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Journal of Information Technology and its Utilization
Published by Sekolah Tinggi Multi Media Yogyakarta
ISSN : 29854067     EISSN : 2654802X     DOI : https://doi.org/10.56873/jitu
Core Subject : Science, Engineering,
Computer Science & IT Engineering
To explore scientific developments in the field of information technology and its utilization, including data mining, IoT, Artificial Intelligence, Digital Processing, and Information Systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 78 Documents
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ALGORITHM C4.5 IN CLASSIFYING HEALTH OF CAT NURLINDASARI TAMSIR
Journal of Information Technology and Its Utilization Vol 4 No 2 (2021)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.4.2.4410

Abstract

One of the activities in the TIU (Technical Implementing Unit) of Office of Animal Husbandry and Animal Health is to carry out the examination of pet health, record and issue an Animal Health Certificate (AHC). The object in this research was cat, where the examination was still performed by laboratory test, using paper as a form of diagnosis carried out by a vet and not using the technology. Therefore, an application to provide decision in determining healthy cat that also implements the algorithm C4.5 based on android system was designed. This system was able to perform diagnosis of cat diseases quickly based on previous medical record, with a training history (training data) as many as 44 cases. Then the classification process would strengthen the results of cat disease diagnosis such as how to deal with disease that had similar symptoms so as to facilitate the Office of Animal Husbandry and Animal Health, as a comparison to issue an Animal Health Certificate. Based on the Black Box testing, the functionality of the module was in accordance with the needs of the system, while the accuracy testing generated the percentage value of 93.18%. This shows that the algorithm C4.5 has a good accuracy to determine healthy cat.
COMBINING SUPERVISED AND UNSUPERVISED METHODS IN TOURISM VISITOR DATA Weksi Budiaji; Vebriana Vebriana; Juwarin Pancawati
Journal of Information Technology and Its Utilization Vol 5 No 1 (2022)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.1.4659

Abstract

Combining supervised and unsupervised method can assist in the data analysis process. This research aims to apply a supervised method, i.e. Poisson regression, that is followed by an unsupervised method, namely cluster analysis of the visitors in a tourism dataset. The samples were taken 80 persons purposively from the visitors of the Flower Garden X in Serang Regency, Banten Province. The dataset consists of the number of visits, travel cost, income/ stipend per month, gender, age, distance from the place of origin, and perception, which is formed by 11 questions of facilities and services. The Poisson regression was applied in the 30, 40, and 50 bootstrap samples resulted in the perception as the significant features. Then, medoid-based cluster analysis, i.e. pam and simple k-medoids, in the perception dataset was applied. They compared simple matching and cooccurrence distances and were validated via medoid-based shadow value. It grouped the visitors into five clusters as the most suitable number of clusters. The combined methods of supervised and unsupervised provided the cleanliness as the important indicator. The improvement of the tourism object had to be focus on the cleanliness aspect.
NAIVE BAYES ALGORITHM IN HS CODE CLASSIFICATION FOR OPTIMIZING CUSTOMS REVENUE AND MITIGATION OF POTENTIAL RESTITUTION Hafizh Adam Muslim
Journal of Information Technology and Its Utilization Vol 5 No 1 (2022)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.1.4740

Abstract

The Directorate General of Customs and Excise, as a government revenue collector, must maximise import duty receipts each year. One common issue is the return of unpaid import duty and/or administrative punishments in the form of fines based on the objection judgement document. The Tax Court could help you minimise your gross receipts at the Customs Office. Data mining techniques are intended to provide valuable information regarding the HS Code classification technique, which can assist customs agents in determining duties and/or customs values. This study makes use of data from the Notification of Import of Goods at Customs Regional Office XYZ from 2018 to 2020. The Cross-industry Standard Process for Data Mining (CRISP-DM) model is used in this study, and the Naive Bayes Algorithm in Rapidminer 9.10 is used for data classification. According to the model, the calculation accuracy is 99.97 percent, the classification error value is 0.03 percent, and the Kappa coefficient is 0.999..
NEXT WORD PREDICTION USING LSTM Afika Rianti; Suprih Widodo; Atikah Dhani Ayuningtyas; Fadlan Bima Hermawan
Journal of Information Technology and Its Utilization Vol 5 No 1 (2022)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.1.4748

