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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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Selection of Candidates for Academic Scholarships Using Analytical Hierarchy Process (Ahp) and Simple Additive Weighting (SAW) Methods at National University Asafalex Asafalex; M Firmansyah; Muhammad Darwis; Iqnal Shalat SW
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (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.v15i1.24780

Abstract

The National University administers several scholarships for new students each year. The problem is, the University does not yet have a standard method for determining beneficiaries. They have difficulty in determining prospective scholarship recipients with the same criteria. In fact, sometimes it only relies on people's instincts, which can be subjective. The University should implement a DSS system to overcome this problem. Therefore, in this study, the AHP method is applied and used to weight the criteria and test the level of consistency so that the criteria are in accordance with the type of scholarship. In addition, the SAW method is also used for determining scholarship recipients according to the quota. The results of this study are the priority weights of the importance of each criterion, namely the average value of report cards (0.35), parents' income (0.23), certificates (0.05), affidavits of not working and receiving scholarships (0.15), year of graduation (0.11) and number of certificates (0.10). The consistency ratio value is 0.03741 indicating the weight is consistent. This study also resulted in the best ranking of candidates for academic scholarships, with a result of 0.93. The average value of the application test results using the TAM method is 80.5%.
Comparison of Support Vector Machines and K-Nearest Neighbor Algorithm Analysis of Spam Comments on Youtube Covid Omicron Sudianto Sudianto; Juan Arton Arton Masheli; Nursatio Nugroho; Rafi Wika Ananda Rumpoko; Zarkasih Akhmad
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.v15i2.24996

Abstract

Every time a new variant of Coronavirus (Covid-19) appears, themedia or news platforms review it to find out whether the new variantis more dangerous or contagious than before. One of the media orplatforms that is fast in presenting news in videos is YouTube.YouTube is a social media that can upload videos, watch videos, andcomment on the video. The comment field on YouTube videos cannotbe separated from spam comments that annoy other users who want tofollow or participate in the comment column. Indication of spamcomments is still done by observing one by one; this is very inefficientand time-consuming. This study aims to create a model that canclassify spam on YouTube comments. The classification method uses the SVM (Support Vector Machines) algorithm and the KNN (K-Nearest Neighbor) algorithm to identify spam comments or not with comment data taken from Omicron's Covid-19 news video on national news channels. The classification results show that the SVM method is superior inaccuracy with the Linear SVC algorithm of 75.12%, SVC of 76.11%, and Nu-SVC of 77.11%. While the KNN algorithm with k=2 is 65.67%, k=4 is 64.51%, k=6 is 62.35%.
Dynamic Approval Matrix Application Design for Technical Department Document Change Request Application Riska Zulfiqoh; Muhamad Bahrul Ulum
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.v15i2.27324

Abstract

This study discusses problems on the website of the NPPS companywhich will also be used by its branch company, namely NPPSLK.While the website currently only supports one company, it isnecessary to develop the website to become multicompany. If thewebsite is made multicompany, then the applications in it areautomatically adjusted. One of the applications on the website is anapplication with systematic approval, namely the Dynamic ApprovalMatrix (DAM). DAM was developed to be able to supportmulticompany, support flow management features, status, andapproval actions for each company. So, a multi-company configuration is carried out on one system, and using the waterfall method with steps. Advance Dynamic ApprovalMatrix (ADAM) was created as multi-enterprise support DAMdevelopment. So, it can be used by multi-company. ADAM is madeusing waterfall method using Odoo with Python, XML, andPostgreSQL. The app contains forms to manage related apps, approvalflow settings, multi-company, status settings, and Call-to-Actionbuttons to facilitate document approval. The ADAM application has been tested on the TDCR application using black box indicator with the conclusion that website results aremore effective and efficient because it can be used by multicompany,and administrators can freely adjust according to company needs.
Interaction Design of ITB Library Application Using User-Centered Design Elisabeth Levana Thedjakusuma; Fetty Fitriyanti Lubis
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.v15i2.27956

Abstract

The Technical Implementation Unit is a part of a university or institute that supports the three pillars of higher education, one of which is the library. Library has a large collection of resources that can be accessed through a library catalog. ITB Library is a mobile application that allows users to search catalogs, but it currently lacks optimal appearance and user experience. The aim of this final project is to improve the ITB Library by implementing a user-centered design approach, which focuses on understanding and addressing user needs. The end goal is to create a high-fidelity prototype that meets the usability goals of effective to use, have good utility, easy to learn, and the user experience goal of being helpful. To evaluate the design, usability testing was conducted on the prototype. Testing was evaluated using several metrics, including task completion rate (100%), System Usability Scale (SUS) (93/100), Single Ease Question (SEQ) (6.7/7), and Intrinsic Motivation Inventory (IMI) (6.7/7 for the value/usefulness subscale) during the third iteration. Based on the results of the testing, the interaction design of the ITB Library meets the usability and user experience goals that were set out to be achieved.
Comparative Analysis of KNN, Naïve Bayes and SVM Algorithms for Movie Genres Classification Based on Synopsis. Nurhayati Buslim; Lee Kyung Oh; Muhammad Hugo Athallah Hardy; Yusuf Wijaya
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.v15i2.29302

