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All Journal snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Proceedings of KNASTIK Semantik Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik JSI: Jurnal Sistem Informasi (E-Journal) Jurnal SOLMA Jurnal Ilmiah Matrik JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Progresif: Jurnal Ilmiah Komputer Zonasi: Jurnal Sistem Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Sistem Informasi dan Sains Teknologi MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknimedia: Teknologi Informasi dan Multimedia CITIZEN: Jurnal Ilmiah Mulitidisiplin Indonesia Jurnal Abdimas Musi Charitas Jurnal Sistem Informasi JSITP JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Jurnal Ilmiah Sistem Informasi MDP Student Conference Jurnal Sistem Informasi Journal Of Informatics And Busisnes Jurnal TEFSIN ( Jurnal Teknik Informatika dan Sistem Informasi) Scientica: Jurnal Ilmiah Sains dan Teknologi Jurnal Ilmiah Computer Science Masterpiece: Journal of Islamic Studies and Social Sciences Journal of Technology and System Information Jurnal Riset Teknik Komputer Jurnal Sains Sistem Informasi Jurnal Riset Sistem Informasi Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi Jurnal Sains dan Teknologi Jurnal Ilmu Komputer dan Informatika Jurnal Riset Multidisiplin Edukasi Sinergi : Jurnal Ilmiah Multidisiplin INTECH - Informatika Dan Teknologi
Andri Wijaya
Universitas Katolik Musi Charitas
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Perbandingan Algoritma Naïve Bayes Dan Support Vector Machine Dalam Menentukan Sentimen Publik Terhadap Copilot Agustio Dwitama; Meilinda, Meilinda; Julian Masidin, Nevin; Wijaya, Andri
Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi Vol. 3 No. 1 (2025): Januari
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/jsimtek.v3i1.800

Abstract

Chatbot modern, termasuk Copilot dari Microsoft Edge, berkembang pesat berkat teknologi pemrosesan bahasa alami (NLP). Penelitian ini menganalisis sentimen publik terhadap Copilot menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM). Dengan mengumpulkan 20.000 ulasan dari Google Play Store melalui library Python “google_play_scraper”, data diproses dengan langkah-langkah preprocessing, diikuti pelabelan menggunakan VADER untuk mengklasifikasikan ulasan menjadi positif, negatif, dan netral. Metode TF-IDF digunakan untuk mengindeks dan memberikan bobot pada istilah sebelum menerapkan model pencarian berbasis vektor. Hasil evaluasi menunjukkan SVM unggul dibandingkan Naïve Bayes dalam akurasi (96,54% vs 90,32%), precision, recall, dan F1-score, terutama dalam mendeteksi ulasan negatif. Word Cloud analisis menunjukkan kata kunci positif dominan seperti "app" dan "good", mencerminkan persepsi pengguna yang baik terhadap Copilot. Penelitian ini merekomendasikan pengoptimalan lebih lanjut untuk Naïve Bayes dan menegaskan bahwa SVM adalah pilihan lebih baik untuk analisis sentimen kompleks.
Penggunaan Machine Learning (ML) dan Natural Language Processing (NLP) untuk mendeteksi Sentimen Ancaman Siber Wijaya, Andri; Putra, Steven Adi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 1 (2025): Maret
Publisher : Universitas Wahid Hasyim

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

Abstract

Cybersecurity has become a critical issue in the digital era, with evidence in the last 3 years there have been 6 cybercrime cases in Indonesia that attacked servers, one of which was the latest theft of Bank Syariah Indonesia data in May which resulted in the server being paralyzed for 5 days and the impact was that customers could not access the mobile banking application. From the various cybercrime cases that have occurred in Indonesia, we need to know the current trend of public sentiment about it and one of the sources of public sentiment is Twitter. The use of Machine Learning (ML) and Natural Language Processing (NLP) has become a major focus in understanding public sentiment contained in twitter data. This research proposes an approach that combines ML and NLP techniques to detect sentiment in tweets. The method includes a pre-processing stage to clean and transform the tweet text into a vector representation, followed by the application of ML classification model namely Naïve Bayes to identify positive, negative or neutral sentiments from the tweet dataset. This research utilizes a set of collected and annotated tweet data using python to train and test the model. The experimental results show that the proposed approach successfully produces sentiment classification with an accuracy rate of 62%. It can be concluded that the accuracy of the model is still satisfactory with a positive recall value of 74%, meaning that the public sentiment of the tweets still contains words of a positive nature.
Perencanaan Strategis Sistem Informasi pada Perusahaan XYZ di Palembang Masidin, Nevin Julian; Meilinda, Meilinda; Dwitama, Agustio; Wijaya, Andri
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11186

