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INDONESIA
TEKNIK INFORMATIKA
Published by Universitas Islam Negeri Syarif Hidayatullah Jakarta
ISSN : 19799160     EISSN : 25497901     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Teknik Informatika merupakan wadah bagi insan peneliti, dosen, praktisi, mahasiswa dan masyarakat ilmiah lainnya untuk mempublikasikan artikel hasil penelitian, rekayasa dan kajian di bidang Teknologi Informasi. Jurnal Teknik Informatika diterbitkan 2 (dua) kali dalam setahun.
Arjuna Subject : -
Articles 262 Documents
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Implementation of IoT Technology on MySmartTrash Waste Bank Application Viva Arifin; Siti Ummi Masruroh; Rizka Amalia Putri; Fitri Mintarsih; Nenny Anggraini; Nurhayati; Dewi Khairani
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.46673

Abstract

The effectiveness of Waste Bank in addressing national waste management challenges is limited by inherent shortcomings. Conventional processes, which heavily rely on manual labor and record-keeping, often face logistical challenges and inefficiencies that limit the effectiveness of waste banks. This paper presents the MySmartTrash application, a solution that integrates IoT technology to enhance waste management practices through a smart waste bank system. By utilizing IoT-enabled sensors, the application allows users to monitor waste levels in real time, thereby optimizing waste collection processes and promoting effective waste segregation. This study employed IoT Design Methodology and Prototyping. Through a SWOT analysis of existing waste management applications, the research identifies strengths and opportunities for enhancing waste management systems. Usability testing also highlighted the significance of various features. This study offers insights for future research into IoT applications in environmental sustainability and waste management systems.
ANALISIS QUALITY OF SERVICE JARINGAN WIRELESS SUKANET WiFi DI FAKULTAS SAINS DAN TEKNOLOGI UIN SUNAN KALIJAGA Sugiantoro, Bambang; Mahardhika, Yuha Bani
JURNAL TEKNIK INFORMATIKA Vol. 10 No. 2 (2017): Jurnal Teknik Informatika
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v10i2.7027

Abstract

ABSTRAK Performa layanan jaringan Internet pada UIN Sunan Kalijaga Fakultas Sains dan Teknologi masih belum maksimal, yaitu memiliki tingkat kualitas delay sebesar 159 milidetik menurut TIPHON Bagus. Besar Throughput sebesar 9.0 MBps dan presentase Throughput sebesar 50 % dikategorikan menurut standarisasi TIPHON sedang. Dan memiliki nilai packet loss ratio sebesar 36 % dikategorikan menurut standarisasi TIPHON adalah jelek. ABSTRACT Internet service network performance in Islamic State University of Sunan Kalijaga environment in the faculty of science and technology area is still not maximal. It has a delay quality level of 159 milliseconds according to good TIPHON. Large throughput of 9.0 Mbps and throughput percentage of 50% are categorized according to standardized of normal TIPHON and it has a value of packet loss ratio of 36% categorized according to TIPHON standardization is bad.How to Cite : Sugiantoro, B. Mahardhika, Y.B . (2017). ANALISIS QUALITY OF SERVICE JARINGAN WIRELESS SUKANET WiFi DI FAKULTAS SAINS DAN TEKNOLOGI UIN SUNAN KALIJAGA. Jurnal Teknik Informatika, 10(2), 191-201. doi:10.15408/jti.v10i2.7027Permalink/DOI: http://dx.doi.org/10.15408/jti.v10i2.7027
Attendance Recognation by Using Smart Meter Based On IoT Study Case : FST UIN Jakarta Fahrianto, Feri; Suseno, Hendra Bayu; Reza, Alfatta
JURNAL TEKNIK INFORMATIKA Vol. 12 No. 1 (2019): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v12i1.11043

