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All Journal JUSIFO : Jurnal Sistem Informasi Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Sistemasi: Jurnal Sistem Informasi Briliant: Jurnal Riset dan Konseptual Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA INOVTEK Polbeng - Seri Informatika Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Indonesian Journal of Informatic Research and Software Engineering Malcom: Indonesian Journal of Machine Learning and Computer Science CONSEN: Indonesian Journal of Community Services and Engagement METRIK SERIAL TEKNOLOGI DAN SAINS
Zarnelly Zarnelly
Jurusan Sistem Informasi Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Physics Social Sciences Other

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Classification of Service Sentiments on the by.U Application using the Support Vector Machine Algorithm Zulkarnain, Zulkarnain; Novita, Rice; Angraini, Angraini; Zarnelly, Zarnelly
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5367

Abstract

This study aims to classify user sentiment toward the by.U application service using the Support Vector Machine (SVM) algorithm. The background of this research is based on the importance of understanding user opinions on the quality of digital services as a basis for evaluation and service improvement. Review data was collected from the Google Play Store, totaling 9,091 data points, which were then processed through preprocessing stages such as cleaning, case folding, tokenization, stopword removal, and stemming. Sentiments were categorized into three groups: positive, negative, and neutral. The training and testing process involved dividing the data into training and testing sets with an 80:20 ratio, and evaluation was conducted using metrics such as accuracy, precision, recall, and F1-score. The evaluation results showed that the SVM algorithm achieved an accuracy of 83% in classifying sentiments. The model performed best on positive sentiment (precision 84%, recall 90%, F1-score 87%) and negative sentiment (precision 81%, recall 92%, F1-score 86%), while neutral sentiment still had weaknesses with an F1-score of only 64%. This indicates that neutral sentiment classification still requires model enhancement. This study demonstrates that SVM is an effective method for automatically analyzing user opinions on digital services. These classification results can serve as a reference for developers in evaluating and improving service quality based on user feedback.
Implementation of Digital Marketing and Digital Payment in the Community of UMKM Cake Entrepreneurs : Penerapan Digital Marketing dan Digital Payment pada Komunitas UMKM Pengusaha Kue Etalase Zarnelly, Zarnelly; Fronita, Mona; Afifah, Afifah Pendri
CONSEN: Indonesian Journal of Community Services and Engagement Vol. 5 No. 1 (2025): Consen: Indonesian Journal of Community Services and Engagement
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/consen.v5i1.2041

Abstract

The current problem is the problem of promotion on social media and online sales, currently cake sales are done manually or conventionally so that it is not felt to be optimal, because it is often constrained by the weather, if it rains then cake sales are somewhat hampered, as well as during school holidays, because sales are still consignment or consignment systems, if they are not sold out then the cake producer bears the loss, in addition, in making transactions they have difficulty in providing change and storing coins, for that it is felt necessary to carry out mentoring activities for the implementation of digital marketing and digital payments to help overcome the problems of the UMKM community of cake showcase entrepreneurs. The community service method used is the PAR method, starting from problem identification, activity preparation, activity implementation and evaluation. The mentoring activity was attended by 11 participants consisting of cake producers and cake showcase entrepreneurs in Rumbai sub-district, the presentation material discussed the socialization of digital marketing and digital payment practices using the DANA application, at the end of the community service activity an evaluation was carried out with the results that 70% of participants were satisfied with the mentoring activities and wanted to implement digital marketing and digital payments in their businesses.
Analisis Sentimen Layanan J&T Express pada Sosial Media X Menggunakan Algoritma Naïve Bayes Clasifier dan K-Nearest Neighbor Priady, Muhamad Ilham; Afdal, M.; Permana, Inggih; Zarnelly, Zarnelly
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7721