Abstract

Next word prediction which is also called as language modelling is one field of natural language processing that can help to predict the next word. It’s one of the uses of machine learning. Some researchers before had discussed it using different models such as Recurrent Neural Networks and Federated Text Models. Each researcher used their own models to make the prediction and so the researcher here. Researchers here chose to make the model using  Long Short Term Memory (LSTM) model with 200 epoch for the training. For the dataset, the researcher used web scraping. The dataset contains 180 Indonesian destinations from nine provinces. For the libraries, researchers used  tensorflow, keras, numpy, and matplotlib. To download the model in json format, the researcher used tensorflowjs. Then for the tool to code, the researcher used Google Colab. The last result is 8ms/step, loss: 55%, and accuracy: 75% which means it’s good enough and can be used to predict next words.
WEBSITE PHISING DETECTION APPLICATION USING SUPPORT VECTOR MACHINE (SVM) Diki Wahyudi; Muhammad Niswar; A. Ais Prayogi Alimuddin
Journal of Information Technology and Its Utilization Vol 5 No 1 (2022)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.1.4836

Abstract

Phishing is an act to get someone's important information in the form of usernames, passwords, and other sensitive information by providing fake websites that are similar to the original. Phishing (fishing for important information) is a form of criminal act that intends to obtain confidential information from someone, such as usernames, passwords and credit cards, by impersonating a trusted person or business in an official electronic communication, such as electronic mail or instant messages. Along with the development of the use of electronic media, which is followed by the increase in cyber crime, such as this phishing attack. Therefore, to minimize phishing attacks, a system is needed that can detect these attacks. Machine Learning is one method that can be used to create a system that can detect phishing. The data used in this research is 11055 website data, which is divided into two classes, namely "legitimate" and "phishing". This data is then divided using 10-fold cross validation. While the algorithm used is the Support Vector Machine (SVM) algorithm which is compared with the decision tree and k-nearest neighbor algorithms by optimizing the parameters for each algorithm. From the test results in this study, the best system accuracy was 85.71% using SVM kernel polynomial with values of degree 9 and C 2.5.
Analisa Performansi Jaringan 5G pada Kondisi Line-of-Sight Menggunakan Frekuensi 3.3 GHz di Sawahan, Surabaya Solichah Larasati Larasati; Khoirun Ni'amah; Zein Hanni Pradana
Journal of Information Technology and Its Utilization Vol 5 No 2 (2022): December 2022
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.2.4892

Abstract

This research is expected to be the beginning of the initial design for the implementation of 5G technology in Indonesia especially in Area Sawahan, Surabaya based on the coverage area with the frequency of 3.3 GHz. Performance analysis with line-of-sight (LOS) conditions using propagation model urban macro (uMa) according to the recommendation of 3GPP (3rd Generation Partnership Project) TR 38.901. This research based on four scenarios, outdoor-to-outdoor (O2O) for downlink and uplink, and outdoor-to-indoor (O2I) scenario for uplink and downlink. Performance of 5G network simulated using Atoll 3.4 and shown the pathloss values ​​of 105.405 dB for uplink and 101.405 dB for downlink. The performance results in the O2O scenario for the uplink direction require 5 gNodeB and 8 gNodeB in the downlink direction. In the O2I scenario, the uplink direction requires as many as 6 gNodeB and the downlink direction as much as 9 gNodeB. The simulation parameters analyzed in this research are based on the signal strength received by the user (SS-RSRP) and signal quality (SS-SINR). The best result of SS-RSRP in the O2I uplink scenario is -89 dBm and the SS-SINR parameter in the O2O scenario is 0.93 dBm. These results show that in the city of Sawahan a 5G system can be applied.
Bahasa Inggris Heti Mulyani; Ricak Agus Setiawan; Musawarman; Annisa Romadloni
Journal of Information Technology and Its Utilization Vol 5 No 2 (2022): December 2022
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.2.4894

