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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.
Arjuna Subject : -
Articles 344 Documents
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IMPLEMENTATION OF FIREWALL MANGEL ON NETWORKS IN SMK ASSODIQIYAH SEMARANG Putra, Toni Wijanarko Adi; Widodo, Muchamad
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.4565

Abstract

This study aims to regulate bandwidth usage and monitor website access using MikroTik. Bandwidth regulation with the aim of equalizing internet use where the number of students and teachers is 500 people, while monitoring websites and blocking negative websites aims to limit student access, which amounts to 416 students, consisting of 120 junior high school students, 150 vocational high school students, and 150 students. SD 100 and students 66 people. This research was conducted at Asshodiqiyah Vocational School as a technology base in the school environment under the Asshodiqiyah Foundation. The Assodiqiyah Foundation oversees elementary, junior high, and vocational schools and accommodates foreign students as boarding students. The service location is located at Jl. Sawah Besar Timur No 99 Rt.9 Rw. 2 Kaligawe Village, Gayamsari District, Semarang City. The method used in this research is Research and Development (R&D) [4]. This research discusses how to create and implement to the public how to use the Mikrotik tool as a regulator of bandwidth usage and see the sites that are accessed and if necessary block sites that are considered less suitable for students to access. The expected result is an even use of internet bandwidth and security of site access from negative things. So that students will avoid the negative influences that exist from the internet.
SISTEM MANAJEMEN PENEGAKAN DIAGNOSA PENYAKIT TYPUS DENGAN METODE NAIVE BAYES Setijaningsih, Retno Astuti; Setiawan, Aries; Sugiyanto, Zaenal; Farida, Ida; Widjajanto, Budi; Rizqa, Ifan
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5792

Abstract

Dalam dunia kesehatan, beberapa gejala yang timbul bisa menjadi tanda-tanda penyebab dari beberapa penyakit sekaligus. Kondisi yang dilematis ini sering kali mempersulit pengambilan keputusan mengenai penyakit yang diderita seseorang. Penentuan langkah pencegahan maupun pengobatan juga menjadi sulit untuk dilakukan, sehingga pemeriksaan lanjutan perlu dilakukan oleh tim medis. Sangat dimungkinkan jika tim medis kurang akurat dalam menentukan analisis penyakit dikarenakan munculnya gejala yang sama pada beberapa penyakit. Diperlukan sistem penegakan diagnose penyakit dengan metode na ve bayes akan mampu membantu pembelajaran bagi mahasiswa dalam mengenal gejala-gejala penyakit typus, dan juga dilengkapi dengan solusi pencegahan maupun solusi penanggulangan.
Perbandingan LSTM dengan Support Vector Machine dan Multinomial Na ve Bayes pada Klasifikasi Kategori Hoax Cahyo, Puji Winar; Aesyi, Ulfi Saidata
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5880

Abstract

Hoax is fake news, now massively spread through social media. The impact of hoaxes is that people's misperceptions in understanding of news are very high. With the existence of hoaxes are spreading through social media, it requires the public to think smart when receiving the news. Currently, many ways to prevent hoaxes, right now we have Fact Checker Directory Platform which is a truth platform sourced from several fact check sites. On the truth check platform, every news detected as hoaxes has been categorized into specific type of hoax, manually by the validator. For this reason, this research attempts to automatically categorize the types of hoaxes using comparation of Deep Learning with Machine Learning classifications. Deep Learning uses Long Short Term Memory Network (LSTM), while Machine Learning uses Support Vector Machine (SVM) and Multinomial Naive Bayes. Through the build model process, SVM produces the best accuracy quality of 0.74, Multinomial Na ve Bayes produces an accuracy quality of 0.62 while LSTM displays 0.49. The results of low accuracy in LSTM need to be evaluated on model architecture and data normalization during preprocessing.
Penerapan Metode Case Based Reasoning Pada Sistem Pakar Diagnosis Dini Post Traumatic Stress Disorder dwiana, Tina -
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.4874

Abstract

AbstrakLatar Belakang: Pada kasus gangguan post traumatic stress disorder (PTSD) banyak orang yang tidak menyadari gejala-gejala awal karena masih menganggap hal biasa, akhirnya terlambat didiagnosis sehingga mencapai tahap kronis yang membuatnya sulit untuk ditangani, belum lagi kesalahan penyimpulan yang dilakukan oleh para dokter atau tenaga medis yang mengakibatkan kesalahan penanganan awal pada pasien. Padahal setiap penyakit sebelum mencapai tahap kronis atau arena tinggi umumnya menunjukkan gejala-gejala dini penyakit yang telah diderita oleh pasien tetapi masih dalam tahap ringan.Tujuan: Tujuan dari pembuatan sistem pakar ini adalah untuk mempermudah pasien untuk mengenali gejala-gejala dini gangguan post traumatic stress disorder sebelum mencapai tahap kronis.Metode: Metode pengambilan kesimpulan menggunakan metode case base reasoning dengan ambang batas kemiripan ‰¤ 70%   dengan basis kasus berbasis pengetahuan.Hasil: Berdasarkan hasil uji black box pada sistem menunjukan sistem dapat berjalan sesuai dengan yang diharapkan dan berdasarkan hasil uji pada sistem menggunakan basis kasus baru menghasilkan tingkat akurasi diatas 80%.Simpulan : Metode case base reasoning dapat digunakan untuk menentukan gangguan PTSD dengan nilai rata-rata akurasi diatas 80%, menunjukan bahwa sistem bisa digunakan untuk mendiagnosa gangguan PTSD.
Sistem Pendukung Keputusan Penerima Bantuan Kartu Indonesia Pintar dengan Metode Weighted Product Yuniarti, Wenty Dwi; Damayanti, Laili Zanura; Nur'aini, Siti
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5877