Abstract

The demand for goods delivery services is increasing along with the widespread use of e-commerce platforms for buying and selling. One of the popular and frequently used delivery service providers is J&T Express. Until now, J&T has had a wide service coverage. However, various customers also have complaints that are often conveyed through social media X. For this reason, this study conducted a sentiment analysis of J&T Express user opinions on social media X using the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms. Data collection was carried out through scraping over a time span from January 1, 2023 to December 1, 2024, resulting in a total of 1,000 data points. The modeling results show that the NBC algorithm outperforms KNN, achieving an accuracy of 72.30%, a precision of 74.76%, and a recall of 72.30%. Meanwhile, the KNN algorithm with the best parameters (K = 9) only has an accuracy of 67.29%, precision of 69.46%, and recall of 67.29%. Then the results of the analysis show that J&T user opinions are dominated by negative sentiment (42.20%), followed by positive sentiment (38.70%) and neutral sentiment (19.10%). Further analysis based on five variables was also conducted and an understanding of J&T's weaknesses, namely in the service aspect, with the highest negative sentiment (21.0%). On the other hand, the user experience aspect is an advantage with the most positive sentiment (16.8%). The data visualization results also indicate that there are dominant customer complaints about the delay in the delivery process. However, customers also appreciate the speed and security of the delivery of goods. These findings provide valuable insights for J&T Express to conduct evaluations and improvements, especially in the service aspect, to improve overall customer satisfaction and experience.
Penerapan Support Vector Machine untuk Analisis Sentimen Pengguna X terhadap IndiHome, Biznet, dan Starlink Alfian, Zhevin; Afdal, M; Novita, Rice; Zarnelly, Zarnelly
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7429

Abstract

This study aims to analyze user sentiment on the social media platform X toward three major internet service providers in Indonesia, IndiHome, Biznet, and Starlink. The analysis focuses on five key variables: internet speed, network stability, pricing and service packages, customer service quality, and coverage availability. A total of 4,500 data points were collected through data crawling, then processed using text mining techniques and the Support Vector Machine (SVM) algorithm, with data imbalance addressed through the Random Oversampling method. Evaluation results show that IndiHome consistently demonstrated the best performance, achieving an accuracy of up to 90% in the customer service quality variable, and an overall average accuracy above 85% across all variables. Biznet generally ranked second, with accuracy ranging from 63% to 80%. Starlink placed lowest overall, although it still recorded competitive results, such as 82% accuracy in the internet speed variable. The application of Random Oversampling improved the model’s classification accuracy by an average of 6–12% compared to the non-oversampling model. This study offers strategic insights into public perception of internet services and can serve as a reference for improving service quality based on data-driven user feedback.
Sistem Pendukung Keputusan Pemilihan Jurusan pada SMA menggunakan Metode Profile Matching Anjani, Yulia Merry; Muttakin, Fitriani; Zarnelly, Zarnelly; Permana, Inggih
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5166

Abstract

Every year, in the process of selecting a new major at ABC High School, a major selection is carried out. This process requires students to identify their interests, talents, and abilities in order to make informed choices. However, this process often takes quite a long time because student data must be processed one by one using various different criteria. Apart from that, the selection of majors is currently based on the highest and lowest scores, with the highest score for the Science major and the lowest score for the Social Sciences major which is considered less efficient. To overcome this problem, the development of a Decision Support System (DSS) is proposed. able to provide recommendations for selecting majors more objectively. This research aims to develop SPK using the profile matching method, which will provide major recommendations based on certain criteria at SMA ABC. The criteria used include PPDB scores, science subject scores, social studies subject scores, mathematics scores, Indonesian language scores, psychological test results, student interests and parental preferences. Based on sample trials, this system recommends 6 students to enter the science department and 4 students to enter the social studies department. This system is expected to help students obtain education that suits their abilities and interests, as well as increase the efficiency of the majors process at SMA ABC.
ANALYSIS OF DIGITAL LIBRARY SERVICE QUALITY ON USER SATISFACTION USING WEBQUAL, LIBQUAL AND IPA METHODS Rahman, Eman; Jazman, Muhammad; Zarnelly, Zarnelly; Permana, Inggih
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.4.942

