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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi International Journal of New Media Technology KACANEGARA Jurnal Pengabdian pada Masyarakat JOURNAL OF SCIENCE AND APPLIED ENGINEERING IJID (International Journal on Informatics for Development) Jurnal Berdaya Mandiri Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Dinamika Informatika (JDI) Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia Jurnal INFOTEL Teknomatika: Jurnal Informatika dan Komputer
Kusumaningtyas, Kartikadyota
Universitas Jenderal Achmad Yani Yogyakarta
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SMART PERPUSTAKAAN: INOVASI PENINGKATAN LITERASI SEKOLAH ANAK USIA DINI AKAR TUMBUH MELATI DI KELURAHAN SENDANGADI MLATI SLEMAN Aris Wahyu Murdiyanto; Kartikadyota Kusumaningtyas; Ikbal Rizki Putra; Septiyati Purwandari; Bara Falah Adikaputra; Agung Satria Panca; Fitriatul Hasanah
Jurnal Berdaya Mandiri Vol. 6 No. 3 (2024): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v6i3.7184

Abstract

This program aims to enhance educational services and literacy knowledge among early childhood students at Akar Tumbuh Melati School through the implementation of appropriate technology (Smart Perpustakaan). The activities were carried out in five stages: socialization, training, technology implementation, assistance, and evaluation with sustainability measures. The Smart Perpustakaan technology includes a library space, an encyclopedia book collection, virtual reality (VR) videos for interactive reading activities, and Cardboard VR devices. The results show a 92% increase in digital literacy knowledge and a 33.33% improvement in the quality of educational services. This program successfully reduced children's dependency on non-educational digital content and opened opportunities for sustainable collaboration with related stakeholders. Keyword: early childhood literacy, educational services, appropriate technology, Smart Library, community service
Ekstraksi Aspek Aksesibilitas untuk Peningkatan Pengalaman Pengguna Menggunakan NER dengan CNN dan LSTM Dwijayanti, Irmma; Rizqi Lahitani, Alfirna; Kusumaningtyas, Kartikadyota; Habibi, Muhammad
JURNAL FASILKOM Vol. 14 No. 3 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i3.8032

Abstract

Transportasi online memberikan dampak positif bagi sebagian besar masyarakat, namun penggunaan aplikasi oleh penyandang disabilitas masih menghadapi sejumlah tantangan. Belum adanya fasilitas yang memadai dan pengalaman pengguna yang baik menjadi kendala utama. Realitas ini menunjukkan bahwa perlunya perhatian khusus terhadap prinsip aksesibilitas untuk meningkatkan pengalaman pengguna dan kenyamanan bagi penyandang disabilitas. Melalui ulasan pengguna dapat diidentifikasi aspek-aspek aksesibilitas untuk mendukung peningkatan pengalaman pengguna. Penelitian ini bertujuan mengekstraksi informasi dari ulasan pengguna terkait aksesibilitas menggunakan metode NER dengan pendekatan CNN dan LSTM. Data yang dikumpulkan melalui web scraping terdiri dari 6.255 ulasan aplikasi Gojek, Grab, Maxim, dan Indriver. Hasil evaluasi menunjukkan bahwa kedua model memiliki akurasi tinggi yaitu CNN 99,84%, dan LSTM 99,48%. Namun memerlukan perbaikan dalam mendeteksi entitas yang jarang muncul atau berkonteks kompleks. Hasil analisis menunjukkan bahwa ulasan lebih banyak membahas fitur aplikasi dan keluhan yang berkaitan dengan aksesibilitas. CNN lebih efektif dalam menangkap pola spesifik, sedangkan LSTM lebih kuat dalam menangkap variasi kata.
Analisis Tren Topik dalam Ulasan Negatif Aplikasi M-Banking Menggunakan Latent Dirichlet Allocation Kusumaningtyas, Kartikadyota; Dwijayanti, Irmma; Rizqi Lahitani, Alfirna; Habibi, Muhammad
JURNAL FASILKOM Vol. 14 No. 3 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i3.8035

