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All Journal Jurnal Dedikasi Sainteks TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Simantec Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Fountain of Informatics Journal JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Universitas Pamulang Jurnal Repositor JATI (Jurnal Mahasiswa Teknik Informatika) JIKA (Jurnal Informatika) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Jaring SainTek IICS Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Informatika: Jurnal Pengembangan IT
Gita Indah Marthasari
Universitas Muhammadiyah Malang
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Optimization of Sentiment Analysis for Indonesian Presidential Election using Naïve Bayes and Particle Swarm Optimization Nur Hayatin; Gita Indah Marthasari; Lia Nuarini
JOIN (Jurnal Online Informatika) Vol 5 No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.558

Abstract

Twitter can be used to analyze sentiment to get public opinion about public figures to find a trend in positive or negative responses, especially to analyze sentiments related to presidential candidates in the 2019 election in Indonesia. Naïve Bayes (NB) can be used to classify tweet feed into polarity class negative or positive, but it still has low accuracy. Therefore, this study optimizes the Naïve Bayes algorithm with Particle Swarm Optimization (NB-PSO) to classify opinions from twitter feeds to get a good accuracy of public figures sentiment analysis. PSO used to select features to find optimization values to improve the accuracy of Naïve Bayes. There are four steps to optimize NB using PSO, i.e., initializing the population (swarm), calculate the accuracy value that matched with selected features, selected the best accuracy of classification, and updating position and velocity. From this study, the group of tweets was obtained based on the positive and negative sentiments from the community towards two Indonesia presidential candidates in 2019. The NB-PSO test shows the accuracy result of 90.74%. The result of accuracy increases by 4.12% of the NB algorithm. In conclusion, the inclusion of the Particle Swarm Optimization algorithm for Naïve Bayes classification algorithm gives a significant accuracy, especially for sentiment analysis cases.
Analisis Usability dalam User Experience pada Sistem KRS Online UMM menggunakan USE Questionnaire Wahyu Andhyka Kusuma; Vebrian Noviasari; Gita Indah Marthasari
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 5 No 4: November 2016
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (825.165 KB)

Abstract

KRS-Online system is a web-based information system to assist the process of preparing the KRS of every student in University of Muhammadiyah Malang. In this research, the level of usability of the system will be measured and the relationship between the independent variables (usefulness,ease of use, and ease of learning) and dependent variable (satisfaction), either simultaneously or partially, will be analyzed. Usability measurement adopted in this study is USE questionnaire that contains usefulness, ease of use, ease of learning, and satisfaction variables. This research involves 100 respondents from the KRS-Online system users. The result shows that measuring usability produces feasibility of 73.312%, which means usability of KRS-Online system is "acceptable". On the other hand, this study proves that there is a significant influence between usefulness, ease of use, and ease of learning variables with the satisfaction variable simultaneously. In addition, usefulness and ease of use variables significantly affect the satisfaction variable partially, while the ease of learning variable does not significantly affect the satisfaction variable.
Prediksi Data Time-series menggunakan Jaringan Syaraf Tiruan Algoritma Backpropagation Pada Kasus Prediksi Permintaan Beras Gita Indah Marthasari; Silcillya Ayu Astiti; Yufis Azhar
Jurnal Informatika: Jurnal Pengembangan IT Vol 6, No 3 (2021): JPIT, September 2021
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v6i3.2627

Abstract

Recently, Indonesia, as a country where the majority of the population chooses rice as the primary food source, gets a decline in the rice consumption patterns, which resulted in reduced demand for rice that should have been stable. The decrease of rice purchasing power impacts several rice suppliers, commonly referred to as rice agents, to buy rice from rice production companies. Therefore, prediction of rice stock is essential to do. This paper aims to apply the backpropagation neural network method to forecast the amount of rice demand. The data used in the study is time-series data in the form of the number of requests for rice as much as 609 data from two types of rice. The modeling scenario in this study applies one to five hidden layers with a different number of hidden neurons in each experiment. The elastic net regularization method was applied after the data denormalization process to improve the quality of the resulting model. Based on the experiments, obtained the best model on architecture 7-50-200-300-250-300-1 with MSE = 0.001278, RMSE = 0.301950 in the training process and MSE results = 0.002391, RMSE = 0.204972 in the testing process.
Perancangan dan Implementasi Sistem E-Commerce berbasis Web pada UMKM Al Haadziq di Kabupaten Malang Gita Indah Marthasari; Mahar Faiqurahman; Luqman Hakim
TEMATIK Vol 10 No 1 (2023): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2023
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v10i1.1238