Abstract

Universitas Pahlawan Tuanku Tambusai has used the information system Senayan Library Management System (SLiMS) version 7. SliMS is an integrated system to provide information to support operational, management and decision-making functions in libraries. However, there are still obstacles in its use, namely, the lack of tools and technology to support the implementation of the SLiMS system, the unattractive SliMS content, the OPAC service menu is less effective in searching for references in the library, and the book collection is rarely updated so it does not meet what the user needs. This study aims to measure the service quality of SLiMS from the user's perspective. This research instrument used Web Quality (WebQual), Library Quality (LibQual), and Importance Performance Analysis (IPA) methods. The results of this study resulted in a good level of system service quality but GAP was still found from perceived performance which still had a value of <0 or -0.63 and a conformity level of 78%, which meant that there were still results of user dissatisfaction with the performance provided by the service. SLiMS Hero University of Tuanku Tambusai. Quadrant A results are a top priority to be improved. the variables are: Easy to navigate (UQ3), Attractive appearance (UQ5), Latest available information (SI1), Provides detailed information (SI4), Provides up to date information (IC3), Cleanliness and beauty (LP2), Lighting and temperature settings (LP3), Guidance from the librarian (AS5).
COMPARISON OF DATA MINING ALGORITHM FOR CLUSTERING PATIENT DATA HUMAN INFECTIOUS DISEASES Nurfadilla, Nadia; Afdal, M.; Permana, Inggih; Zarnelly, Zarnelly
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.983

Abstract

Tuberculosis is known as an infectious disease whose transmission through air intermediaries is caused by the germ Mycobacterium Tuberculosis. This disease has become a case that has almost spread throughout the pelalawan Regency with the number continuing to increase every year so that it is possible to be able to group the areas where this disease spreads. Grouping of tuberculosis data distribution areas using data mining methods in the form of clustering with the data used coming from the Pelalawan Regency Health Office from 2020 to 2022. The data obtained earlier will then be processed using k-medoids, k-means, and x-means algorithms. The beginning of this research was by processing data from each year using these three algorithms. Determination of the most optimal algorithm using DBI or known as the Davies Bouldin Index. The results of the processing of existing indicators are grouped into three sections, namely areas with a high, medium, and low number of cases. From the results of the study, the optimal algorithm in 2020 data is the k-medoids algorithms with a DBI value of 0,553 and in 2021 data, the most optimal algorithm is the k-means and x-means algorithm with similar DBI values of 0,582. Furthermore, the data in 2022 the most optimal algorithms are the k-means and x-means algorithms because they have the same DBI value, which is 0,510.
Analisis Kinerja Sistem Informasi Kesejahteraan Sosial Next-Generation Menggunakan Metode IT Balanced Secorecard Ariansah, Rizky; Maita, Idria; Muttakin, Fitriani; Zarnelly, Zarnelly; Hamzah, Muhammad Luthfi; Marsal, Arif
BRILIANT: Jurnal Riset dan Konseptual Vol 9 No 2 (2024): Volume 9 Nomor 2, Mei 2024
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v9i2.1781

Abstract

SIKS-NG is an application implemented by social services to provide targeted information on data on underprivileged communities. However, in its implementation, the feasibility value of this application is not yet known, so there are several problems that affect the performance of user services such as network problems, server problems and several features that are not optimal. This research aims to measure performance in the SIKS-NG application using the IT balanced corecard method, which is a method for assessing the performance of an information technology system by considering information technology units from 4 variables, namely company contribution, user orientation, operational excellence (operational excellence), and future orientation (future orientation). Data was taken through a questionnaire from 31 respondents involving the main admin coordinator, agency admin and SIKS-NG users. The total results of measurements using the IT Balanced Corecard approach on SIKS-NG performance are in the "GOOD" category, reaching 70.1% of the influence that occurs comes from the dependent variable, while the remaining 20.9% is influenced by other dependent variables.
Analisis Kepuasan Pengguna Aplikasi BRImo Menggunakan Metode End User Computing Satisfaction dan Delone & Mclean Harmutika, Della; Rahmawita, Medyantiwi; Rozanda, Nesdi Evrilyan; Zarnelly, Zarnelly
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 2 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i2.38876

