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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TELKOMNIKA (Telecommunication Computing Electronics and Control) SITEKIN: Jurnal Sains, Teknologi dan Industri JUSIFO : Jurnal Sistem Informasi Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Seminar Nasional Teknologi Informasi Komunikasi dan Industri INOVTEK Polbeng - Seri Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Inotera JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Zonasi: Jurnal Sistem Informasi Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) 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 Journal of Informatics, Electrical and Electronics Engineering The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika
Febi Nur Salisah
Program Studi Sistem Informasi, Fakultas Sains Dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Other

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Applying KNN, NBC, and C4.5 Algorithms to Identify Eligibility for Non-Cash Food Aid Rizki Pratama Putra Agri; Permana, Inggih Permana; Salisah, Febi Nur; Jazman , Muhammad; Afdal, Muhammad
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/89xvxf70

Abstract

The Indonesian government has implemented the Non-Cash Food Assistance (BPNT) program as an effort to improve people's welfare. However, in its implementation, there are still obstacles in the process of determining the right beneficiaries. Determining the right BPNT recipients is important to ensure that the assistance is received by people who really need it and to prevent budget misuse. This research aims to help the government to easily process data using three classification algorithms, namely K-Nearest Neighbour (K-NN), Naïve Bayes Classifier (NBC), and C4.5 in classifying BPNT recipient data in Air Molek Village, Indragiri Hulu Regency. K-NN, NBC, and C4.5 were chosen because they represent different approaches: K-NN is distance-based, NBC is probability-based, and C4.5 uses decision trees. The stages of the methodology used include data collection, data preprocessing, data splitting (Hold-Out), data balancing and model testing. The results showed that the K-NN algorithm got an accuracy of 70.45%, precision 68.34% recall 72.42%, NBC got an accuracy of 60.58%, precision 58.21%, recall 85.42%, and C 4.5 with an accuracy of 62.56%, precision 59.17%, recall 63.33%. The results of this study can help the government in developing a more objective and data-based decision support system for determining BPNT recipients. The limitation of this research is the use of data that is limited to only one of the data sources.
Analisis Kepuasan Mahasiswa Pekanbaru Pada Aplikasi Flip dengan Metode End User Computing Satisfaction (EUCS) Anggi Widya Atma Nugraha; Inggih Permana; Febi Nur Salisah; Tengku Khairil Ahsyar; M. Afdal
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2439

Abstract

A Flip is a Financial Technology (fintech) company providing admin fee-free money transfer services that has been used by more than 10 million users. Along with technological developments in the financial sector, Flip must be able to compete and survive against similar service providers. Efforts that can be made to compete include measuring satisfaction levels in using Flip. The purpose of this study is to assess the level of satisfaction of Flip users so that the results of this research can be used to provide recommendations for evaluating the Flip information system. In conducting satisfaction level analysis, the End User Computing Satisfaction (EUCS) approach can be applied. EUCS is able to evaluate usage satisfaction in using information systems in the areas of content, accuracy, format, ease of use, and timeliness based on information system usage experience. The research was conducted with sample data from university student users of the Flip application in Pekanbaru City. Based on the test results, the highest result with a percentage value of 80% in the Very Satisfied category was observed in the Ease of Use variable from the Likert scale results. The average satisfaction level of Flip application users was 77% in the Satisfied category. The Classical Assumption Test results showed that in the normality test, the testing was normal, and in the multicollinearity testing, it was found that multicollinearity did not occur in the test results. In the Multiple Linear Regression Test, the variable equation result obtained was Y = 0.158 + 0.114X1 + 0.031X2 + 0.054X3 + 0.111X4 + 0.001X5. Based on the Coefficient of Determination Test results, it was found that the content variable, accuracy variable, format variable, ease of use variable, and timeliness variable were able to explain their relationship to the dependent variable and showed an influence of 53%.
Pengukuran Retensi Pelanggan Insyira Oleh-Oleh Berdasarkan Analisis Sentimen Pengguna Instagram Fiki; Inggih Permana; Febi Nur Salisah; Eki Saputra; Arif Marsal
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2473