Abstract

State Islamic University Syarif Hidayatullah Jakarta as rapidly growing university toward world-class research university placed in the edge of Jakarta has academic information centre running by Pustipanda (The Center of Information Technology and Database). The acadmic information system (AIS) has been used for recording an academic activity in university for almost a decade, this information system has a functionality for detecting the lecturer attandancity, but the attendance system needs to be input by admin. In this research, the system to detect attendancity from lecturer is build and synchronize to universisty academic information system.  Internet of Things, based on ITU-T 2015, some objects are able to transmit data among object by using Internet connection. It means by this technology the Internet used has been widely changed, from human to machine communication now also become machine-to-machine communications. By using this technology a small object or device is able to implement into electrical system to detect an activity occured in the room. Things implemented in the room are able to monitor which electronic device is active and motion of moving objects, also the position of objects. The communication connection between smart phones and acces point in the class room is also monitored in order to identify the lecturer identity.
A Backpropagation Artificial Neural Network Approach for Loan Status Prediction Nugraha, Edwin Setiawan; Sitepu, Gabrielle Jovanie
JURNAL TEKNIK INFORMATIKA Vol. 15 No. 2 (2022): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v15i2.27006

Abstract

Providing credit has become a main source of profit for financial and non-financial institutions. However, this transaction might lead into credit risk. This risk occurred if debtors unable to complete their obligations that will led loss for creditors.  It is necessity for company to create assessment in distinguishing eligible or non-eligible prospective customer. Artificial Neural Network (ANN) is introduced in solving this typical classification case. Furthermore, one of learning algorithm in ANN namely Backpropagation is able to minimizing error of output in order to receive accurate result. This research aims to form models that capable in classifying the loan status of applicants by utilizing historical data. The method developed in this research is Backpropagation with activation function is a sigmoid function. In addition, this research formed two data model for analyzed; with first data model is every variable given in dataset and for the second data model is the variables that influenced the loan acceptance. Backpropagation shows high performance with more or less data variables. The results of this research show that the both data model has highest accuracy of prediction is 94.37% while the lowest accuracy prediction is 80.28%.
Implementation of Design Thinking Method in UI/UX Redesign of Public Complaint Application (Case Study: Go Siaga App) Pangestu, Rafi Kurnia; Ulum, Muhamad Bahrul
JURNAL TEKNIK INFORMATIKA Vol. 16 No. 2 (2023): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v16i2.27416

Abstract

Go Siaga App is a mobile-based application by Tangerang Sub-district Police Office that provides special community services for the Tangerang sub-district community which provides features in the form of reports of disturbances in public security and reports of loss or damage. Since it is a new application released in March 2021 on Google Playstore, there are several things that need to be considered to maintain the usability of the application. This research aims to redesign the user interface and user experience (UI/UX) of the Go Siaga application using Design Thinking Method in the design process. Some of the supporting aspects for testing the user satisfaction such as effectiveness, efficiency, usefulness, satisfaction, and learnability are met in the usability testing. The results showed that the percentage of all the aspects in usability from the redesigned version were all higher than the current one with 80% of effectiveness, 80% of efficiency, 80% of usefulness, 86.67% of satisfaction, and 73.33% of learnability. Therefore, based on the research results, the redesign of Go Siaga is more effective, more efficient, more useful, more satisfying, and also easy to learn.
Machine Learning for the Model Prediction of Final Semester Assessment (FSA) using the Multiple Linear Regression Method Rachmawati, Fitria; Jaenudin, Jejen; Ginting, Novita Br; Laksono, Panji
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.28652

Abstract

Corona virus (COVID-19) is the reason behind the collapse of the National Assembly. The first is the Final Semester Assessment (FSA) , which is a component of the student's graduation. The aforementioned evaluation process is a crucial consideration for the teacher since it uses several intricate surveys and mark components. A prediction model is employed to assist teachers in providing suitable results for student learning. The method that is used is called the multiple linear regression. This multiple linear regression algorithm yields an accuracy level of approximately 92%. The analysis results using the method are used as a guide to understanding student’s index. This index is a rating that appears based on the Minimum Credit Count (MCC). Therefore, the goal of this study is to determine students' understanding of the FSA prediction value, which will be taken into consideration through the results of the MCC weights in the form of a range in the form of "Grade." Additionally, the research aims to determine the accuracy of the results from the model obtained using multiple linear regression algorithms in predicting students' FSA.
A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University Wicaksono, Damar; Nisworo, Sapto; Nata, Imam Adi
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.32132

