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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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PELATIHAN KOMPUTER UNTUK SISWA TK KRISTEN 1 SATYA WACANA SALATIGA MELALUI PERMAINAN EDUKASI ONLINE Yessica Nataliani; Krismiyati Krismiyati; Erwien Christianto; Theophilus Wellem; Anton Hermawan; Agustinus Fritz Wijaya; Imanuel Susanto
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2023)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v3i32023p405-416

Abstract

This community service activity was carried out to facilitate the needs of the Satya Wacana Christian 1 Kindergarten students in Salatiga as an effort to introduce kindergarten students to computers. Students usually only know cell phones or tablets but rarely use computers. This training activity was attended by kindergarten students with an age range of 5-6 years and was carried out in four stages, namely the planning stage, the preparation stage, the implementation stage, and the evaluation stage. The activity involved a team of lecturers from the Faculty of Information Technology, Satya Wacana Christian University as activity facilitators and three teachers from Satya Wacana Christian 1 Kindergarten. This program was conducted at the Computer Laboratory of the Faculty of Information Technology, Satya Wacana Christian University, which included introducing computer equipment, opening websites, and practicing using a mouse through online educational games. The online educational games used in this activity are mixing colors, counting, getting to know water transportation, getting to know 2D shapes, knowing numbers, and assembling puzzles. The activity went well, where the students could recognize and operate computers, especially using the mouse, and learn through the online educational games.
Analisis Klasterisasi Kerawanan Gempa Bumi di Provinsi Papua Menggunakan Algoritma Invasive Weed Optimization (IWO) Lorna Yertas Baisa; Danny Manongga; Yessica Nataliani
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.65312

Abstract

Gempa bumi adalah fenomena alam yang sering terjadi di Indonesia, termasuk di Provinsi Papua. Untuk mengurangi risiko dampak gempa bumi, diperlukan analisis untuk mengidentifikasi daerah-daerah yang rawan terha  dap gempa bumi. Penelitian ini bertujuan untuk menganalisis klasterisasi kerawanan gempa di Provinsi Papua menggunakan algoritma Invasive Weed Optimization (IWO). Metode ini dipilih karena dapat menghasilkan klaster yang lebih baik dibandingkan dengan algoritma klasterisasi lainnya. Data yang digunakan adalah data kejadian gempa di Provinsi Papua yang terdiri dari atribut latitude, longitude, magnitude, dan depth mulai tahun 2018 sampai Februari 2023 yang diperoleh dari website Badan Geologi Amerika Serikat yaitu United States Geological Survey (USGS). Tahapan penelitian meliputi normalisasi data, klasterisasi menggunakan algoritma IWO, dan evaluasi hasil klasterisasi menggunakan SSE dan F-Measure. Jumlah klaster terbaik yang dihasilkan oleh metode Elbow yaitu sebanyak enam klaster kerawanan gempa di Provinsi Papua, yang diberi label Sangat Tidak Rawan, Tidak Rawan, Kurang Rawan, Cukup Rawan, Rawan dan Sangat Rawan. Dengan nilai parameter sinitial sebesar 8, algoritma IWO menghasilkan nilai SSE dan F-Measure terkecil dibanding nilai parameter sinitial lainnya, yaitu masing-masing sebesar 19.1002 dan 0.5137. Evaluasi hasil klasterisasi menggunakan SSE menunjukkan nilai yang baik dari 30 kali percobaan, dengan rata-rata SSE sebesar 19.218, lebih kecil dibanding dengan rata-rata SSE hasil metode k­-Means dan DBSCAN yaitu masing-masing sebesar 19.307 dan 59.910.
ANALISIS JARINGAN SOSIAL PENGGUNA TWITTER DALAM SKEMA PENYEDIAAN LAPTOP BAGI TOKO KOMPUTER Rama Tri Budi Ardianto; Yessica Nataliani
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 2 No 3 (2023): IT-Explore Oktober 2023
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v2i3.2023.pp208-218

Abstract

Twitter is a social media that provides information for its users. Interactions on Twitter may increase the amount of data from its users. Business development cannot be separated from product competition between business actors. One way for companies to win the competition is to know the purchasing power of customers. A product's selling power can be known one way or another through user interaction on Twitter. User-generated content (UGC) results from data on Twitter. UGC data can be used to determine the product supply scheme taken by laptop products in this study. The method used to analyze the interaction is Social Network Analysis (SNA) by comparing the properties of the network. Social network modeling on UGC data was carried out on three laptops: Lenovo v14, Asus ZenBook S, and Acer Swift 3. From the graph visualization, it was found that Acer excels in two properties, namely "Size" and "Average Degree." Meanwhile, the Asus ZenBook S dominates the "Modularity" property.
Analisis Sentimen Penilaian Masyarakat Indonesia terhadap GeNose pada Komentar Youtube Menggunakan Metode Naïve Bayes Michael Jonathan; Yessica Nataliani
d\'Cartesian: Jurnal Matematika dan Aplikasi Vol 11, No 1 (2022) Maret 2022
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/dc.11.1.2022.38339