Abstract

Mobile banking atau M-banking menjadi semakin populer seiring dengan meluasnya penggunaan ponsel pintar. Pertumbuhan ini didorong oleh beberapa faktor, seperti kebijakan pemerintah melalui Gerakan Nasional Non-Tunai (GNTT) dan inovasi dari bank. Latar belakang penelitian ini berangkat dari pentingnya merespons keluhan pengguna terhadap aplikasi M-banking. Ulasan negatif mencerminkan masalah yang dialami pengguna dan bisa memengaruhi kepercayaan terhadap layanan. Sayangnya, platform seperti Google Play Store tidak menyediakan fitur untuk mengidentifikasi tren dari ulasan negatif. Oleh karena itu, penelitian ini menggunakan metode Latent Dirichlet Allocation (LDA) untuk memodelkan tren topik dalam ulasan negatif guna memberikan wawasan bagi penyedia layanan untuk meningkatkan kualitas aplikasi mereka. Penelitian ini dilakukan melalui beberapa tahap, dimulai dengan pengumpulan data ulasan negatif dari tiga aplikasi M-banking populer. Selanjutnya data akan melalui tahap preprocessing, meliputi: tokenizing, stopwords removal, dan stemming. Sentimen dari ulasan dianalisis menggunakan algoritma Support Vector Machine (SVM) dengan akurasi mencapai 93%, untuk memisahkan ulasan positif dan negatif. Selanjutnya, LDA digunakan untuk memodelkan topik pada ulasan negatif, dengan mengidentifikasi sejumlah topik optimal melalui Coherence Score, yang menunjukkan struktur topik yang logis dan terorganisir. Hasil penelitian menunjukkan bahwa pada BRImo, topik yang dominan adalah biaya dan kecepatan layanan aplikasi. Pada BCA mobile, pengguna lebih banyak membahas fitur dan kemudahan penggunaan aplikasi, sedangkan pada Livin’ by Mandiri, topik utama yang dibahas berkaitan dengan fitur transfer dan jam transaksi. Kesimpulan dari penelitian ini adalah bahwa metode LDA berhasil digunakan untuk menemukan tren utama dari ulasan negatif pengguna, yang diharapkan dapat membantu bank dalam meningkatkan kualitas layanan dan keamanan aplikasi mobile banking.
Online Integrated Development Environment (IDE) in Supporting Computer Programming Learning Process during COVID-19 Pandemic: A Comparative Analysis Kusumaningtyas, Kartikadyota; Nugroho, Eko Dwi; Priadana, Adri
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09202

Abstract

COVID-19 has spread to various countries and affected many sectors, including education. New challenges arise in universities with study programs related to computer programming, which require a lot of practice. Difficulties encountered when students should setting up the environment needed to carry out programming practices. Furthermore, they should install a text editor called Integrated Development Environment (IDE) to support it. There is various online IDE that supports computer programming. However, students must have an internet connection to use it. After all, many students cannot afford to buy internet quotas to access online learning material during the COVID-19 pandemic. According to these problems, this study compares several online IDEs based on internet data usage and the necessary supporting libraries' availability. In this study, we only compared eleven online IDEs that support the Python programming language, free to access, and do not require logging in. Based on the comparative analysis, three online IDEs have most libraries supported. They are REPL.IT, CODECHEF, and IDEONE. Based on internet data usage, REPL.IT is an online IDE that requires the least transferred data. Moreover, this online IDE also has a user-friendly interface to place the left and right sides' code and output positions. It prevents the user from scrolling to see the results of the code that has been executed. The absence of advertisements also makes this online IDE a more focused appearance. Therefore, REPL.IT is highly recommended for users who have a limited internet quota, primarily to support the learning phase of computer programming during the COVID-19 pandemic.
Tweets Classification of Mental Health Disorder in Indonesia Using LDA and Cosine Similarity Dwijayanti, Irmma; Habibi, Muhammad; Kusumaningtyas, Kartikadyota; Riyadi, Sujono
Telematika Vol 21 No 1 (2024): Edisi Pertama 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i1.10725

