics. The results demonstrated that the Linear Regression model predicted monthly DHF incidence with greater accuracy than the other models, as indicated by lower MAE and RMSE values. These findings suggest that integrating climate data with machine learning provides an effective tool for early warning systems for DHF, supporting public health planning and interventions in Banda Aceh City, particularly in anticipation of an increase in DHF cases.

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