Abstract

Pandemi Covid-19 yang melanda Indonesia memberi dampak signifikan terhadap keberlangsungan Usaha Mikro Kecil dan Menengah (UMKM). Namun, pandemi juga mendatangkan peluang kepada pelaku UMKM untuk memanfaatkan teknologi informasi dan komunikasi (TIK) sebagai support sytem bagi usahanya. Al Haadziq Team merupakan UMKM yang bergerak di bidang penjualan produk perawatan kulit. Selama ini, promosi dan transaksi penjualan produknya dilakukan melalui media sosial yaitu aplikasi WhatsApp. Untuk memperluas jangkauan pemasaran, pada kegiatan ini dirancang dan dibangun sebuah sistem e-commerce berbasis web yang diharapkan dapat menjadi media pemasaran yang strategis. Metode pelaksanaan diawali dengan analisis persoalan, pembuatan dan pengujian website. Analisis situasi dilakukan melalui observasi dan wawancara kepada pengguna. Selanjutnya, dilakukan rancang bangun aplikasi web dengan fitur-fitur antara lain manajemen katalog dan pemesanan produk. Berdasarkan hasil pengujian, disimpulkan bahwa web e-commerce telah sesuai dengan pengguna.
Assistance in Preparing Engineering Prompts for Muhammadiyah School Teachers to Optimize the Use of ChatGPT in the World of Education: Pendampingan Penyusunan Prompt Engineering Bagi Guru Sekolah Muhammadiyah Untuk Mengoptimalkan Pemanfaatan ChatGPT Di Dunia Pendidikan Setio Basuki; Mahar Faiqurrahman; Gita Indah Marthasari; Rizky Indrabayu; Fatimatus Zachra; Nico Ardia Effendy
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 3 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i3.19522

Abstract

ChatGPT, a widely used Large Language Model (LLM), enhances productivity in various sectors, including education. However, its extensive usage often lacks proficiency in writing effective prompts, resulting in less optimal, biased, and hallucinated outputs. This community service initiative by Universitas Muhammadiyah Malang (UMM) aims to educate teachers on prompt engineering, enabling them to (i) write effective prompts to utilize ChatGPT's potential, (ii) educate about potential biases and hallucinations of ChatGPT, and (iii) integrate ChatGPT into educational practices with integrity. Partnering with three Muhammadiyah Schools, the program trains 7-8 teachers from each institution. The training covers five key areas: (a) prompt engineering introduction, (b) building optimal prompts, (c) leveraging ChatGPT in teaching and learning, (d) prompt engineering for educational material creation, and (e) ethics of LLM usage in professional and academic settings. The effectiveness of this program is evaluated through pre-test and post-test questionnaires. Results indicate a significant improvement in prompt engineering proficiency, rising from 35.3% (pre-test) to 87.5% (post-test), and in the utilization of ChatGPT for learning support, increasing from 23.5% (pre-test) to 81.3% (post-test).
Optimization of Sentiment Analysis for Indonesian Presidential Election using Naïve Bayes and Particle Swarm Optimization Nur Hayatin; Gita Indah Marthasari; Lia Nuarini
JOIN (Jurnal Online Informatika) Vol 5 No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.558

Abstract

Twitter can be used to analyze sentiment to get public opinion about public figures to find a trend in positive or negative responses, especially to analyze sentiments related to presidential candidates in the 2019 election in Indonesia. Naïve Bayes (NB) can be used to classify tweet feed into polarity class negative or positive, but it still has low accuracy. Therefore, this study optimizes the Naïve Bayes algorithm with Particle Swarm Optimization (NB-PSO) to classify opinions from twitter feeds to get a good accuracy of public figures sentiment analysis. PSO used to select features to find optimization values to improve the accuracy of Naïve Bayes. There are four steps to optimize NB using PSO, i.e., initializing the population (swarm), calculate the accuracy value that matched with selected features, selected the best accuracy of classification, and updating position and velocity. From this study, the group of tweets was obtained based on the positive and negative sentiments from the community towards two Indonesia presidential candidates in 2019. The NB-PSO test shows the accuracy result of 90.74%. The result of accuracy increases by 4.12% of the NB algorithm. In conclusion, the inclusion of the Particle Swarm Optimization algorithm for Naïve Bayes classification algorithm gives a significant accuracy, especially for sentiment analysis cases.
Redesigning the User Interface in the Mobile-Based Ngaji.AI Application Using the Design Thinking Method Aminudin; Aldiensyah; Gita Indah Marthasari; Ilyas Nuryasin; Saiful Amien; Galih Wasis Wicaksono; Didih Rizki Chandranegara; I'anatut Thoifah
IAIC International Conference Series Vol. 4 No. 1 (2023): SEMNASTIK 2023
Publisher : IAIC Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/conferenceseries.v4i1.635