Abstract

Education is a bridge to educate the nation s life. The government has launched various programs for equitable distribution and expansion of access to education, one of which is Program Indonesia Pintar (PIP). Smart Indonesia Card (KIP) is a marker for PIP recipients. The implementation of PIP is considered effective if KIP is given on target. SMK An Najah has implemented PIP. Each period, SMK An Najah faces many applicants with complex requirements documents. Unfortunately, the determination of KIP aid recipients is still done manually, so it takes a long time and has the potential for inaccurate targets. This study proposes the use of a computer-based decision support system using the Weighted Product (WP) method to determine KIP recipients. WP uses a multiplication technique to connect attributes ratings that have been raised to the power of weight. Based on the evaluation using User Acceptance Testing (UAT), it is known that the decision support program can be used with an acceptance rate of 79.15% or in the worthy category.
Robusta London Coffee Price Forecasting Analysis Using Recurrent Neural Network – Long Short Term Memory (RNN – LSTM) Nosa, Ferzy Tryanda; Kurniasari, Dian; Amanto, Amanto; Warsono, Warsono
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5482

Abstract

Coffee price forecasting has a significant role in preventing price fluctuations at a time. Therefore, a method is needed that can be used to forecast the price of coffee. This study discusses the analysis of coffee price forecasting using the Recurrent Neural Network – Long Short-Term Memory (RNN – LSTM) method. This study will be determined the best LSTM model that aims to get the results of forecasting the price of London robusta coffee with the smallest  Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) values. Using the LSTM model with units of 128 and dropouts of 0.1, forecasting the price of London robusta coffee has an RMSE value of 1,303 and MAPE of 3.53%. Therefore, the LSTM model can indicate the cost of London robusta coffee with an accuracy rate of 96.47%. 
Pengembangan Laboratorium Virtual Bermuatan Project-Based Learning Berbasis Android Untuk Meningkatkan Pemahaman Siswa SMK Pada Mata Pelajaran Komputer Dan Jaringan Dasar Pratama, Muchammad Ryan; Elmunsyah, Hakkun; Asfani, Khoirudin; Aprillia, Dewi
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5029

Abstract

The Covid-19 outbreak has changed the learning system in Indonesia from face to face to distance. This causes the practicum learning process to experience difficulties because the practicum requires a real laboratory so that practicum activities can be carried out. Therefore, to solve these problems through the development of virtual laboratory learning media containing Android-based PjBL to improve student understanding. The existence of a virtual laboratory allows students to carry out practical simulations through these learning media flexibly. The development method used is Successive Approximation Model 1 with 3 iterative stages, namely (1) Evaluate, (2) Design, and (3) Develop. The test results of user testing get a percentage value of 88.17% with a very valid category. It was concluded that the learning media developed was very feasible to use and quite effective in increasing the understanding of SMK students majoring in TKJ on Computer and Basic Network subjects.  
Model Integer Programming untuk penugasan pekerjaan dengan waktu kedatangan dan keberangkatan yang berbeda Sugiyono, Andre; Kurniadi, Dedy
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5911

Abstract

Penelitian  ini membahas masalah alokasi peti kemas ke lokasi galangan terminal kapal dimana peti kemas memiliki waktu kedatangan dan keberangkatan yang berbeda untuk meminimalkan total biaya penanganan peti kemas. Diasumsikan bahwa jika lokasi galangan yang dipilih lebih dekat ke titik dimana peti kemas diturunkan dari kapal, biaya keseluruhan akan berkurang. Masalah ini dapat didefinisikan sebagai masalah alokasi mesin pekerjaan di mana biaya pemrosesan pekerjaan pada setiap mesin berbeda tetapi tidak tergantung pada waktu pemrosesan dan pekerjaan yang tidak dapat diakhiri memiliki waktu kedatangan dan keberangkatan yang berbeda. Masalah ini dirumuskan dalam solusi eksak sebagai model pemrograman integer campuran. Hasil komputasi menunjukkan bahwa heuristik ketiga yang diusulkan efisien dalam memecahkan masalah lokasi dalam biaya yang berbeda, jumlah pekerjaan, dan waktu komputasi.
MotoGP Mandalika 2022 Sentiment Classification Using Machine Learning Pardede, Doughlas; Hayadi, B. Herawan
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5364

Abstract

MotoGP is a world-class motorcycle racing event, which will be held in the 19th series in 2022 at the Pertamina Mandalika Circuit. This study tries to analyze public sentiment collected from the results of tweeter social media tweets, in the form of sentiment and emotion values. With the features of sentiment and emotion values extracted from the contents of this tweet, k-means clustering is used to generate sentiment clusters as targets for classification using the MLP algorithm. From the results of the evaluation using 10-fold cross validation, the accuracy value is 97%, the precision value is 94.64% and the recall value is 100%. The classification results also show that the public response to the 2022 MotoGP event at the Mandalika circuit is quite balanced, where 53% have a positive response, while the rest have a negative response
Perancangan Aplikasi SiCitra Menggunakan Unified Modelling Language Wardani, Deyana Kusuma; Rahmawati, Oktavia Citra Resmi; Fatihia, Wifda Muna
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.5886

Abstract

Find out the live location of the family or friends that be city bus passengers is the one of city bus application users needs that hasn t been implemented yet until now, so we propose the design of software engineering that has the main feature in the form of shared live location with people that allow knowing with utilizing Unified Model Language Diagram. There are 3 (three) types of UML Diagram that have we created in this research, including Use Case Diagram, Class Diagram, and Activity Diagram. Besides that, we also produce Entity Relational Diagram and System Design to fit up the design of software engineering. Thus with modeling software before starting the development process, the system will be structured and delivered to the user as well.

Page 27 of 35 | Total Record : 344

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