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Jurnal Transformatika
Published by Universitas Semarang
ISSN : 16933656     EISSN : 24606731     DOI : -
Core Subject : Science,
Computer Science & IT
Transformatika is a peer reviewed Journal in Indonesian and English published two issues per year (January and July). The aim of Transformatika is to publish high-quality articles of the latest developments in the field of Information Technology. We accept the article with the scope of Information Systems, Web Technology, Computer Networks, Artificial Intelligence, and Multimedia.
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Articles 10 Documents
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Search results for , issue "Vol. 19 No. 2 (2022): January 2022" : 10 Documents clear
Content Classification based-on Latent Semantic Analysis and Support Vector Machine (LSA-SVM) Marthasari, Gita Indah; Hayatin, Nur; Yuniarti, Maulidya
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.2745

Abstract

The diversity of the content of a web page can have a negative impact if used by the wrong user. Almost a half of internet users are children. Therefore, it is important to classify web pages to find out which pages are worthy of being seen by children and that are not feasible. One method that can be used is the Support Vector Machine (SVM) algorithm. SVM is a binary classification whose working principle is to find the best hyperplane to separate the two classes. To obtain better classification accuracy, the SVM is combined with the Latent Semantic Analysis (LSA) algorithm. The data used in this study were taken from the DMOZ web data which has been classified into two categories. The data is then entered into the pre-processing stage for further feature extraction using LSA. The LSA algorithm is used to find out the semantic similarities of words and text contained in web pages. The results of feature extraction are then classified using SVM with RBF kernel. Based on the testing result, we obtain a classification accuracy of 64%.
USABILITY EVALUATION MODEL USING CONFIRMATORY FACTOR ANALYSIS ON ONLINE BUYING SITES Solechan, Achmad; Putra, Toni Wijanarko Adi
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.3624

Abstract

The data obtained from the Top brand index shows that there are 3 market leaders of online buying and selling sites in Indonesia, namely lazada.co.id; shopee.co.id and tokopedia.com. This makes the reason for choosing the object of research with the aim of research to find out the usability evaluation model using confirmatory factor analysis. The research data were obtained by distributing questionnaires as many as 150 respondents to 3 market leader online trading sites in Indonesia, namely lazada.co.id; shopee.co.id and tokopedia.com. The five components that will be used to turn into a questionnaire are learning ability, memory, efficiency, errors, satisfaction. The results showed that the design of the model in solving this particular problem is needed to measure the level of suitability of the use of the technology being made, so that research that has been carried out using the CFA method for the usability evaluation model can be concluded that by using 5 latent variables and 22 constituent indicators, resulting latent variables which are very influential in evaluating usability on online buying and selling sites. The results of the data analysis on questionnaire filling conducted by respondents were based on five variables, namely learnability, memorability, efficiency, errors and satisfaction, namely the most important factors in usability evaluation were memorability, efficiency, errors, with each index value of 5.60 in the very high category. Meanwhile, the Learnability factor has the lowest score of 5.56.
Penerapan K-Nearest Neighbors (KNN) untuk Klasifikasi Aset dalam Upaya Menentukan Aset Wakaf Produktif Sugiarto, Edi; Fahmi, Amiq; Muslih, Muslih; Hendriyanto, Novi
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.3356

Abstract

aset wakaf berupa tanah yang tersebar di Indonesia terbilang cukup besar, sehingga aset wakaf yang besar ini perlu dikelola dengan baik agar tidak menimbulkan banyak permasalahan yang pada akhirnya tanah wakaf tidak sesuai dengan tujuannya dan tidak dapat digunakan untuk kepentingan umat. Instrument pengamanan aset wakaf telah memenuhi, namun masih banyak muncul persoalan mengenai aset wakaf seperti menguapnya bondo wakaf, sengketa, alih fungsi, dll, sehingga dalam hal ini menunjukan bahwa banyak persoalan terkait pengelolaan aset wakaf yang harus dipecahkan. potensi wakaf sangat besar, bahkan diperkirakan potensi tanah wakaf di indonesia mencapai lima kali luas singapura, namun saat ini belum dikelola secara profesional dan lebih produktif. Penggunaan tanah wakaf di indonesia masih identik dengan masjid dan makam, padahal wakaf dapat juga dikelola menjadi aset-aset ekonomi yang menghasilkan keuntungan sehingga hasil dari wakaf produktif tersebut dapat digunakan untuk kepentingan umat. K-Nearest Neighbors (KNN) merupakan algoritma klasifikasi yang didasarkan pada analogi yaitu membandingkan data uji dengan data latih yang berada dekat dengan dan memiliki kemiripan dengan data uji tersebut, dalam penelitian ini KNN digunakan sebagai metode untuk klasifikasi aset wakaf guna mengidentifikasi aset wakaf tersebut berpotensi produtif atau tidak produktif. Penelitian dilakukan dengan menggunakan 57 data aset wakaf yang diperoleh dengan membagi menjadi 45 data untuk training dan 12 untuk testing. Hasil pengujian yang telah dilakukan membuktikan metode KNN ini memiliki akurasi yang baik untuk klasifikasi aset wakaf yaitu mencapai 93% pada data training dan 83% pada data testing.
Sistem Informasi Pendanaan Proyek Berbasis Web Pada Perusahaan Jasa Konstruksi Magdalena, Hilyah; Santoso, Hadi; Leonita, Litha
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.3670