Abstract

Information system strategic planning is an important step in supporting business sustainability and growth, especially in today's digital era. XYZ Company in Palembang faces challenges in managing information systems, such as less than optimal data security, high manual usage (paper recording) in operations, and suboptimal use of data to support strategic decision making that can hinder efficiency and competitiveness. This study aims to develop an integrated information system strategy using the Ward and Peppard method, as well as SWOT and PESTLE analysis to evaluate the internal and external environment. The results of the analysis indicate the need to increase the use of digital technology for operational transformation and data-based decision making. So that this study can provide solutions for companies in utilizing information systems to improve efficiency, innovation, and competitiveness in the industry.
Analisis Sentimen Film Squid Game Melalui Platform X Menggunakan Metode Lexicon Based Anggoro, Deo; Alessandro, Andreas; Aditya, Putra; Wijaya, Andri
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11197

Abstract

This study discusses the role of movies as a medium in conveying social and emotional messages, with a focus on the Squid Game series. This research applies Lexicon-Based sentiment analysis to evaluate audience reactions to the series using 10,000 tweets from Twitter (X). The results of the analysis showed that 36.3% of the comments had a positive sentiment, 46.4% were neutral, and 17.2% were negative. The majority of neutral sentiment indicates that many viewers were interested but did not have strong opinions, while the significant positive sentiment indicates a favorable reception to the movie. These results provide insight into how audiences responded to the themes of economic inequality and social oppression in the movie. This analysis highlights the relevance of sentiment analysis in understanding audience responses to social issues, as well as how films can reflect deeper cultural and social issues.
ANALISIS SENTIMEN ULASAN PENGGUNA GAME SIMULATOR TOKO SUPERMARKET PADA GOOGLE PLAYSTORE Sugiarti, Sabar; Pamungkas, Martinus Ponco; Adtiya, Setenilaus; Wijaya, Andri
Jurnal Sains Sistem Informasi Vol 3, No 2 (2025): JSSI (Mei)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jssi.v3i2.18053

Abstract

Pengembangan game daring semakin pesat dan mencakup berbagai genre yang menarik bagi pengguna. Supermarket Shop Simulator adalah game yang sangat digemari dan tersedia di Google Play Store. Tujuan dari penelitian ini adalah untuk menerapkan metode Naïve Bayes guna menganalisis sentimen ulasan pengguna terhadap game tersebut. Metode web scraping digunakan untuk mengumpulkan data dari Google Play Store, dan langkah-langkah praproses seperti pembersihan, normalisasi, penghapusan stopword, tokenisasi, dan stemming digunakan untuk menganalisis data. Metrik untuk mengingat, akurasi, dan presisi digunakan untuk menilai model yang dikembangkan. Temuan analisis menunjukkan bahwa pendekatan Naïve Bayes memiliki akurasi klasifikasi sentimen sebesar 78%. Menurut data word cloud, istilah "iklan", "game", "bagus", "menyenangkan", dan "bermain" sering ditemukan dalam ulasan pengguna. Diharapkan bahwa penelitian ini akan membantu pengembang dalam memahami reaksi pelanggan dan meningkatkan kualitas game di masa mendatang.
Pemetaan Tata Kelola IT Menggunakan Standarisasi Cobit 4.1 (Studi Kasus UKMC Palembang) Simbolon, Defrianti; Wijaya, Andri
MEANS (Media Informasi Analisa dan Sistem) Volume 4 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.245 KB) | DOI: 10.54367/means.v4i1.496

Abstract

COBIT 4.1 is a standardization of framework mapping using a balanced scorecard that aims to implement information technology governance performance in UKMC. Information technology carried out in UKMC must be monitored and managed properly so as to avoid problems such as disrupted data security, data leakage, and organizational losses. Identification results obtained from COBIT 4.1 mapping obtained 21 sub domain processes that must be applied in UKMC such as PO (PO1, PO2, PO4, PO8, PO10), AI (AI, AI2, AI4, AI6, AI7), DS (DS1, DS2 , DS3, DS4 DS5, DS7, DS8, DS10, DS13), and ME (ME1, ME2). The sub domain of the process must be implemented and implemented in UKMC to support the achievement of the realization of good university governance and ensure that the information technology system that has been implemented in UKMC is aligned with the organization's goals so that the vision and mission of KSITK will run effectively and efficiently for UKMC development
Penggunaan Technology Acceptance Model (TAM) 3 Untuk Mengukur Tingkat Penerimaan Aplikasi Threads Pada Kalangan Remaja Dwitama, Agustio; Wijaya, Andri
Jurnal Sistem Informasi dan Sains Teknologi Vol 7, No 2 (2025): Jurnal Sistem Informasi dan Sains Teknologi
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/sistek.v7i2.2286