Abstract

This research aimed to classify achievement factors for electrical engineering students at Tidar University using K-Means and Agglomerative Clustering classification algorithms. The goal was to understand if any parameters influence high-achieving student performance. The Indonesian government and private sector for university students provide significant education funds. Student scholarships are awarded based primarily on GPA and entry path, overburdening staff and causing confusion during distribution to eligible recipients. A system was needed to accommodate additional eligible criteria. The researcher selected factors to identify engineering student performance, including school origin, entry path, tuition fees, and GPA. These inputs could determine graduation status. The results compared calculation methods based on collected data accuracy, processing times, and characterizing clustered data to determine the best classification method. Agglomerative Hierarchical Clustering performed better. Accuracy testing on 600 training data points yielded 73.94% for improved K-means and 90.42% for AHC. The Average processing time was 674.92 seconds for improved K-means and 554.35 seconds for AHC. Silhouette testing also characterized calculation methods, with improved K-means scoring best at 0.654 and AHC at 0.787 using two clusters.
Use of Ticketing System in Freelancing Platform to Maintaining Client Trust in Product Development Process Sitanggang, Andri Sahata; Hasti, Novrini; Syafariani, R Fenny; Melian, Lusi; Santoso, Bondan Rachmat; Shidiq, Muhammad Daffa
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.32228

Abstract

Micro, small, and medium enterprises (MSMEs) are considered to be one of the important components in the economic development of a country, especially Indonesia. However, it has been found that MSMEs are lagging in digitalization, the adoption of information technology, and digital marketing. An information system where MSMEs can have easy access to IT and digital marketing professionals can be a solution to boost and encourage digitalization among local MSMEs. Developing such an information system requires the project to be able to quickly adapt and change based on the user’s needs and current trends. This study proposes an incremental solution to building an accessible information system catered for MSMEs by incorporating the ADDIE model into the development cycle. To understand the feasibility of the system, several group meetings are arranged to demonstrate and try out the system’s capability to the target users. The results indicate that the system is generally able to fit the needs of MSMEs and is quite effective at connecting the MSESs to IT and Digital marketing resources and experts.
Analyzing User Satisfaction of a Study Abroad Guidance Company Website Using the Customer Satisfaction Index (CSI) Method Nispi, Fajrian; Kurniawati, Ana; Wulandari, Lily
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.34612

Abstract

XYZ is an education technology company dedicated to assisting Indonesian students in gaining acceptance to universities worldwide through full scholarship, partial, or self-funding. Until 2024, XYZ has a thousand alumni accepted in 46 countries and many universities worldwide. One of the marketing trackers that XYZ has is the website. With this website, the company will deliver the service to customers and receive user feedback to run and improve their services. The measurement of user satisfaction level can be used to improve the quality of service in digital media. The method used in this study to measure user satisfaction level is the Customer Satisfaction Index (CSI), which evaluates satisfaction across five (5) dimensions: usability, information quality, assurance, reliability, and data accessibility. This method's result shows a value of 83.64%, which means the XYZ website performance is in the "Very Satisfied" category. These findings suggest that XYZ Company's website is highly effective and has a "Very Satisfied" result category in meeting user needs, paving the way for continued success in their mission to assist Indonesian students in pursuing global education opportunities
Ensemble Learning Development Based on Transfer Learning for Indonesian Traditional Food Detection Nurhayati, Nurhayati; Zulfiandri, Zulfiandri; Nurjannah, Wilda; Muntasha, Irlan
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i2.35034

Abstract

Development of traditional food competes with other traditional foods now. They must compete with fast food and food from abroad. In 2013, the food and beverage sector were the second highest contributor to tourist expenditure after accommodation. This shows its very important role in the economy. That caused, we need a model that can predict traditional Indonesian foods and snacks.  We used ensemble learning. It had 2 transfer learning methods, namely VGG-19 and Xception. They will be combined to improve the performance of the existing model. The research result shown output. It has found that the ensemble learning model achieved accuracy of up to 97% on training data and 91% on testing data. It is hoped that this prediction model can help people recognize typical Indonesian food and increase interest in and preserve the food around them.

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