Abstract

CV. YustiKarya as a construction company realizes that the ability to manage project finance is one of the important requirements for smooth project management. CV. YustiKarya often has to manage several projects simultaneously with remote locations. This condition made it difficult for financial staff in the office to manage project financial allocations and also made it difficult for project managers in the field and had to report the status of project expenditures to the office. This difficulty drives CV. YustiKarya is to improve the project's financial management system which originally used a spread sheet to become a web-based information system. Web-based information systems will be developed using object-oriented methods. The object-oriented system development method was chosen because of its modular development capabilities and adapts to system requirements. The information system that is produced is able to create a construction project management system starting from employer entry, contract entry, billing entry, printing proof of receipt, printing proof of expenditure, and generating project income and expenditure reports online. Web-based information systems will automate the financial status of projects whose locations are scattered. This system also makes it easy for directors to be aware of current project developments.
Semantic Web Seni Pertunjukan Indonesia Virginia, Gloria; Susanto, Budi; Proboyekti, Umi; Nugraha, Silvanus Satno
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.4327

Abstract

Documentation of performance arts is an effort of cultural heritage to maintain the dignity and nobility of a nation.   Semantic web is a promising alternative that support the objective.   From the user side, the website will be more informative, while from the technical side, the website has ontology (a well-defined formal knowledge which is highly potential to be related to other websites). This research is an effort to developed a performance arts ontology using Methontology method.   To enrich the ontology, two ontologies were merged .   Linked-data principal was implemented by the use of dbpedia.   The ontology was evaluated based on 4 parameters (consistency, completeness, verification, and validation) and proved to be effective while implemented in a website.
Evaluasi Kualitas Website Menggunakan Webqual 4.0 (Studi Kasus: Sistem Informasi Kebencanaan Kabupaten Boyolali) Ramadhan, Muhammad Rizky; Hartomo, Kristoko Dwi
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.4195

Abstract

This study aimed to measure the quality of the Disaster Mitigation Information System (Sikabi) belonging to the Regional Disaster Management Authority of Boyolali Regency. Quality tests are carried out to determine the quality and functionality of the system that functions optimally and can display accurate, easily accessible, and useful information for disaster mitigation in the region. The results of the study are useful for providing feedback to information system developers regarding the quality of the website usability aspect, the quality of the information presented, and the quality of the interactions provided as well as the user satisfaction at accessing the Disaster Information System website. This study uses the Webqual 4.0 method which has 4 assessment variables, namely in terms of usability (information quality), interaction service (interaction quality), and user satisfaction while accessing the website (overall impression). From the research results, the information quality variable has a sig value. 0,000 <0,05 which indicates that there is an influence of information quality on user satisfaction in using the Sikabi website. Therefore, we recommend improving the quality of the information displayed on the Sikabi website page.
Evaluation of The Implementation of IBM IOC Using the Delone and Mclean Model SARI, DWI ITA NURMALA
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.3870

Abstract

Information systems are an essential part of technological progress, the success of information systems that can produce precise, accuracy, quality, and fast information that enhances the performance of organizations and people. According to Delone and McLean's model, there are an information system's critical success factors. Six key variables that support information systems success are information quality, quality system, service quality, use, user satisfaction, and net benefits. This research uses quantitative research methods, and the data used were 80 respondents by using purposive sampling, assisted by using questionnaire data collection methods. Analysis of the data used is PLS-SEM using the SmartPLS application. The results showed a significant effect on the quality information on use, user satisfaction, and net benefits. There is no significant effect on the quality system to use, user satisfaction, and net benefits. Quality of service is significant for use and net benefits, but there is no significant effect on user satisfaction.
Classification Covid-19 Based on X-Ray Using GLCM and ANN Backpropagation Riyanto, Ghafur Ade
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.4518

