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All Journal Jurnal Buana Informatika Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science (JOINTECS) JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA INOVTEK Polbeng - Seri Informatika Indonesian Journal of Information System JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik Indonesian Journal of Computing and Modeling Jurnal Informatika JUSIM (Jurnal Sistem Informasi Musirawas) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Aiti: Jurnal Teknologi Informasi Idealis : Indonesia Journal Information System Jurnal Teknik Informatika (JUTIF) Jurnal Indonesia : Manajemen Informatika dan Komunikasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Ilmiah Sains Jurnal Ilmiah Ilmu Terapan Universitas Jambi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Midang Jurnal Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi d'Cartesian: Jurnal Matematika dan Aplikasi Indonesian Journal of Intelligence Data Science (IJIDS) International Journal of Information Technology and Business JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK
Yessica Nataliani
Universitas Kristen Satya Wacana
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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Analisis Penerimaan Sistem Self-Service Kiosk McDonald's Menggunakan Technology Acceptance Model Berdasarkan Kelompok Usia Revalina Saputera; Yessica Nataliani
IDEALIS : InDonEsiA journaL Information System Vol. 9 No. 2 (2026): Jurnal IDEALIS Juli 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v9i2.3807

Abstract

The fast-food industry continues to adopt digital technology, one example being the implementation of self-service kiosks at McDonald's outlets in Bandung. Although these kiosks are intended to improve service efficiency and reduce dependence on cashiers, their acceptance by users requires further evaluation. This study examines factors influencing user acceptance of self-service kiosks using the Technology Acceptance Model (TAM) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The model comprises Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude Toward Using (ATU), and Behavioral Intention (BI), while Multi-Group Analysis (MGA) compares users aged ≤35 years and >35 years. Data were collected from 100 kiosk users in Bandung through purposive sampling. The findings indicate that PU (β = 0.314) and ATU (β = 0.596) positively and significantly affect BI, whereas PEOU influences BI indirectly through PU and ATU. The structural model explains 78.6% of the variance in behavioral intention. In addition, MGA reveals no significant differences between the two age groups. These findings suggest that age does not substantially influence user acceptance of self-service kiosks in Indonesian fast-food restaurants.
PENGENALAN GAME EDUKASI BAGI SISWA TK KRISTEN 1 SATYA WACANA SALATIGA USIA 5-6 TAHUN Anton Hermawan; Yessica Nataliani; Hindriyanto Dwi Purnomo; Erwien Christianto; Angela Atik Setyanti; Hanita Yulia; Krismiyati; Adriyanto Juliastomo Gundo; Theophilus Wellem; Hendry
Jurnal DIMASTIK Vol. 3 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i2.12302

Abstract

Kemajuan teknologi informasi dan komunikasi menuntut adanya adaptasi dalam dunia pendidikan, termasuk pada jenjang pendidikan anak usia dini. Pengenalan teknologi sejak dini menjadi langkah strategis dalam membentuk kesiapan anak menghadapi era digital. Kegiatan pengabdian ini bertujuan untuk mengenalkan teknologi, khususnya komputer, kepada siswa Taman Kanak-kanak (TK) melalui game edukasi berbasis online. Kegiatan dilaksanakan secara luring di TK Kristen 1 Satya Wacana, Salatiga, dengan melibatkan siswa berusia 5–6 tahun. Metode pelatihan dilakukan dalam beberapa sesi, mencakup pengenalan bagian-bagian komputer, penggunaan mouse, serta pelatihan melalui game edukasi seperti pengenalan huruf, angka, bentuk geometri, dan jenis-jenis kendaraan. Hasil evaluasi menunjukkan bahwa siswa menunjukkan antusiasme tinggi selama pelatihan, serta mulai mengenal komputer sebagai media pembelajaran alternatif selain perangkat yang biasa digunakan di rumah seperti handphone dan tablet. Kegiatan ini membuktikan bahwa pendekatan belajar sambil bermain dengan teknologi dapat meningkatkan minat belajar dan keterampilan dasar siswa dalam menggunakan komputer.
Clustering Performa Pemain Basket Berdasarkan Posisi dan Statistik Pemain Menggunakan Metode Fuzzy c-Means Febrianus Gregorry; Yessica Nataliani
Jurnal Transformatika Vol. 20 No. 1 (2022): July 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i1.5137