Abstract

Ngaji.AI is a mobile-based application that makes it possible to learn the recite very flexibly, wherever and whenever we can use it to learn the recite. This application is supported by artificial intelligence (AI) which provides direct and accurate assessments of how to recite Al-Quran verses properly and correctly and this application has been released on the Google Playstore platform and has been downloaded by more than 5 thousand. The Ngaji.AI application is faced with a crucial challenge, after direct observation of children and through the results of previous user input on Playstore, most of the input from users states that it needs to improve the User Interface (UI) design to make it easier to operate for children. The application of the Design Thinking method is an approach that prioritizes creativity and deep understanding of users and the problems they face and is indeed suitable for developing UI/UX of an application. Testing using the System Usability Scale (SUS) in the first test before the redesign got an average score of 50.25 and after the redesign got a significant score of 83.75. This reflects a significant increase in the level of satisfaction and ease for children in learning to recite the recite on the Ngaji.AI application.
Leveraging ESRGAN for High-Quality Retrieval of Low-Resolution Batik Pattern Datasets Azhar, Yufis; Marthasari, Gita Indah; Regata Akbi, Denar; Minarno, Agus Eko; Haqim, Gilang Nuril
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.3202

Abstract

As one of the world's cultural heritages in Indonesia, batik is one of the quite interesting research subjects, including in the realm of image retrieval. One of the inhibiting factors in searching for batik images relevant to the query image input by the user is the low resolution of the batik images in the dataset. This can affect the dataset's quality, which automatically also impacts the model's performance in recognizing batik motifs with complex details and textures. To address this problem, this study proposes using the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) method to increase the resolution of batik images. By increasing the resolution, it is hoped that ESRGAN can clarify the details and textures of the initial low-resolution image so that these features can be extracted better. This study proves that ESRGAN can produce high-resolution batik images while maintaining the details of the batik motif itself. The resulting image's high PSNR and low MSE values confirm this. The implementation of ESRGAN has also been proven to improve the performance of the image retrieval system with an increase in precision and average precision values between 1-5% compared to other methods that do not implement it.
Implementasi Teknik Search Engine Optimization (SEO) Menggunakan Metode White Hat SEO Pada Website Xuzu (Studi Kasus: PT. Bintang Konveksi Indo) Cahyanto, Mochammad Andre; Aminudin, Aminudin; Marthasari, Gita Indah
Sainteks Vol. 21 No. 2 (2024): Oktober
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/sainteks.v21i2.21843

Abstract

PT. Bintang Konveksi Indo adalah perusahaan jasa pembuatan pakaian dan aksesoris, termasuk baju dinas, baju organisasi, dan perlengkapan wisuda. Perusahaan tersebut juga memperkenalkan brand XUZU dengan fokus pada kualitas, desain, dan pelayanan terbaik. Namun, saat ini bisnis tersebut mengalami kesulitan dalam mengenalkan produk ke luar daerah karena kurangnya media pendukung. Untuk itu, perusahaan ingin mengembangkan sarana pemasaran alternatif secara online melalui website yang mudah ditemukan di mesin pencarian. Tujuan penelitian ini adalah meningkatkan visibilitas website pada mesin pencarian. Metode yang digunakan yaitu teknik White Hat SEO yang diintegrasikan dengan data terstruktur seperti schema markup. Untuk mengetahui peningkatan rangking pada mesin pencarian, dilakukan pengujian dan analisis menggunakan tools pengujian yaitu SEO Site Checkup, Google search Console, Google Analytics dan perkembangan rangking pada Search Engine Result Page (SERP). Hasil Penelitian menunjukkan penerapan White Hat SEO berhasil meningkatkan visibilitas dan peringkat website berdasarkan analisis Google Search Console dan Google Analytics. Dan integrasi Schema Markup juga berdampak positif, meningkatkan kunjungan pengguna dan Click Through Rate (CTR) karena pengguna lebih tertarik pada informasi terstruktur.
Implementasi Metode Personal Extreme Programming Pada Pengembangan Sistem Informasi Surat Menyurat(Studi Kasus: Dinas Pendidikan Pemuda Dan Olahraga Kabupaten Tambrauw) Alfin Lutfi Sidiq; Gita Indah Marthasari; Aminudin
Jurnal Jaring SainTek Vol. 7 No. 1 (2025): April 2025
Publisher : Fakultas Teknik, Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/zsbj5v55