Abstract

Text classification is a process of categorizing a text into the correct label. Text classification in natural language processing is a challenging task that requires accuracy to get the correct results, manual text classification tends to be inefficient because it requires a lot of time and also experts. The utilization of machine learning for automatic text classification can be a solution to this problem. KNN, Naive Bayes, and SVM are known as some of the most algorithms to solve classification problems, especially text classification. In this study, we are trying to compare the KNN, Naive Bayes, and SVM algorithms for text classification with the problem of classifying movie genres based on a synopsis using datasets obtained from Kaggle.com and IMDB Dataset. The results of this study indicate that of the 12 experiments, Support Vector Machine (SVM) is the bestperforming algorithm with an accuracy of 90%, 93%, 65%, and 63%. It is hoped that this research can help to determine the best algorithm in the text classification process. 
Hacking as a Cyber Crime, Reviewed from the Perspective of Quran Surah An-Nur Verse 27 Warsino Warsino
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.v15i2.25842

Abstract

Sarcasm is a statement that conveys an opposing viewpoint viapositive or exaggeratedly positive phrases. Due to this intentionalambiguity, sarcasm identification has become one of the importantfactors in sentiment analysis that make many researchers in naturallanguage processing intensively study sarcasm detection. Thisresearch is using multiple channels embedding the attentionbidirectional long-short memory (MCEA-BLSTM) model thatexplored sarcasm detection in news headlines and has differentapproach from previous research-developed models that lexical,semantic, and pragmatic properties. This research found that multiplechannels embedding attention mechanism improve the performance ofBLSTM, making it superior to other models. The proposed methodachieves 96.64% accuracy with an f-measure of 97%
Selection of Home Wifi Internet: Machine Learning Implementation With Decision Tree C4.5 Algorithm Method Dewi Khairani; Muhammad Ammaridho Romdhan Siregar; Siti Ummi Masruroh; Miftakhul Nuuril Azizah
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.v15i2.27741

Abstract

The multiple bandwidths that internet service providers offer make it difficult for people to choose, especially for regular people unfamiliar with the internet; therefore, most people choose because the price is reasonable. Numerous users also lament the difficulty and slow internet usage. The issue is then concentrated on internet service providers, who are thought to be poor at offering services. The quantity of bandwidth consumed, which does not correspond to the user’s needs, is one factor contributing to slow internet. As a result, the appropriate bandwidth must be chosen based on the requirements of each user. Compared to other algorithms, the C4.5 decision tree method can deliver the best and correct decision, according to the current literature. As a result, this project will develop a web application based on the C4.5 decision tree algorithm that can assist in determining bandwidth and internet following community needs. Using this C4.5 Decision Tree, decisions are based on patterns identified in previously collected data. Predictions about various forms of internet use in the neighborhood may subsequently be produced from these patterns. Based on the calculation, the accuracy obtained is 0.54, or a percentage of 54%. The black box testing indicated that the bandwidth determination application was functioning correctly
Action Recommendation Model Development for Hydromon Application Using Deep Neural Network (DNN) Method Meida Cahyo Untoro; Eko Dwi Nugroho; Mugi Praseptiawan; Aidil Afriansyah; Muhammad Nadhif Athalla
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.v15i2.26762

Abstract

Controlling hydroponic plants, which is currently being carried outmanually, can be said to be less effective because it still involves thehard work of farmers to continuously monitor the condition of thehydroponic plants. Therefore, the general objective of this research isto develop a model that can be used as a recommendation system foractions that farmers need to take based on hydroponic crop conditions.The model formed with this machine learning method will then beused in the Hydromon application which allows farmers to manageand monitor the condition of hydroponic plants and take action basedon the recommendations given. This model was developed using adeep neural network algorithm consisting of five layers with the helpof the TensorFlow framework. The results show that the model isaccurate with an accuracy value of 96.47% on the test data to classifyplant conditions so that it can be used in the Hydromon application.
Sarcasm Recognition on News Headlines Using Multiple Channel Embedding Attention BLSTM Azika Syahputra Azwar; Suharjito Suharjito
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.v15i2.28417

Abstract

Sarcasm is a statement that conveys an opposing viewpoint via positive or exaggeratedly positive phrases. Due to this intentional ambiguity, sarcasm identification has become one of the important factors in sentiment analysis that make many researchers in natural language processing intensively study sarcasm detection. This research is using multiple channels embedding the attention bidirectional long-short memory (MCEA-BLSTM) model that explored sarcasm detection in news headlines and has different approach from previous research-developed models that lexical, semantic, and pragmatic properties. This research found that multiple channels embedding attention mechanism improve the performance of BLSTM, making it superior to other models. The proposed method achieves 96.64% accuracy with an f-measure of 97%
The Development of Interactive Games for Covid-19 Prevention Using Indonesian Health Protocols Arrahman Kaffi; Maulana Rizqi; Gerardo AK Laksono; Alvin Julian; Agustinus Bimo Gumelar
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.v15i2.25649

Abstract

COVID-19 has become a virus spreading quickly across the world.The government of Indonesia also immediately adjusted theconditions to minimize the spread of the COVID-19 virus byimplementing the health protocols 5M namely, wearing a mask,washing hands, keeping distance, avoiding crowds, and reducingmobility. With the advancement of technology, games can be used aseducational media to support users learning processes and increasetheir knowledge. Therefore, we conducted a study using the learningsupport media, namely interactive games based on a personalcomputer platform with the Windows operating system to help theusers understand the prevention of the COVID-19 virus byimplementing health protocols. This study proposes using a structurefor the iterative cycle process called the ADDIE model framework andusing the Unity game engine for its game development tools. Tomeasure the feasibility of interactive games as educational media, weuse the System Usability Scale method. Based on the applicationtesting of 50 respondents, interactive games get a score of 90 on a scalethat is acceptable. The results also indicate that interactive games aseducational media will improve the users learning process andmotivation about implementing the health protocols.

Page 15 of 27 | Total Record : 262

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