Abstract

Satya Wacana Saints Salatiga is one of the professional teams that compete in Indonesian Basketball League (IBL). Player evaluation has been done as an effort to maintain the quality and performance of all players which can be used as team records. They can also make a couple of improvements within the team for the next season. Classifying the players performance by using the fuzzy c-means algorithm is the aim of this research. Player performance is determined based on five kinds of player statistical criteria, namely points, assists, blocks, rebounds, and steals from each position. The assessment carried out in this study is using weighting criteria for each position. The grouping by weighting aims to get the highest to the lowest scores from each player so that they can be grouped into three performance groups; good, moderate, and poor performance. The results of the fuzzy c-means grouping of 15 players of the Satya Wacana Saints Salatiga team with weighting obtained three players with good performance, five players with moderate performance, and seven players with poor performance. Meanwhile, the results of the fuzzy c-means grouping without weighting obtained five players with good performance, three players with moderate performance, and seven players with poor performance. Both grouping results are compared with the actual performance data. The result of the comparison was found that the grouping with weighting resulted in an accuracy rate of 100% and the grouping without weighting resulted in an accuracy rate of 86.67%. Grouping with weighting on different statistical values for each player position has an effect on player performance. Each player position has different strengths in scoring points, assists, rebounds, steals, block shoots, and field goals.
Analisis Loyalitas Customer Perusahaan Konveksi dengan Model RFM dan Algoritma k-Means Matthew Gerian; Yessica Nataliani
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.v21i2.7248

Abstract

Strategi yang baik diperlukan suatu perusahaan dalam menjalankan usahanya. CV. Karunia Jaya merupakan salah satu perusahaan yang bergerak dalam bidang konveksi yanag menjual pakaian bayi. Dalam pelayanan terhadap customer CV. Karunia Jaya belum menerapkan strategi Customer Relationship Management (CRM). Untuk mengetahui loyalitas customer maka perlu dilakukan segmentasi pelanggan terhadap customer. Penelitian ini menggunakan data transaksi dari tahun 2021-2022. Algoritma k-means digunakan dalam penentuan cluster berdasarkan model Recency, Frequency, dan Moneetary (RFM), dibantu dengan tools Weka 3.8.6. Metode elbow digunakan untuk mencari jumlah cluster terbaik dari sekelompok data. Hasil dari penelitian ini yaitu terdapat 27 customer yang terbagi dalam tiga cluster, 21 customer potensi rendah, tiga customer potensi sedang, dan tiga customer potensi tinggi. Perusahaan dapat memberikan layanan yang berbeda terhadap setiap kelompok customer, sehingga hal tersebut dapat menguntungkan perusahaan.
STIMULASI NUMERASI PRAKONSEPTUAL ANAK USIA 4–5 TAHUN MELALUI GAME BERBASIS WEB UNTUK PENGENALAN JUMLAH DAN POLA BILANGAN Willson Mangoki; Anton Hermawan; Krismiyati; Hanita Yulia; Adriyanto Juliastomo Gundo; Rissal Efendi; Angela Atik Setiyanti; Charitas Fibriani; Yessica Nataliani; Erwien Christianto; Indrastanti Ratna Widiasari; Theophilus Wellem; Hendry; Dian Widiyanto Chandra; Danny Manongga
Jurnal DIMASTIK Vol. 4 No. 2 (2026): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v4i2.14113