Abstract

Instagram as a social media platform has opened new opportunities for businesses to market their products creatively and efficiently. Through interactive features such as the comments section, users can express their opinions about the products or services offered. These comments contain sentiments that can be analyzed to understand customer perceptions. This study aims to measure customer retention using sentiment analysis of Instagram user comments. The comment data was collected using web scraping techniques from the Instagram page, followed by labeling using a lexicon-based approach and sentiment classification into positive, negative, and neutral categories through sentiment analysis. This analysis is linked to the concept of customer retention, which is an important strategy for maintaining long-term relationships with consumers. Furthermore, the results of customer retention analysis in this study show that positive sentiment has a retention rate of 53.4% (303 out of 567 comments), neutral sentiment 6.9% (45 out of 650 comments), and negative sentiment 15.1% (22 out of 146 comments). Overall, 370 out of 1,363 comments, or 27.1%, were categorized as contributing to retention. In terms of the proportion of sentiment contributing to total retention, positive comments dominate with 81.9% (303 out of 370). These findings suggest that although neutral comments are the most frequent, positive sentiment contributes the most to customer retention. This indicates that positive sentiment is a strong predictor of customer loyalty, highlighting the importance for companies to foster positive experiences through quality products, reliable services, and active engagement on social media. Insyira is capable of maintaining customer retention, especially from those who express positive sentiment, which reflects satisfaction with its products, services, and interactions on social media
Evaluating the Impact of Data Balancing Techniques on the k-Nearest Neighbors Algorithm for Microarray Data Classification Febi Nur Salisah; Inggih Permana; Sanusi; Shir Li Wang
Jurnal Inotera Vol. 10 No. 2 (2025): July - December 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss2.2025.ID497

Abstract

Microarray data classification poses significant challenges in bioinformatics due to the nature of the data, which has a very high number of features but a limited number of samples, and an unbalanced class distribution. This condition can cause a decrease in the performance of classification models, including k-Nearest Neighbor (kNN). This study aims to evaluate the performance of the kNN algorithm in classifying unbalanced and balanced data. The balancing techniques used are Random Undersampling (RUS), Random Oversampling (ROS), and Synthetic Minority Over-sampling Technique (SMOTE). The datasets used in this study are three leukemia datasets with different class structures, namely two, three, and four classes. The experimental results show that the ROS and SMOTE techniques consistently improve the performance of kNN, with the best accuracy reaching more than 97%. In the two-class dataset, ROS gave the best performance (99.4%), while in the three-class dataset, SMOTE showed the most optimal results (98.5%). In the four-class dataset, the performance improvement due to balancing was very significant; SMOTE and ROS were able to improve the accuracy from 89.7% (without balancing) to 99.0% and 98.8%, respectively. Although RUS recorded perfect accuracy of 100%, the results were anomalous and inconsistent. RUS showed less stable performance and was often lower than the condition without balancing, especially on datasets with four classes. Overall, the SMOTE technique proved to be the most stable and effective for various class structures. This study shows the importance of balancing strategies in the classification of complex and imbalanced microarray data.
Density-Based Spatial Clustering, K-Means and Frequent Pattern Growth for Clustering and Association of Malay Cultural Text Data in Indonesia Mustakim, Mustakim; Salisah, Febi Nur
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7512

Abstract

Several studies state the need to develop information technology to disseminate information related to culture in Indonesia. There are many similar studies but they still have weaknesses, one of which is that they do not use machine learning and intelligent computing. This research answers the challenges of previous researchers, namely developing machine learning-based learning applications using the Density-Based Spatial Clustering of Application Noise (DBSCAN) and Frequent Pattern Growth (FP-Growth) algorithms. The results of the modeling of the two algorithms are deemed to still require improvement in the future, as it is proven that DBSCAN does not yet have optimal validity. So in this research, one of the comparison algorithms is used, namely K-Means Clustering, with a better evaluation than DBSCAN. The modeling results were implemented into mobile programming as a cultural learning application in Indonesia, especially Riau Malay Culture, the black box testing results had an accuracy of 100% and the User Acceptance Test (UAT) was 86%. Thus, it is concluded that this application can be used effectively and efficiently for general users.
EVALUASI USER EXPERIENCE PADA APLIKASI WONDR BY BNI MENGGUNAKAN METODE UEQ DAN SUS Lestari, Indah; Saputra, Eki; Afdal, M; Nur Salisah, Febi; Syaifullah, Syaifullah
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/vksfqm62

Abstract

Wondr by BNI is a mobile banking application in Indonesia designed to support systematic financial management through three main concepts: Insight, Transaction, and Growth. Despite offering advanced features, many users complain about issues such as failed transactions, login difficulties, and slow application response times. This study evaluates the user experience of the Wondr app by combining the UEQ and SUS methods. The UEQ evaluation results show an average score of: attractiveness 1.12; clarity 1.06; efficiency 1.05; accuracy 1.07; stimulation 0.71; and novelty 0.77. Meanwhile, the SUS score of 64.6 falls into category D, “OK” on the adjective scale, and “Marginally Acceptable” on the usability scale—indicating that the app's usability is slightly below the average standard. Overall, users gave positive ratings for clarity, efficiency, accuracy, and stimulation, but attractiveness and novelty still need improvement. To date, no studies have specifically evaluated the UX of the Wondr app by combining the UEQ and SUS methods. This research contributes new scientific insights by demonstrating the app's UX performance and areas requiring improvement.
Sistem Pendukung Keputusan Pemilihan Supplier Menggunakan Metode Simple Additive Weighting Pada Toko Grosir Dua Putri Mawaddah, Zuriatul; Salisah, Febi Nur; Saputra, Eki; Afdal, M.
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 8 (2025): JPTI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.958

