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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Komputer dan Informasi CommIT (Communication & Information Technology) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Komtika (Komputasi dan Informatika) Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika Ekonomi Bisnis Computer Science and Information Technologies Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pendidikan Indonesia (Japendi) International Journal of Engineering Continuity J-Icon : Jurnal Komputer dan Informatika Jurnal Informatika Ekonomi Bisnis Jurnal Sistem Informasi The Indonesian Journal of Computer Science
Yova Ruldeviyani
Fakultas Ilmu Komputer, Universitas Indonesia
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 Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

 1 
Strategy to Improve Employee Security Awareness at Information Technology Directorate Bank XYZ Halida Ernita; Yova Ruldeviyani; Desiana Nurul Maftuhah; Rahmad Mulyadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 4 (2022): Agustus 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.312 KB) | DOI: 10.29207/resti.v6i4.4170

Abstract

Bank handles private information like customer financial transactions and personal data. There was a 63% increase in cyberattacks attempted against Bank XYZ in 2021, and 1,323 attempted attacks on corporate email Bank XYZ. Therefore, implementing security awareness training for all employees is crucial for Bank XYZ. The information security awareness program must be assessed to determine the program's efficiency and the level of information security awareness among employees. Therefore, this study assesses the information security awareness at Bank XYZ, especially the Information Technology (IT) Directorate using the Human Aspect of Information Security Questionnaire (HAIS-Q) method. The findings of this study revealed that employees at Bank XYZ in the information security work unit had a "Good" level of awareness. In contrast, the results from other IT work units were “Medium”. Based on the assessment results, Bank XYZ's security awareness strategy recommendation is to align awareness content with information security policies and procedures, use a variety of media awareness, and focus on the "Internet Use" and "Information Handling" awareness areas. As a way of determining the achievement of information security Key Performance Indicators (KPI), security awareness measurement must be done regularly, for example, once a year.
Sentiment Analysis of Electricity Company Service Quality Using Naïve Bayes Yuli Astuti; Yova Ruldeviyani; Faris Salbari; Aldiansah Prayogi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4627

Abstract

In facing the era of technological disruption, a large company providing electricity in Indonesia, namely PT PLN is transforming to digitize all business processes and improve the quality of customer service. PLN Mobile application was developed in December 2020, and 18 million users have downloaded it. PLN Mobile application provides various electrical services for users. There are a lot of online opinions today. Organizations need to know the public perception of their product or service, sales projections, and customer happiness. Our research will identify public opinion (positive and negative) about PLN Mobile Application using sentiment analysis by taking review data from Google Play Store. Sentiment analysis is classified using Naïve Bayes and analyzed based on the dimensions of the quality of electricity services: empathy, responsiveness, and reliability. The results of this study indicate that Naïve Bayes is quite well used for binomial labels (positive and negative) with an accuracy of 73%. Still, for service quality dimensions, the accuracy is 45%. Indonesian language datasets are quite difficult to process due to non-standard language, foreign words, mixed language variations, and abbreviations. Determination of ground truth or manual labeling requires consistency and skilled personnel to determine the context of the text data to obtain a model with optimal performance. This study informs the classification of each dimension of the quality of electricity services in Indonesia based on positive and negative sentiment data for PLN Mobile Application users. Reliability received the most negative sentiments. This can be used for PT PLN to improve the quality-of-service reliability to customers.
Sentiment Analysis of Twitter Users to the PeduliLindungi Using Naïve Bayes Algorithm Lia Ellyanti; Yova Ruldeviyani; Lelianto Eko Pradana; Andro Harjanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4684

Abstract

Covid-19 was declared as a pandemic by World Health Organization (WHO) in March 2020, has a major impact on the lives. Indonesian’s government has made several efforts to suppress the spread of the virus by requiring the societies to use PeduliLindungi in every activity. There are many pros and cons from the societies in using PeduliLindungi, many reviews about the performance of this application found through playstore, app store or social media. Twitter is one of social media that allows the societies to express their feeling, idea, opinion, or critics about any topics. This study takes the review of PeduliLindungi from Twitter with period from June up to December 2021, which has the highest cases of covid-19 and tighter movement restriction from the government. The data collected were manually labeling into positive and negative class and processed using sentiment analysis with Naïve Bayes algorithm, give the result 64.69% positive sentiment and 35.5% negative sentiment regarding PeduliLindungi. The model tested using Naïve Bayes algorithm with 10-fold cross validation has the highest performance, the accuracy obtained is 95.86%, with precision 96.99% and recall 94.12%. The positive sentiment indicates the pro expression from society, like the data integration with vaccine certificate, PCR or antigen result, that makes the activities to entry public transport or public space easily. The negative sentiment indicates the cons expression from the societies, related with the performance of the application and the data security. The result of this study expected being reference, give insight, and information for developers and governments to build a better strategy in improving the performance of PeduliLindungi application.
Making AI Work for Government: Critical Success Factor Analysis Using R-SWARA Brillianto, Bramanti; Ruldeviyani, Yova; Sidiq, Darmawan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 3 (2024): June 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i3.5813