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengenalkan konsep numerasi awal kepada anak usia 4–5 tahun melalui game berbasis web. Kegiatan dilaksanakan di TK Kristen 1 Satya Wacana Salatiga melalui tiga tahapan, yaitu persiapan, pelaksanaan, dan evaluasi. Tahap pelaksanaan dilakukan dalam dua sesi, yaitu pengenalan perangkat komputer dan pembelajaran numerasi menggunakan game berbasis web seperti Color by Number, Find the Number, Number Matching, Complete the Missing Number, dan Connect the Dots. Evaluasi dilakukan secara observasional dengan fokus pada keterlibatan anak, pengenalan perangkat komputer, dan pemahaman numerasi. Hasil menunjukkan bahwa anak memiliki antusiasme tinggi, mengenal perangkat komputer secara terbatas, serta lebih mudah memahami konsep angka melalui pendekatan gamifikasi. Pendampingan oleh guru dan mahasiswa berperan penting dalam keberhasilan kegiatan.
Analisis faktor penerimaan pengguna terhadap adopsi Artificial Intelligence di Perguruan Tinggi melalui Extended UTAUT2 Jessica Nathania Kho; Hindriyanto Dwi Purnomo; Yessica Nataliani
AITI Vol 23 No 3 (2026)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v23i3.449-464

Abstract

Artificial Intelligence (AI) has increasingly been used to support scientific writing, offering various benefits while simultaneously raising ethical challenges for higher education institutions. This situation highlights the need for targeted AI integration based on a comprehensive understanding of students’ acceptance and actual use. This study investigates the factors influencing users’ acceptance and actual use of AI in research and scientific writing using the Extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework and Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected through a survey of 129 respondents from the Faculty of Information Technology, Satya Wacana Christian University (SWCU). The results indicate that Trust has the strongest influence on Behavioral Intention, followed by Habit and Social Influence. Meanwhile, Habit is the strongest predictor of Use Behavior, whereas Facilitating Conditions and Behavioral Intention do not significantly influence actual use. These findings provide evidence of an Intention–Behavior Gap, suggesting that actual AI use in scientific writing is influenced more strongly by established usage habits than by conscious behavioral intentions alone.
Sentiment Analysis of Healthcare Services at RSUD Soe Using Machine Learning and Latent Dirichlet Allocation Agatha Marilin Saekoko; Hindriyanto Dwi Purnomo; Yessica Nataliani
Jurnal Ilmiah Sains Vol. 26 No. 1 (2026): Issue November 2025 - April 2026
Publisher : Sam Ratulangi University, Manado, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/jis.v26i1.67193

Abstract

Healthcare services constitute a crucial aspect in improving public well-being. Every individual has the right to receive healthcare services that are of high quality, safe, efficient, and affordable. This study aims to identify and analyze public perceptions and sentiments toward healthcare services at RSUD Soe, as well as to evaluate the performance of several machine learning methods in classifying such sentiments. The data were collected from 278 respondents through a Likert-scale questionnaire that represents perceptions and levels of satisfaction regarding various service aspects. Sentiment analysis was conducted using four machine learning algorithms, namely Naïve Bayes, C4.5, Random Forest, and Support Vector Machine. The results indicate that Naïve Bayes achieved the highest accuracy of 82.14 percent, followed by SVM at 80 percent, Random Forest at 79 percent, and C4.5 at 73.21 percent. This study also applied the Latent Dirichlet Allocation (LDA) method to identify the main themes within public feedback. LDA generated twelve topics reflecting key issues such as waiting time, availability of medical personnel, facility cleanliness, and the attitudes of healthcare staff. The majority of comments exhibited positive sentiment, particularly concerning staff friendliness and service quality. These findings were used to formulate improvement recommendations, including enhancing service quality, increasing the number of medical personnel, and optimizing facilities. This research demonstrates that a data-driven quantitative approach is effective in evaluating healthcare service quality and supporting more targeted decision-making. The results are expected to assist RSUD Soe in continuously and effectively improving service quality.
ANALISIS SENTIMEN PENGGUNA APLIKASI SHOPEE BERBASIS LONG SHORT-TERM MEMORY (LSTM) DAN WORD EMBEDDING Whigi Tantriya Putri; Yessica Nataliani
JURNAL INFORMATIKA DAN KOMPUTER Vol 10, No 3 (2026): Oktober 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v10i3.2742