Abstract

Purpose: Twitter related to mental health has great potential as a medium to provide important information to the public and health organizations on a large scale, but an evaluation of tweet data related to mental health disorders has not been carried out. This study aims to classify tweet data to determine the most common mental health disorders in Indonesia based on the symptoms experienced.Methodology: The classification process is carried out using cosine similarity calculations between tweets data and keywords which are compiled based on theoretical studies and optimization of the LDA topic modeling results.Findings/result:The classification results show that the most discussed issues on Twitter are depression, bipolar, schizophrenia, dementia, and PTSD. Based on these results it can be interpreted that the level of prevalence and public attention to depressive diorders is quite high compared to other disorders. From the results of the classification, it is also possible to identify the most discussed symptoms throughthe emergence of keywords from each category.Originality: Classification is calculated based on the cosine similarity between tweets and keywords compiled from human judgement and enriched using the results of LDA topic modeling to improve classification performance
EDUKASI LITERASI KESEHATAN MENTAL BERBASIS DIGITAL MELALUI PENGENALAN PLATFORM DETEKSI DINI PADA GENERASI Z Irmma Dwijayanti; Alfirna Rizqi Lahitani; Kartikadyota Kusumaningtyas; Muhammad Habibi; Kharisma
Jurnal Berdaya Mandiri Vol. 7 No. 1 (2025): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v7i1.7666

Abstract

Mental health education in Z Generation still receives less attention, even though mental health disorders in adolescents can develop into serious problems if not treated early. Many students do not understand or recognize the early symptoms of mental health disorders, and there is a lack of school involvement in providing related education. Technology can be a solution to help with early detection, one of which is through the Beck Depression Inventory (BDI)-based platform from Pijar Psikologi. This activity is expected to provide an understanding of the importance of mental health and how to recognize the early symptoms of mental health disorders. Pengabdian kepada Masyarakat (PkM) activity aims to introduce early detection tools for mental health disorders for students of SMK N 02 Yogyakarta. The methods used include pre-test, socialization and dissemination of research results, the practice of using early detection platforms, and post-test. Based on the results of the comparative analysis of pre-test and post-test scores, there was an increase in participants' knowledge regarding mental health by 90%. This shows that the delivery of the material provided is effective in increasing participants' knowledge. This increase in knowledge can be the basis for students to become cadres who are directly involved in disseminating digital literacy related to the use of information technology in mental health. Keyword: mental health, mental health education, Z generation, early detection tools
Mapping User Dissatisfaction in Mobile Banking Applications Using Ensemble Clustering LDA and LSA Kusumaningtyas, Kartikadyota; Lahitani, Alfirna Rizqi; Dwijayanti, Irmma; Habibi, Muhammad
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v12i1.3804

Abstract

Mobile banking has become one of the most popular choices compared to other online banking services. Google Play Store is an online application store platform provides a review section for users to give ratings and comments on the applications they use. Positive reviews typically contain good experiences that reflect user satisfaction, while negative reviews usually contain poor experiences that indicate complaints and user dissatisfaction. However, Google Play Store does not yet have a feature to automatically map the main topics in both positive and negative reviews. Specifically for negative reviews, this can make it difficult for developers to understand the root problems and take appropriate corrective actions. In some situations, negative reviews need to be handled more quickly. Slow handling of negative reviews can impact the decline in reputation and customer loyalty. This research aims to identify user dissatisfaction topics based on negative reviews of several popular mobile banking applications in Indonesia, namely BCA Mobile and BRImo.
SMART PERPUSTAKAAN: INOVASI PENINGKATAN LITERASI SEKOLAH ANAK USIA DINI AKAR TUMBUH MELATI DI KELURAHAN SENDANGADI MLATI SLEMAN Aris Wahyu Murdiyanto; Kartikadyota Kusumaningtyas; Ikbal Rizki Putra; Septiyati Purwandari; Bara Falah Adikaputra; Agung Satria Panca; Fitriatul Hasanah
Jurnal Berdaya Mandiri Vol. 6 No. 3 (2024): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v6i3.7184

Abstract

This program aims to enhance educational services and literacy knowledge among early childhood students at Akar Tumbuh Melati School through the implementation of appropriate technology (Smart Perpustakaan). The activities were carried out in five stages: socialization, training, technology implementation, assistance, and evaluation with sustainability measures. The Smart Perpustakaan technology includes a library space, an encyclopedia book collection, virtual reality (VR) videos for interactive reading activities, and Cardboard VR devices. The results show a 92% increase in digital literacy knowledge and a 33.33% improvement in the quality of educational services. This program successfully reduced children's dependency on non-educational digital content and opened opportunities for sustainable collaboration with related stakeholders. Keyword: early childhood literacy, educational services, appropriate technology, Smart Library, community service
Tweet Analysis of Mental Illness Using K-Means Clustering and Support Vector Machine Kusumaningtyas, Kartikadyota; Habibi, Muhammad; Dwijayanti, Irmma; Sumiyarini, Retno
Telematika Vol 20 No 3 (2023): Edisi Oktober 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i3.9820