Abstract

Saat ini dunia sedang menghadapi virus yang benar-benar mematikan yaitu  COVID-19 karena virus ini menyebar dengan sangat cepat dan menyerang paru-paru. Banyak orang yang meninggal dunia dikarenakan sulit untuk bernafas. Khususnya di Indonesia, banyak masyarakat Indonesia yang terkena COVID-19 dan banyak yang sampai meninggal dunia. Banyak daerah yang ditetapkan sebagai zona merah yang menandakan bahwa daerah tersebut beresiko tinggi. Oleh karena itu universitas berbondong-bondong untuk menciptakan alat yang dapat meminimalisir penyebaran COVID-19. Salah satunya adalah Universitas Gadjah Mada (UGM) yang menciptakan alat yang dapat mendeteksi COVID-19 yaitu GeNose. Masyarakat memiliki beberapa argumen pro dan kontra dengan adanya GeNose. Untuk itu diperlukan penelitian untuk mengetahui apakah GeNose dapat berguna terhadap masyarakat Indonesia dalam meminimalisir virus tersebut atau tidak. Penelitian dilakukan menggunakan metode Naïve Bayes. Hasil klasifikasi menghasilkan accuracy mencapai 90.70% dengan kategori komentar bersifat negatif. Nilai recall sebesar 87.60% dan precision sebesar 93.39%. Data tersebut membuktikan bahwa GeNose kurang maksimal dalam meminimalisir COVID-19.
PENGEMBANGAN PERPUSTAKAAN SEKOLAH ANAK TERANG BETHANY SALATIGA Suharyadi, Suharyadi; Koerniawati, Tintien; Gundo, Adriyanto Juliastomo; Sembiring, Irwan; Wellem, Theophilus; Nataliani, Yessica
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2023)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v4i22023p196-206

Abstract

Perpustakaan sekolah dibangun oleh komponen sarana prasarana perpustakaan, pengelola peprustakaan dan kepala sekolah. Perpustakaan Sekolah Anak Terang Bethany Salatiga, membutuhkan sentuhan pengelolaan perpustakan secara profesional serta penerapan Teknologi Informasi. Program pengabdian masyarakat yang dilakukan bertujuan untuk mengatasi permasalahan Sumber Daya Manusia dengan memberikan pelatihan klasifikasi pustaka dan pelatihan pengelolaan perpustakaan berbasis Teknologi Informasi dengan penerapan SLiMS (Senayan Lybrary Management System). Hasil dari program ini Perpustakaan Sekolah Anak Terang Bethany Salatiga lebih mudah dalam penelusuran dan pengelolaan pustaka serta kemudahan anak-anak didik dalam mengakses buku-buku perpustakaan.
Sentiment Analysis of Customer Review Using Classification Algorithms and SMOTE for Handling Imbalanced Class Sediatmoko, Nur Siradj; Nataliani, Yessica; Suryady, Irwan
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.8879

Abstract

Ralali.com is a B2B e-commerce platform that offers various brands across categories ranging from automotive to building materials. The Play Store is a tool for downloading applications used by many people. This research aims to compare and find the best model among Naïve Bayes (NB), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN) in classifying the sentiment reviews of Ralali.com's application on the Play Store, and analyze the negative labels to provide recommendations for Ralali.com developers. Based on the research results, the NB Algorithm stands out as the best choice compared to SVM and k-NN in addressing class imbalance. The use of SMOTE generally improves the model performance on minority classes for Precision, Recall, and F-Measure, although there are still challenges related to the lower Accuracy compared to the use of non-SMOTE.
ANALISIS KUALITAS LAYANAN WEBSITE DISDUKCAPIL KABUPATEN SEMARANG DIUKUR MENGGUNAKAN INSTRUMEN WEBQUAL 4.0 Putra, Andree Eka; Nataliani, Yessica
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 3 (2023): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i3.292