Abstract

Dalam era digital saat ini, aplikasi mobile telah menjadi bagian utama dalam kehidupan sehari-hari yang mendukung berbagai aktivitas, seperti belanja, hiburan, dan komunikasi. Salah satu sektor yang berkembang pesat adalah e-commerce, dimana Shopee merupakan salah satu platform yang populer dan banyak digunakan oleh masyarakat Indonesia. Penelitian ini bertujuan menganalisis sentimen ulasan pengguna aplikasi Shopee menggunakan metode Word2Vec dan Long Short-Term Memory (LSTM). Data yang digunakan sebanyak 6.000 ulasan berbahasa Indonesia yang dikumpulkan melalui web scraping dari Google Play Store. Proses dilanjutkan melalui tahapan cleaning text, case folding, slang normalization, penghapusan kata duplikat, stopword removal, dan stemming. Data kemudian diberi label sentimen positif, negatif, dan netral menggunakan Inset Lexicon. Model LSTM menghasilkan akurasi sebesar 85,08%, precision 84,08%, recall 85,08%, dan F1-score 84,18%. Performa terbaik pada sentimen positif, namun masih terdapat kesalahan pada sentimen negatif dan netral akibat ketidakseimbangan data. Hasil ini menunjukkan bahwa Word2Vec dan LSTM dapat digunakan pada analisis sentimen ulasan aplikasi e-commerce terutama dalam mengklasifikasi sentimen positif.
Co-Authors Ade Iriani Adriyanto Juliastomo Gundo Advensius Natalis Agatha Marilin Saekoko Agustinus Fritz Wijaya Alberaldo Difra Gunawan Aldi Herindra Lasso Alexander Franklyn Alwin Adi Putra Andree Eka Putra Angela Atik Setiyanti Angela Atik Setyanti Anissa Enggar Pramitasari Anton Hermawan Anton Hermawan Antoni Erga Arthur, Christian Axsana, Samuel Richard Bryan Adha Elang Praditya Cahyaningtyas, Christian Chandra, Dian W. Charitas Fibriani Chrisanty Mariana Rorimpandey Daniel D. Kameo Danny Manongga Darmawan Utomo Deinard Yordan Sihombing Dian Widiyanto Chandra Diwa Oktario Dacwanda Edi Suharyadi Eko Sediyono Elizabeth Sri Lestari Erdi Amos Saputra Ering, Anatasya Lingkanwene Erwien Christianto Ester Gea Evi Maria Febrianus Gregorry Francesco Totti Samuelly Gigih Prima Subakti Gilang Jonathan Phita Hanita Yulia Hapsari, Theresia Shinta Hendry Hindriyanto Dwi Purnomo Hindriyanto Dwi Purnomo Hui-Ming Wee Imanuel Susanto Indrastanti Ratna Widiasari Irwan Sembiring Ivanna K. Timotius Jessica Nathania Kho Jessica Widyadhana Iskandar Kirono, Aryo Sasi Krismiyati Kristoko Dwi Hartomo Leony Martiyana Putri Lorna Yertas Baisa Marchelino Nathanael Maria Feby Tri Martin Martin Mas Kahono Alif Bintang Firmansyah Matthew Gerian Merryana Lestari Michael Jonathan Mramra , Welianus Yohanes Yehuda Mulyono, Andronikus Natalis, Advensius Penidas Fodinggo Tanaem Prandiska, Kelvin Putra, Andree Eka Rama Tri Budi Ardianto Revalina Saputera Rissal Efendi Samuel Wijayadi Sugiharto Sanjaya, Rian Sediatmoko, Nur Siradj Setyanti, Angela Atik Sugiarto, Adrian Herma Suharyadi Suryady, Irwan Tambunan, Shanto Moyrano Theophilus Wellem Tigar Cahyo Wiguno Tintien Koerniawati Vigo Yano Sahertian Wahab, Nur Haliza Abdul Whigi Tantriya Putri Willson Mangoki Willy Thomas Winsy C.D Weku Yuda Novianto Yuliana Tien Bayangkhariwati Tacoh