Abstract

Purpose: Social media, particularly Twitter, provides a venue for individuals to share their thoughts. The public's perception of mental illnesses is often debated on Twitter. So yet, no evaluation of community tweets connected to data on mental health conditions has been performed. The purpose of this study is to examine tweets linked to mental illnesses in Indonesia in order to identify the themes of conversation and the polarity trends of these tweets.Design/methodology/approach: To address this issue, the K-Means Clustering algorithm is utilized to aggregate tweet data that is used to find themes of conversation. The emotion polarity value of each cluster result was then determined using the Support Vector Machine (SVM) approach.Findings/results: This study generated five topic clusters based on tweets about mental illness. While sentiment analysis revealed that all clusters had more negative sentiment classes than positive. Cluster 4 and Cluster 5 had the highest number of negative sentiment values. These clusters emphasize the necessity of consulting with psychiatrists and psychologists if people have mental health disorders, as well as financing for mental health disorder treatment through BPJS Kesehatan services.Originality/value/state of the art: The analysis was done in two stages: data grouping to find themes of conversation using K-Means clustering and SVM to look for positive and negative polarity values associated to twitter data about mental illness.
Implementasi Metode ARAS dalam SPK Berbasis Web pada Pemberian Bantuan Pengembangan Desa Wisata Dwi Cahya Novita; Putri; Fajrianti, Erika M. N.; Repi, Sandika T. P.; Kusumaningtyas, Kartikadyota; Asnawi, Choerun
Jurnal Teknomatika Vol 18 No 2 (2025): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v8i2.1612

Abstract

Proses seleksi desa wisata untuk menerima bantuan Dukungan Pengembangan Usaha Pariwisata dan Ekonomi Kreatif (DPUP) dalam program Anugerah Desa Wisata Indonesia (ADWI) memiliki kompleksitas tinggi dalam menentukan desa yang tepat sasaran. Dari 6.016 desa wisata yang mendaftar pada tahun 2024, hanya 24 desa yang terpilih untuk menerima bantuan. Proses penilaian tersebut melibatkan pengelolaan data dengan banyak alternatif dan kriteria. Oleh karena itu, penelitian ini mengusulkan penerapan metode Additive Ratio Assessment (ARAS) dalam SPK yang didukung dengan RESTful API guna meminimalkan bias dan meningkatkan efisiensi pengolahan data. Penelitian ini menggunakan 15 alternatif desa wisata di Kabupaten Sleman dengan 5 kriteria penilaian yaitu Kelembagaan & SDM, Amenitas, Digital, Daya Tarik, dan Resiliensi. Hasil penelitian menunjukkan bahwa sistem mampu memberikan peringkat secara konsisten yang telah diverifikasi melalui pengujian black box dan perbandingan perhitungan manual. Berdasarkan evaluasi tersebut, Desa Wisata Tegal Loegood menduduki peringkat pertama dengan nilai 0,913 sebagai desa yang paling layak menerima bantuan. Sistem ini diharapkan membantu pemerintah dalam membuat keputusan efisien terkait pemberian bantuan pengembangan desa wisata.
Co-Authors Adri Priadana Agung Satria Panca Alfirna Rizqi Lahitani Alfun Roehatul Jannah Anas Sufi Hasan Manahingati Aris Wahyu Murdiyanto Asnawi, Choerun Ayu Dewi Nurullatifah Bara Falah Adikaputra Bayu Saputra, Andika Cahyani, Natalia Dwi Dedy Hariyadi Dwi Cahya Novita Eko Dwi Nugroho Eko Dwi Nugroho Eko Dwi Nugroho Fajrianti, Erika M. N. Fitriatul Hasanah Grita Supriyanto Dewi Irmma Dwijayanti Kharisma Lahitani, Alfirna Rizqi Mahendra Dewantoro, Septian Muhammad Habibi Muhammad Habibi Natalia Dwi Cahyani Nurul Fatimah Nurul Fatimah Nurullatifah, Ayu Dewi Puji Winar Cahyo Puji Winar Cahyo Putra, Ikbal Rizki Putri Repi, Sandika T. P. Rizqi Lahitani, Alfirna Saputra, Andika Bayu Septian Mahendra Dewantoro Septiyati Purwandari Sujono Riyadi Sumiyarini, Retno Ulfi Saidata Aesyi