Abstract

Perkembangan teknologi informasi yang pesat telah mendorong lahirnya berbagai aplikasi media sosial baru, salah satunya adalah Threads yang dikembangkan oleh Meta. Threads menarik perhatian kalangan remaja, namun menghadapi kendala teknis seperti bug, error, crash, algoritma tidak relevan, notifikasi spam, dan batasan karakter, yang dapat mempengaruhi penerimaan pengguna. Tujuan dari penelitian ini untuk menganalisis tingkat penerimaan aplikasi Threads di kalangan remaja di kota Palembang dengan menggunakan pendekatan TAM 3. Data dikumpulkan melalui kuesioner online terhadap 100 responden yang ditentukan dengan teknik purposive sampling, dan dianalisis menggunakan metode Partial Least Square - Structural Equation Modeling (PLS-SEM) dengan bantuan software SmartPLS 4. Hasil penelitian menunjukkan bahwa dari total 19 hipotesis yang diuji, sebanyak 12 hipotesis dinyatakan berpengaruh signifikan (p-value < 0,05) dan 7 hipotesis tidak signifikan (p-value ≥ 0,05). Faktor yang terbukti berpengaruh signifikan dalam penerimaan aplikasi Threads adalah Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Behavioral Intention (BI), Subjective Norm (SN), Computer Self-Efficacy (CSE), Computer Playfulness (CP), Output Quality (OQ), dan Voluntariness (VOL). Temuan ini diharapkan dapat memberikan pemahaman lebih mendalam penerimaan aplikasi Threads pada kalangan remaja.
IMPLEMENTASI PENDEKATAN AGILE UNTUK PENGEMBANGAN OLAP DATA PENJUALAN Wijaya, Andri; Maharani, Mutia; Meilinda
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 1 (2024): Publikasi Artikel ZONAsi Periode Januari 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i1.17337

Abstract

Sales data in large quantities are difficult to process and report using Microsoft Excel, which takes a long time. The proposed solution is to use Online Analytical Processing, a method that allows for faster decision-making through multidimensional data manipulation. In developing Online Analytical Processing for sales data, an agile approach is applied. With Online Analytical Processing, access to and display of transactional data becomes more efficient, improving analysis quality and supporting management decisions. Research results show that the prototype accelerates sales reports with a response time of 0.0039 seconds. Online Analytical Processing also facilitates decision-making in seconds. User Acceptance Testing results show high software quality and performance (100%), with an overall evaluation of 86,67% categorized as “Very Good”. Keywords: Sales Data, Online Analytical Processing, User Acceptance Testing, Agile Development
ANALISIS SENTIMEN ULASAN APLIKASI SHAZAM DI GOOGLE PLAY STORE MENGGUNAKAN SUPPORT VECTOR MACHINE Wijaya, Andri; Meilinda; Maharani, Mutia
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 1 (2024): Publikasi Artikel ZONAsi Periode Januari 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i1.17994

Abstract

Shazam is a popular music recognition app on the Google Play Store. Shazam allows users to discover new songs and identify songs that are playing around them. In addition, it provides song lyrics, music videos, and song recommendations. User reviews give an idea of how users perceive the application, be it positive or negative. In this study, sentiment analysis was conducted on Shazam user reviews on the Google Play Store. The researchers used a Support Vector Machine (SVM) model to classify user reviews into two sentiments, namely positive and negative. Results show that SVM has 84% accuracy in predicting the sentiment of Shazam reviews. Furthermore, it can be shown that Shazam gets five times more positive responses than negative responses. Therefore, SVM is better at predicting positive reviews than negative reviews. This research can help interested parties to understand how users perceive the app as a whole.
Pemanfaatan teknologi sudah dilakukan di banyak bidang kehidupan seperti sudah banyaknya aplikasi baik berbasis website ataupun android yang menjadi sahabat bagi semua lapisan masyarakat. Sebagian besar masyarakat hanya dapat menggunakan teknologi tersebu Maria Bellaniar; Andayani, Sri; Wijaya, Andri; Hermawan, Latius
Jurnal Abdimas Musi Charitas Vol. 5 No. 1 (2021): Jurnal Abdimas Musi Charitas Vol. 5 No. 1, Juni 2021
Publisher : Universitas katolik Musi Charitas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (482.73 KB)