Abstract

Pemilihan supplier yang tepat memegang peranan penting dalam menjaga efisiensi operasional dan daya saing perusahaan, khususnya dalam bisnis grosir. Toko Grosir Dua Putri mengalami kesulitan dalam menentukan supplier terbaik secara objektif. Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan (SPK) berbasis web menggunakan metode Simple Additive Weighting (SAW) guna mendukung pemilihan supplier secara efektif dan transparan. Metode SAW dipilih karena kemampuannya dalam memberikan penilaian terukur berdasarkan pembobotan beberapa kriteria, seperti harga, kualitas, ketepatan pengiriman, tempo pembayaran, dan layanan purna jual. Sistem ini dibangun menggunakan PHP dan MySQL. Evaluasi dilakukan melalui Black Box Testing dan User Acceptance Test (UAT), yang menunjukkan bahwa sistem bekerja dengan baik, dengan tingkat kepuasan pengguna sebesar 97,5%. SPK yang dikembangkan mampu memberikan rekomendasi supplier secara objektif, sehingga dapat meningkatkan akurasi dan efisiensi dalam pengambilan keputusan.
Evaluasi Kualitas Layanan Sistem e-Puskesmas di Kecamatan Sungai Mandau Melalui Kerangka Kerja E-SERVQUAL dan Model Kano Setiawati, Elsa; Salisah, Febi Nur; Jazman, Muhammad; Rahmawita, Medyantiwi
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.978

Abstract

Permasalahan dalam penerapan sistem e-Puskesmas masing terjadi, terutama terkait kualitas layanan digital yang belom optimal. Keluhan seperti sistem tidak stabil, tampilan antarmuka membingungkan, dan kurangnya pelatihan menunjukkan perlunya evaluasi menyeluruh. Penelitian ini menggunakan pendekatan kuantitatif dengan metode E-SERVQUAL dan Model Kano. E-SERVQUAL mengukur kesenjangan antara persepsi dan harapan pengguna berdasarkan tujuh dimensi: efficiency, system availability, fulfillment, privacy, responsiveness, compensation, dan contact. Model Kano digunakan untuk mengklasifikasikan atribut layanan berdasarkan dampaknya terhadap kepuasan pengguna. Hasil menunjukkan bahwa seluruh atribut memiliki nilai GAP negative, dengan rata-rata nilai Q sebesar 0.91. ini menandakan bahwa layanan belum memenuhi harapan pengguna. Berdasarkan Model Kano terdapat 12 atribut one-dimensional, 4 attractive, 3 ust-be, dan 1 indifferent. Temuan ini menunjukkan bahwa perbaikan perlu difokuskan pada atribut yang berdampak langsung terhadap kepuasan.
ANALISIS PENERAPAN TRANSFORMASI DIGITAL PADA UMKM PABRIK TEMPE CAP ANGSA MENGGUNAKAN METODE SWOT Shulhan Abdul Gofar; Febi Nur Salisah; Megawati; Zarnelly
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 2 (2024): Publikasi Artikel ZONAsi: Periode Mei 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i2.20336

Abstract

UMKM Pabrik Tempe Cap Angsa merupakan usaha agroindustri pengolahan kedelai menjadi tempe dengan sistem pengolahan semi modren. Permasalahan yang dihadapi saat ini adalah kurangnya memanfaatkan teknologi informasi digital dalam mempromosikan produk, keterbatasan akses pasar, kurangnya analisis data berupa perilaku pelanggan dan tren pasar. Penelitian ini menggunakan metode analisa SWOT dan dikombinasikan dengan Business Model Canvas (BMC) untuk memetakan model bisnis yang dapat dijadikan pedoman pengembangan bisnis dalam transformasi digital. Penelitian ini menunjukkan hasil faktor internal 0,20375 dan nilai faktor eksternal 0,18125 yang mana terletak di kuadran I yang merupakan strategi agrasif, strategi agresif menghubungkan antara Kekuatan (Strength) dan Peluang (Opportunity). Terdapat beberapa alternatif strategi yang tepat untuk UMKM Pabrik Tempe Cap Angsa dirumuskan melalui Business Model Canvas yang memetakan 9 blok peningkatan bisnis.
CYBERBULLYING SENTIMENT ANALYSIS OF INSTAGRAM COMMENTS USING NAÏVE BAYES CLASSIFIER AND K-NEAREST NEIGHBOR ALGORITHM METHODS Anisa Nirmala, Fitri; Jazman, Muhammad; Rozanda, Nesdi Evrilyan; Salisah, Febi Nur
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.5.1997