Abstract

Coronavirus (Covid-19) is a disease that belongs to a large family of disorders that can cause mild to severe symptoms. The coronaviruses Middle East Respiratory Syndrome (MERS) and Serious Acute Respiratory Syndrome (SARS) are two types of coronaviruses that cause severe illness (SARS). According to WHO estimates as of December 17, 2021, Covid-19 has infected about 271,963,258 individuals, with a death rate of 5,331,019 cases. Hospitals only have a limited number of Covid-19 test kits because of the daily increase in cases. As a result, to prevent the spread of Covid-19 among persons, it is necessary to develop an automatic detection method as quickly as feasible, as well as other diagnosis options. The goal of this research was to employ GLCM to extract features and the Backpropagation Neural Network classification technique to automatically develop a Covid-19 diagnosis system by classifying the lungs into two groups: normal lungs and Covid-19 lungs. Pre-processing, segmentation, feature extraction, and classification were all used in this study's lung classification method. The accuracy of the test findings was assessed to be 85%. The sensitivity value for the normal class was 92.5%, whereas the sensitivity value for the Covid-19 class was 77.5%. The specification value for the normal class was 22.5%, whereas the specification value for the covid-19 class was 7.5%. It may be deduced from the accuracy, sensitivity, and specification percentages that the developed system is capable of categorizing lungs using X-Ray lung pictures.
Implementasi Algoritma C5.0 untuk menentukan Pelanggan Potensial di Kantor Pos Cimahi Harani, Nisa Hanum; Rahayu, Woro Isti; Damayanti, Fanny Shafira
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.3098

Abstract

Kantor Pos Cimahi merupakan perusahaan BUMN yang bergerak pada bidang jasa pengiriman barang. Saat ini banyak perusahaan swasta yang bergerak dalam bidang jasa pengiriman barang, sehingga menyebabkan banyaknya pesaing bagi Kantor Pos Cimahi dan dapat menyebabkan pelanggan yang menggunakan jasa Kantor Pos Cimahi berkurang. Oleh karena itu diperlukan suatu sistem yang dapat membantu Kantor Pos Cimahi untuk dapat menentukan pelanggan potensial agar dapat diketahui pelanggan mana yang potensial sehingga dapat diberikan perlakuan khusus agar pelanggan tersebut tetap menggunakan jasa Kantor Pos Cimahi. Sistem yang dibangun menggunakan bahasa pemrograman PHP dan metode Algoritma C 5.0 yang merupakan salah satu algoritma pohon keputusan yang dapat membantu untuk menentukan pelanggan potensial. Penelitian menggunakan data transaksi periode bulan januari oktober 2020 dimana atribut yang digunakan yaitu bulan, nama perusahaan, jenis kiriman yang digunakan, jumlah transaksi selama sebulan, dan total uang. Hasil penelitian menunjukan bahwa algoritma C 5.0 mampu melakukan menentukan data pelanggan potensial dengan akurasi sebesar 96%.
IMPLEMENTASI ALGORITMA LINEAR REGRESSION UNTUK PREDIKSI HARGA SAHAM PT. ANEKA TAMBANG TBK Hermanto, Teguh Iman; Nugroho, Imam Ma ruf; Sunandar, Muhamad Agus; Totohendarto, Mochamad Hafid
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.4396

Abstract

Stock investments that provide high returns, but the higher the benefits offered, the higher the risk that will be faced in investing, especially if it is not supported by knowledge of analyzing stocks. This study utilizes the Data Mining prediction technique with the Linear Regression algorithm on the shares of PT. Aneka Tambang Tbk or ANTM. The dataset that will be used is downloaded through the Yahoo Finance website in the period January 2016 - March 2021. In this study the analytical method used is SEMMA (Sample, Explore, Modify, Model, Assess). With RapidMiner Studio 9.9 tools. The result of testing the RMSE (Root Mean Squared Error) value is 17.135, MSE (Mean Squared Error) is 293.599 and the MAPE (Mean Absolute Percentage Error) value is 1.87%. Based on the MAPE, the accuracy of the Linear Regression algorithm in predicting the stock price of PT. Aneka Tambang Tbk provides high-accuracy predictions.

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