Abstract

The use of technology has been carried out in many areas of life as has been the number of applications based on both websites or android that are friends to all society. Most of the people can only use this technology and a small part of others not only can use but also can make this technology with the help of a programming tool. Self-programming can made with a native concept or the concept of OOP (Object Oriented Programming). Lots of programmers can program with native concepts but not many programmerswho can create programs with the OOP concept. Apart from programmers, there are many students who do not understand the concept of OOP let alone to make it in form a website. Like it or not, these students have to take part in the workshop training on OOP so that knowledge in the IT field can improve. Based on the problem That is, the lecturer service team held a service on Object Training Oriented Programming in Today's Website Development. OOP is a Object-based programming that implements class and object methods as supporters. The dedication carried out is not only a theoretical explanation but also practically so that students can immediately practice what they have explained by the tutor. The result of this activity is that students can make a websites created using OOP and their knowledge and insights about programming can increase.  
Co-Authors Aditya, Putra Adtiya, Setenilaus Afifah Azzahra Agnes Felicia Lubis Agustin, Evelyn Agustio Dwitama Aguswan, Michael Junius Alessandro, Andreas Alfonso Sitompul Andreas Alessandro Andreas Alessandro Fernando Putra Andronikus G Anggoro, Deo Ardi Riyadi Ardika, Petra Putri Arif Aliyanto Arif Aliyanto Arif Aliyanto Arif Aliyanto Arif Aliyanto Arron Mosses Jhon Hadi Ayu Elisya Natama Sianturi Azzahra, Afifah Azzahra, Violina Bima Aprianto S Br Hombing, Nova Magdalena Branchris Buchori Asyik Chintia Cantika Christy, Hanna Crecia Crecia Crecia Crecia Crecia, Crecia Daely, Septia Angelika Gettin Damayanti, Lily Daniawan, Benny Deo anggoro Dwitama, Agustio Effendy, Ellena Enjeli, Margareta Erwin erwin Erwin Erwin Filikano, Thomas Gunawan, Andronikus Hans Rafael Gabriel Turnip Imanuel, Michael Iskandar Syah Jacqueline Henny P Johan Abisay Tambunan Jonathan Supriadi Julian Masidin, Nevin Juni Lapita Hasugian Kevin Alexander Yech Kevin kevin Kusneti, Leni Latius Hermawan Leni Kusneti Maharani, Wianti Marcello, Daniel Maria Bellaniar Ismiati Martinus Ponco Pamungkas Masidin, Nevin Julian Mayer Dani Sitompul Meilinda Meilinda Meilinda Michael Junius Aguswan Michael Junius Aguswan Muhamad Raka Nur Habibi Muhammad Basri Muhammad Raka Nur Habibi Mutia Maharani Nababan, Clara Nova Magdalena Br Hombing Novaldi, Alexander Oktarina, Theresia P. Arindra Pratama Pamungkas, Martinus Ponco Pratama, Paskalis Arindra Putra, Steven Adi Ratu, Anggitta Riski Surya Saputra Rosana Rosana Sanjaya, Aloisius Egi Seli Septi Putri Septi Putri Azzahra Septia Angelika Gettin daely, Septia Angelika Gettin daely Setenilaus Aditya Setiawan, Ferdy Shevchenko, Angelus Galang Silaban, Bintang Jelita Nasrani Simanjuntak, Welmi Simbolon, Defrianti Simbolon, Defrianti Sri Andayani Sri Andayani Stefanus Agung Sagita Stefanus Charles Selvianto, Stefanus Charles Selvianto Stenilaus A Sugiarti, Sabar Sumual, Imanuel Marcell Supriadi, Jonathan Sutikno, Samuel Dimas Theresia Anita Thomas Filikano Thomas Filikano Turnip, Hans Rafael Gabriel VF Anindya W Wayan Pondra Lesmana Welmi Simanjuntak Wiikananda, Ketut Agus Wikananda, Ketut Agus Yakub, Handoyo Yohanes Agung Apriyanto Zalukhu, Indri Feni Asih