Abstract

The Department of Population and Civil Registration organizes and publishes all matters relating to population. The existence of a service information system is a method used by Disdukcapil Semarang Regency to implement e-government, namely through the website http://dukcapil.semarangkab.go.id. Testing is needed for website user satisfaction using Webqual 4.0 as a website quality assessment instrument. The goal of this study is to get an overview of the influence/impact of the three website quality dimensions: usability, information, and service interaction qualities on user satisfaction. This study used 60 data tested by validity, reliability, multiple linear regression, t-test, and F-test. The results showed that the usability and information qualities affects user satisfaction, but the service interaction quality does not. In addition, the research found that the three dimensions of website quality together did not affect user satisfaction. They affect 39.2% of user satisfaction, while other factors outside the variables studied influence the other 60.8%.
Penerapan Metode Design Thinking Pada Perancangan UI/UX Website Gereja di Gereja GMIM Nimahesaan Pinaras Ering, Anatasya Lingkanwene; Nataliani, Yessica
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i2.756

Abstract

The GMIM Nimahesaan Pinaras Church has not optimally utilized information technology to support church services. Until now, all information has been limited to WhatsApp groups or reading congregational news. From these problems, a solution is provided to design and develop the UI/UX of the church website related to worship and church finances. This website's UI/UX design uses the design thinking method in five stages: Empathize, define, ideate, prototype, and test. Test results using the System Usability Scale (SUS) by assessing feasibility, convenience, and system constraints. The success of UI/UX design can be measured with a minimum score of 70%. The final results of testing with the System Usability Scale (SUS) model on the church website system produced a SUS score of 75.75% and was classified in category B, which means GOOD. Therefore, this design was successful.
Perbandingan Algoritma Machine Learning dalam Analisis Penyebab Penyakit Gagal Jantung Kirono, Aryo Sasi; Nataliani, Yessica
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 2 (2024): Volume 10 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i2.78369

Abstract

Penyakit gagal jantung meningkat seiring perkembangan jaman dikarenakan maraknya pola hidup yang tidak sehat, tingkat obesitas, dan angka perokok. Gagal jantung adalah kondisi medis yang abnormal pada struktur atau fungsi jantung. Gejala yang biasa dialami oleh penderita meliputi sesak nafas, kelelahan, dan penurunan tingkat aktivitas. Kemajuan teknologi yang sangat pesat dapat membantu dalam menganalisis penyebab penyakit gagal jantung, salah satunya teknologi machine learning yang mampu dalam memprediksi dan mengklasifikasi pasien yang beresiko gagal jantung dan normal. Penelitian ini menggunakan tiga model machine learning dalam analisis penyakit gagal jantung yaitu Decision Tree, Random Forest, dan XGBoost Ketiga model ini sama "“ sama memiliki fitur yang dapat diterapkan untuk mengetahui penyebab penyakit gagal jantung yaitu feature importance atau tingkat kepentingan karena termasuk dalam tree based model. Data yang digunakan dalam penelitian berjumlah 918 pasien gagal jantung. Dengan menerapkan fitur tersebut, ketiga model menghasilkan ST Slope yaitu kemiringan naik dan turun ST saat berolahraga menjadi variabel tertinggi terhadap resiko penyakit gagal jantung dengan 39% pada model Decision Tree, 22% pada model Random Forest, dan 46% pada XGBoost.
Analisis Penerimaan Masyarakat Kota Salatiga terhadap Fintech ShopeePay dengan Technology Acceptance Model Alwin Adi Putra; Yessica Nataliani
Indonesian Journal of Intelligence Data Science Vol 2 No 1 (2023): Volume 2 No. 1 2023
Publisher : Faculty of Mathematics and Natural Sciences Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Online shopping has become increasingly popular for many people in Indonesia since the Covid-19 pandemic took hold. Shopee is one of the most popular online buying and selling applications. Based on a survey conducted by App Annie, Shopee has been named the most popular marketplace in Indonesia regarding the number of active users and the volume of monthly visits. Shopee has a fintech called Shopeepay. Technology Acceptance Model (TAM) was used to analyze user acceptance during the Covid-19 pandemic. 100 ShopeePay users were taken as a sample using a purposive sampling technique, collected by questionnaire. Determination of the number of samples refers to the number of samples used in previous studies relevant to this research. The analytical techniques used in this study include regression analysis (simple and multiple) and path analysis. The analysis results from the Technology Acceptance Model show that the factors influencing the acceptance of ShopeePay fintech during the Covid-19 pandemic in Salatiga were Perceived Usefulness and Perceived Ease of Use. These two perceptions of TAM influence Attitude toward Using and Behavioral Intention to Use, which impacts Shopeepay's Actual System Usage during the Covid-19 pandemic.
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