Abstract

Dinas Pendidikan Pemuda Dan Olahraga Kabupaten Tambrauw mempunyai tugas membantu Bupati melaksanakan urusan pemerintahan yang menjadi kewenangan daerah dan tugas pembantuan di bidang pendidikan serta tugas lain yang diberikan Bupati. Beberapa masalah yang terjadi dalam pelaksanaan proses bisnis pada pembuatan surat karena masih dilakukan secara manual sehingga pengelolaan surat yang berjalan saat ini masih banyak mengalami kendala. Maka dari itu, dibutuhkan dukungan teknologi informasi yang dapat mengelola sistem informasi surat menyurat yang dapat dibagun secara tepat dan cepat. Metode pengembangan perangkat lunak yang digunakan adalah Personal Extreme Programming (PXP), yang merupakan metode dengan pengembang tunggal. Metode Personal Extreme Programming (PXP) memiliki tahapan penggalian kebutuhan, perencanaan, desain, implementasi, system testing, dan retrospective. Hasil dari penelitian ini adalah terdapat 13 user story, kemudian terjadi penambahan user story di tengah pengembangan sistem sehingga menjadi 15 user story. Pengujian dalam penelitian ini menggunakan unit testing pada tahap implementasi, dan Black Box Testing, dimana akan dilakukan dengan menjalankan unit atau modul dan diamati hasil nya telah sesuai dengan fungsi yang diinginkan pada tiap iterasi. Hasil iterasi yang sudah dikerjakan memiliki hasil yang cukup memuaskan dengan rata – rata lebih cepat dari waktu estimasi. Estimasi waktu pengembangan sistem selama 40 hari. Akan tetapi dalam praktiknya, keseluruhan waktu pengembangan sistem bertambah 10 hari menjadi 50 hari dikarenakan penambahan user stories baru dan iterasi baru. Namun waktu implementasi yang dilakukan selama 37 hari lebih cepat 13 hari dari waktu estimasi yang telah ditentukan
Co-Authors Abu Hanifah Adam Novrisal Agus Eko Minarno Akbi, Denar Regata Aldiensyah Alfin Lutfi Sidiq Amelia Deastu Amelia Dwi Deastu Aminudin AMINUDIN Aminudin, Aminudin Anastasia Lidya Maukar Andjani Chaerun Nisha Anggraini, Syadza Ani Tri Wahyuningsih Anik Vega Vitianingsih Arif Rahmadhani Basuki, Setio Belli Kafilla Gani Briansyah Setyo Wiyono Cahyanto, Mochammad Andre Chita Nauly Harahap Christian Sri Kusuma Aditya Darfian Ardiansyah Diah Risqiwati Didih Rizki Chandranegara Dwi Kurnia Puspitaningrum Eko Budi Cahyono Elsyah Ayuningrum Elza Norazizah Evi Dwi Wahyuni Fajarisma Asfiana Putri Fajrur Rahman Suprapto Fakhrul Islami Fathoni, Muhammad Asrar Fatimah Defina Setiti Alhamdani Fatimatus Zachra Febri Ayu Fitriani Ferin Reviantika Frengky Prastyo Gita Ismadianti Hanafi Prasetyoko Haqim, Gilang Nuril Haris Diyaul Fata Harizal Iqmal Hasan I'anatut Thoifah Imam Halimi Irsandro, Ahmad Karima Maydina Yanti Kresna Arief Nugraha Lailatul Husniah Lia Nuarini Luqman Hakim M. Isnainur Hidyatullah Mahar Faiqurahman Mahar Faiqurrahman Mairissa Anggraini Moh. Taufiq Hidayat Muhammad Alfian Ramadhani Muhammad Asrar Fathoni Muhammad Gufron Muhammad Ilham Muhammad Iqbal Muhammad Iqbal Ramadhan Muhammad Rizky Aviansyah Muhammad Ulfi Nabillah Annisa Rahmayanti Nico Ardia Effendy Nina Mauliana Noor Fajriah Nirma Dwi Wulansari Nirma Noviasari, Vebrian Nur Hayatin Nur Riyan Sahara Nuryasin, Ilyas Pendi, Wendi Praadita, Firman Noor Rellanti Diana Kristy Risdianto Risdianto Rizky Indrabayu Rizky Irwan Saputra Roni Hadi Wijaya S, Vinna Rahmayanti Saiful Amien Silcillya Ayu Astiti Syadza Anggraini Syaifudin Zuhri Tsabitah Ayu Rahmawati Tutik Sulistyowati Vebrian Noviasari Wahyu Andhyka Kusuma Waliyyullah Mufid Wicaksono, Galih Wasis Wildan Suharso Wiyono, Briansyah Setio Wiyono, Briansyah Setyo Yudi Ananta Prasetya Yufis Azhar Yuniarti, Maulidya Zakaria, Irfan Zakiyah Mahfudho Zamah Sari Zildan Rahmatullah