Abstract

BRImo is a mobile banking application that provides online transaction services, but there are still some BRImo users who are still constrained by using the BRImo application. As for difficulties in using the BRImo application, difficulty transacting, difficulty logging in, then users are often blocked which results in less comfort in using the BRImo applicationn which can reduce the level off user trust. The goal is to find out the level of user satisfation of the BRImo application usingg the End User Computing Satisfaction (EUCS) and Delone & Mclean research models. The EUCS model means a comparison model between reality and expectations (reality). DeLone and McLean means a model for identifying factors that cause the success of an information system. In this study, it can be measured from 5 EUCS indicators and 3 Delone & McLean indicators which will use purposive sampling techniques collected through online questionnaires in the form of google forms to 100 user respondents, so that the data obtained will be analyzed using SmartPLS 4. Thus the final resultss of this study state that the variables of content, easy of use, information quality, service quality, and timeliness have a significant effect, then 3 other variables, namely accuracy, format, and system quality, do not have significant positive effect on the satisfaction of BRImo application users.
Analisis Sentimen Ulasan Pengguna Aplikasi Mobile Banking Menggunakan Algoritma K-Nearest Neighbor Munandar, Darwin; Afdal, M.; Zarnelly, Zarnelly; Novita, Rice
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.41409

Abstract

Mobile banking is evident in the improvement of business processes in the banking industry. Even so, the m-banking application cannot be separated from the problems experienced by its users. Therefore, further analysis is required. This research proposes a sentiment analysis technique using K-Nearest Neigbor (KNN) algorithm to identify user opinions and reviews of m-banking applications. Three popular m-banking apps were selected for further analysis namely BRImo, BSI Mobile, and Livin' by Mandiri. The analysis shows that BRImo is the most popular m-banking application, with a positive sentiment percentage of 58.25%, Livin' by Mandiri with 22.50%, and BSI Mobile with the lowest percentage of 12.70%. Modeling results using the KNN algorithm with K = 3, 5 and 7 test values show K = 3 has better capabilities. Based on the application, the best modeling is produced on BRImo with 82.9% accuracy, then Livin' by Mandiri with 70.3% accuracy, and BSI Mobile with 71.35% accuracy. Analysis and visualization were also conducted using word clouds to see keywords that are often discussed in reviews. As a result, m-banking apps have problems with difficult login, complicated registration or verification, and balance deduction despite failed transfer status.
Co-Authors 'alimah, Muta Afifah, Afifah Pendri Afifah, Tiara Afrah Ahsyar, Tengku Khairil Akhiril Anwar Harahap Al-Qadr, Nola Ardelia Al-Yasir, Al-Yasir Alfian, Zhevin Anahyu, Yelfi Dwi Angraini Angraini Anjani, Yulia Merry Anofrizen Anofrizen Ariansah, Rizky Arif Marsal Butar Butar, Febiola Siska Dulbari, Dulbari Eki Saputra fitriano, ernesto Hamzah, Muhammad Luthfi Harmutika, Della Inggih Permana Irwanda, Mahyuda Jazman, Muhammad M. Afdal Megawati , Megawati Megawati - Mona Fronita, Mona Munandar, Darwin Munzir, Medyantiwi Rahmawita Mustakim Mustakim Muttakin, Fitriani Nazaf, Latiful Nurfadilla, Nadia Permana, Jeki Harya Pratama, Arya Yendri Priady, Muhamad Ilham Pristiawati, Andani Putri Putra, Ahdika Sawiyya Putra, Tandra Adiyatma Rahman, Eman Rahmawita, Medyantiwi Ramadhani, Indah Razmi, Fikri Rice Novita Rozanda, Nesdi Evrilyan S. Nagalay, Fitra Salam Siti Monalisa Sri Lestari Sriyanto Sriyanto Suwito, Bagus Anjari Syaifuddin, Aditya tri utami, septiana Ula, Walid Alma Widi Nugroho, Handoyo Widyawati, Dewi Kania Wulandari, Suri Yanti, Rahma Zulkarnain Zulkarnain Zuriati, Zuriati