Abstract

The spread of the coronavirus in Indonesia is quite fast. The spread of Covid 19 is almost evenly distributed in all provinces in Indonesia. Some areas even have a fairly high mortality rate. Therefore, it is necessary to group regions to find out which areas have the highest to lowest Covid cases so that the appropriate response process can be carried out. In addition, data visualization is also needed that provides information on COVID-19 data for each province. In this study, the data were grouped using the K-Means Clustering method. The dataset used is the Indonesian Covid-19 dataset from Kaggle. The criteria for each province's covid cluster are the number of cases and deaths. The Clustering process uses the Python programming language. From the results of this study, it can be seen that there are 3 groups of covid. The first group consists of 30 provinces with several cases below 200,000 and a number of deaths below 6000. The second group contains two provinces that have the highest number of cases, namely above 600,000, but the number of deaths is less than group 3, which is 15000. In group 3 there are 2 provinces where the number of cases is below 500,000 but the death rate is above 30,000.
Implementation of Dashboard Power Bi for Data Visualization of Graduates During Covid-19 Pandemic in The Faculty of Tarbiyah and Teaching Sciences IAIN Palopo Mifta Zulfahmi Muassar
Journal of Information Technology and Its Utilization Vol 5 No 2 (2022): December 2022
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.2.4898

Abstract

  This study presents information regarding the distribution of graduates and the number of students who graduated during the pandemic of Covid-19 at the Faculty of Tarbiyah and Teaching Sciences IAIN Palopo through visualization of data depicted during the Covid19 pandemic, namely in a vulnerable time in 2020 to early 2022. This visualization is done by distributing graduate data into the Microsoft Power BI application and depicted in the form of a diagram, after that the data is visualized in the form of diagrams and numbers based on the categories that have been collected in the form of an Excel file which is then saved in a CSV file type so that the files obtained lighter than before so that the distribution of data in the form of information for graduates of the Faculty of Tarbiyah and Teaching Sciences at IAIN Palopo can be easily observed by policymakers in making decisions.
Time Series Analysis for Customs Revenue Prediction using Arima Model in Python Hafizh Adam Muslim
Journal of Information Technology and Its Utilization Vol 5 No 2 (2022): December 2022
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.2.4927

Abstract

The Directorate General of Customs and Excise (DJBC) serves as a revenue collector in the field of customs and excise. This revenue plays an essential role in supporting infrastructure development. Predictions are needed to plan a good State Revenue and Expenditure Budget (APBN). Predictions serve as a tool for revenue optimization and control. However, forecasting is problematic because unpredictable external factors also influence these receipts. A logical and accountable approach is needed to predict acceptance to overcome this problem. The prediction method used is Autoregressive Integrated Moving Average (ARIMA). According to the computations, the Root Mean Square Percentage Error (RMSPE) value is less than 10%, indicating that the ARIMA model estimation is excellent
Designing Learning Monitoring snd Evaluation Management Systems for Lecturer Performance in Informatics Study Program: (Case Study : Universitas Sarjanawiyata Tamansiswa) Eka Yulia Sari; Titik Rahmawati; Dina Yulina Heriyani
Journal of Information Technology and Its Utilization Vol 5 No 2 (2022): December 2022
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.2.4952

Abstract

The main responsibilities of a lecturer is to transform, to develop and to transfer knowledge through teaching and learning process. Assessment by students for their lecturers to provide input for lecturers and study program quality is needed so that the teaching and learning process can be controlled and in accordance with the established quality standards. In carrying out the process of monitoring and evaluating on lecturer performance, the Informatics Study Program, Faculty of Engineering, Universitas Tamansiswa is currently using Google form to distribute questionnaires. This is considered ineffective and produces invalid data. Therefore, the use of technology can be a solution to this problem. The purpose of this research is to design a management information system model for monitoring and evaluating learning that can facilitate the software development stage. The design of this learning monitoring and evaluation processing system uses the Unified Modeling Language (UML) model. While the software development method proposed by the author is Agile Software Development. The result of this research is a design model with UML in the form of use case diagrams, activity diagrams, and class diagrams, where the results of this design model can facilitate the next stage of software development. In addition, PIECES analysis is used to assist in identifying weaknesses in the current system to facilitate the mapping of system requirements. Needs mapping is used to identify the proposed new system, in which this proposed new system has 4 user levels, namely: administrator, GMP (Gugus Mutu Prodi), lecturers and students. Each user has its own authority in the proposed system.

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