Abstract

The high number of social media users presents major threats and risks, such as cyberbullying Cyberbullying or cyberbullying is one of the negative impacts of the rapid development of technology and social media. Sentiment Analysis is a technique for extracting text data to obtain information about positive, neutral or negative sentiment. One of Indonesian social media that often gets user sentiment through social media is Instagram. By using the Text Mining technique, the classification method will determine whether a sentiment is positive, neutral or negative. This research uses the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) methods with tf-idf weighting accompanied by the addition of an emotional icon (emoticon) conversion feature to determine the existing sentiment classes from tweets about Instagram users. The results of calculations using the first three methods using the Partitionong model, the results using the Naive Bayes method, get an accuracy value of 91.25%, a recall value of 92% and a precision value of 90% and calculations using the KNN method have an accuracy value of 67%, a recall value of 49% and a precision value of 34 %. So it can be concluded that the Naïve Bayes Classifier algorithm has the best performance.
Co-Authors A Anggraini Afdal Muhammad Efendi Ahsyar, Tengku Khairil Anggi Widya Atma Nugraha Anggia Anfina Anisa Nirmala, Fitri Anwar, Tengku Khairil Arabiatul Adawiyah Arif Marsal Arif Marsal Arif Marsal Arrazak, Fadlan Bayu Putra Danil Risaldi Darmawan, Reza Dewi Astuti Efendi, Harisman Eki Saputra Eki Saputra Eki Saputra Elin Haerani Endah Purnamasari Esis Srikanti Fachrurozi Fadhilah Syafria Fadil Rahmat Andini Febrian, Dany Fernanda, Ustara Dwi Fiki Fitri Wulandari Fitriah, Ma’idatul Fitriah, Ma’idatul Fitriani Muttakin Fitriani Muttakin Giansyah, Qhoiril Aldi Gustinov, Mhd Dion Hasbi Sidiq Arfajsyah Hendri, Desvita Husaini, Fahri Idria Maita Idria Maita Idria Maita Idriani R, Nova Imam Muttaqin Indah Lestari, Indah Indri Dian Pertiwi Inggih Permana Intan, Sofia Fulvi Jayadi, Puguh Jazman , Muhammad Jazman, Muhammad Kusuma, Gathot Hanyokro Leony Lidya M Afdal M. Afdal M. Afdal M. Afdal M.Afdal Maulana, Rizki Azli Mawaddah, Zuriatul Mega wati, Mega Megawati Megawati - Megawati Megawati Mona Fronita, Mona Mubarak MR, Najmuddin Muhammad Afdal Muhammad Iqbal Indrawan Muhammad Jazman Muhammad Luthfi Muhammad Luthfi Hamzah Muhammad Munawir Arpan Munzir, Medyantiwi Rahmawita Mustakim Mustakim Muttakin, Fitriani Nabila Putri Nailul Amani Nardialis Nardialis Nasution, Nur Shabrina Naufal Fikri, R. Adlian Nesdi Evrilyan Rozanda Nesdi Evrilyan Rozanda Norhavina Norhavina Nuraisyah Nuraisyah Nurkholis Nurkholis Nurrahma, Intan Puput Iswandi Putri, Amanda Iksanul Rahmawita M, Medyantiwi Rahmawita, Medyantiwi Rangga Arief Putra Ria Agustina Rice Novita Rizka Fitri Yansi Rizki Pratama Putra Agri Rozanda, Nesdi Evrilyan Sanusi Saputri, Setia Ningsih Sari, Gusmelia Puspita Sarjon Defit Setiawati, Elsa Shir Li Wang Shulhan Abdul Gofar Siti Zainah Sulthan Habib Suryani Suryani Susilawati, Susilawati Syahri, Alfi Syaifullah Syaifullah Syaifullah Syaifullah Syaifullah Syaifullah Syarif, Yulia Tengku Khairil Ahsyar Tengku Khairil Ahsyar Tengku Khairil Ahsyar Tengku Khairil Ahsyar Tshamaroh, Muthia Uci Indah Sari Winda Wahyuti Wira Mulia, M. Roid Zarnelly Zarry, Cindy Kirana