Abstract

This study quantifies what makes Artificial Intelligence (AI) work for government, the critical success factors (CSFs) for successful AI implementation within the Directorate General of Taxes (DGT). Analyzing factors such as technology, organization, process, and environment, the research highlights the importance of organizational readiness, strategic vision, and leadership support to drive successful AI integration within DGT. The dimension of the organization became the most critical factor, followed by technology, process, and environment. The findings offer actionable insights for DGT's decision-making processes, aiding in strategic resource allocation and tailored AI strategy refinement. Furthermore, this research is a valuable reference for other public sector organizations that aim to enhance operational efficiency through the adoption of AI. This study empowers decision makers within the DGT and the wider public sector by providing nuanced information on the critical factors that influence the successful implementation of AI, fostering improved operational efficiency and governance practices.
Co-Authors Achmad Nizar Hidayanto Adi Gunawan, Adi Afif Gunung , Muhammad Ahmad Fadhil, Ahmad Ahmad Hendra Maulana Ahmad Syaifulloh Imron Al Adawiyah, Rabiah Al Haq, Muhammad Hezby Al Qahar, Muhammad Yazid Aldiansah Prayogi Alfiandi, Rama Aloysius Prastowo Setyo Nugroho Amanda Ghaisani Andro Harjanto Arif Hidayat Aris Budi Santoso Ariyanto, Bima Tri Astagina, Shania Eriadhani Azis Amirulbahar Bahar, Maharani IF Brillianto, Bramanti Desiana Nurul Maftuhah Devina, Fakhira Dharmawan, GS Budhi Faris Salbari Fathurahman Ma'ruf Hudoarma Fidyawan, Miftahul Agtamas Fitriya, Ghina Genia, Venera Hafiz , Muhammad Halida Ernita Handayani, Putu Wuri Hendry, Darell Hizqil, Ahmad I Made Kurniawan Putra Ines Dwi Andini Jeri Apriansyah Pagua, Jeri Apriansyah Juliansyah, Mohamad Denis Khairunnas, Rezki Khairunnaziri, Muhammad Krisna Maria Rosita Dewi Kurniawati, Monica Vivi Layungsari Layungsari Layungsari Layungsari Layungsari Layungsari Lelianto Eko Pradana Lia Ellyanti Mahsa Elvina Rahmawyanet Melani Puspasari, Hasna Muhammad Farhan Mukharomah, Ulfah Nur Nabasya, Oristania Wahyu Noverina Alfiany Nugraha, Tito Febrian Nugraheni, Sani Parmiyanto, Joko Prastowo, Rahardito Dio Pratiwi, Aprilia Priastomo, Ristyo Yogi Prisillia, Galuh Puja Putri Abdullah Purwandaru, Dhanang Putra Hulu, Freddy Richard Putra, Ramadhoni Putri, Azanisa Rahmad Mulyadi Rahman, Henry Aulia Rahmi Julianasari Raksaka Indra Alhaqq Ramayuda, Muhammad Davin Ratna Yulika Go Rina Rahmawati Sidiq, Darmawan Sudarwono, Dianto Adwoko Sulaeman, Achmad Firmansyah Sulistiyo, Rifta Dimas Syalevi, Rahmad Tri Broto Siswoyo Tri Utami, Avita Utami, Aisyah Nurlita Wibowo, Wahyu Setiawan Widoyono, Bambang Wintang, Siti Mawar Rini Yoga Pamungkas Yudho Giri Sucahyo Yudho Giri Sucahyo Yudistira, Ricko Dwiki Yuli Astuti Zharif Mustaqim, Ilham Zulmy, Mohamad Faisal