Abstract:Penggunaan dompet digital yang terus meningkat menghasilkan banyak ulasan pengguna yang dapat dimanfaatkan untuk mengevaluasi kualitas layanan. Penelitian ini bertujuan meningkatkan akurasi klasifikasi sentimen pengguna…
dompet digital menggunakan metode Stacking Ensemble Machine Learning yang mengombinasikan Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), dan AdaBoost dengan Logistic Regression sebagai meta-learner. Data ulasan diproses melalui tahapan text preprocessing meliputi case folding, cleaning, tokenizing, stopword removal, stemming, dan pembobotan fitur menggunakan TF-IDF. Penyeimbangan data dilakukan dengan SMOTE, sedangkan evaluasi model menggunakan 5-Fold Cross-Validation. Hasil penelitian menunjukkan bahwa model Stacking Ensemble memperoleh akurasi rata-rata 80,55%, lebih tinggi dibandingkan algoritma dasar. Evaluasi menggunakan Confusion Matrix, Classification Report, dan ROC Curve juga menunjukkan peningkatan nilai precision, recall, F1-score, dan kemampuan diskriminasi model. Hasil ini menunjukkan bahwa pendekatan Stacking Ensemble Machine Learning efektif untuk meningkatkan akurasi klasifikasi sentimen pengguna dompet digital serta mendukung evaluasi kualitas layanan berbasis opini pengguna.
The rapid growth of digital wallet usage has generated a large volume of user reviews that can be utilized to evaluate service quality. This study aims to improve the accuracy of digital wallet user sentiment classification using a Stacking Ensemble Machine Learning approach that combines Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), and AdaBoost with Logistic Regression as the meta-learner. User reviews were processed through text preprocessing stages, including case folding, text cleaning, tokenization, stopword removal, stemming, and TF-IDF feature weighting. Synthetic Minority Over-sampling Technique (SMOTE) was employed to address class imbalance, while model performance was evaluated using 5-Fold Cross-Validation. The experimental results show that the proposed Stacking Ensemble model achieved an average accuracy of 80.55%, outperforming the individual base learners. Furthermore, evaluations based on the Confusion Matrix, Classification Report, and Receiver Operating Characteristic (ROC) Curve demonstrated improvements in precision, recall, F1-score, and the model's discriminative capability. These findings indicate that the proposed Stacking Ensemble Machine Learning approach is effective in improving the accuracy of digital wallet user sentiment classification and can serve as a reliable tool for supporting service quality evaluation based on user opinions.
Abstract:Abstract This study aims to analyze the implementation of the Integrated Licensing Service Information System (SIPINTER) at the Investment and One-Stop Integrated Services Office (DPMPTSP) of Tangerang Regency. The research…
earch is grounded in issues of low institutional responsiveness in following up on complaints, mismatches between actual service completion time and the Standard Operating Procedure (SOP), and uneven public socialization of the system. This study employs a descriptive method with a qualitative approach, using 3-dimensional e-government success model, namely Support, Capacity, and Value, as the analytical framework. Data were collected through field observation, regulatory documentation review, and in-depth interviews. The findings indicate that the Support dimension is backed by strong political will, allocated funding, and multi-channel socialization that has driven growth in registered users, though technical assistance responsiveness outside office hours remains weak. The Capacity dimension shows adequate human resources and staff competence, but the technological infrastructure remains prone to disruptions such as OTP delivery failures and server downtime. The Value dimension has produced tangible benefits in efficiency and service transparency, yet this value is undermined by document processing delays exceeding SOP standards, driven by a "digital red tape" practice among internal verification officers. This study recommends strengthening online technical support and adopting contingency resource mechanisms to improve service.
Keywords: SIPINTER, e-government, licensing service, DPMPTSP, Support-Capacity-Value model
Abstrak
Penelitian ini bertujuan untuk menganalisis Penerapan Sistem Informasi Pelayanan Perizinan Terpadu (SIPINTER) di Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu (DPMPTSP) Kabupaten Tangerang. Latar belakang penelitian ini didasari oleh masih rendahnya responsivitas instansi dalam menindaklanjuti laporan, ketidaksesuaian durasi penyelesaian layanan dengan Standar Operasional Prosedur (SOP), serta sosialisasi yang belum merata kepada masyarakat. Penelitian menggunakan metode deskriptif dengan pendekatan kualitatif, dengan analisis berlandaskan model keberhasilan e-government tiga dimensi yaitu Support, Capacity, dan Value. Hasil penelitian menunjukkan bahwa dimensi Support telah didukung oleh political will yang kuat, alokasi anggaran, dan sosialisasi multikanal yang mendorong pertumbuhan pengguna terdaftar, namun masih lemah dalam responsivitas bantuan teknis di luar jam kerja. Dimensi Capacity menunjukkan kecukupan sumber daya manusia dan kompetensi petugas, tetapi infrastruktur masih rentan mengalami gangguan teknis seperti kegagalan pengiriman OTP dan server down. Dimensi Value menghasilkan manfaat nyata berupa efisiensi dan transparansi pelayanan, namun nilainya terdegradasi akibat keterlambatan penyelesaian dokumen yang melampaui SOP, yang dipicu oleh praktik birokrasi digital (digital red tape) di tingkat verifikator internal. Penelitian ini merekomendasikan penguatan dukungan teknis daring serta penerapan mekanisme kontingensi sumber daya untuk meningkatkan layanan.
Kata Kunci: SIPINTER, e-government, pelayanan perizinan, DPMPTSP, model Support-Capacity-Value
Abstract:PayLater services are one of the rapidly growing digital financial innovations widely utilised in fintech apps in Indonesia, including Kredivo and Akulaku. User reviews on the Google Play Store reflect a range of experiences,…
nces, from satisfaction with the ease of use of the service to complaints regarding bills, interest rates, late payment fees, credit limits, and app performance. This study aims to classify the sentiment of user reviews regarding PayLater services on the Kredivo and Akulaku apps using the Multinomial Naïve Bayes algorithm. Data was collected via web scraping from the Google Play Store and automatically labelled based on user ratings, with ratings of 1-2 classified as negative sentiment and ratings of 4-5 as positive sentiment, whilst a rating of 3 was excluded as it was considered ambiguous. Following a preprocessing stage comprising cleaning, case folding, tokenisation, stopword removal, and stemming, as well as feature extraction using TF-IDF, 3,652 reviews were obtained with a training-to-test data split ratio of 80:20. The results indicate that positive sentiment dominates the dataset at 56.49%, whilst negative sentiment accounts for 43.51%. Analysis by application revealed that Kredivo was dominated by positive sentiment (68.20%), whilst Akulaku was dominated by negative sentiment (51.70%). The Naïve Bayes multinomial model achieved an accuracy of 84.13%, with average precision, recall, and F1-score values of 0.84, demonstrating good and balanced classification performance across both sentiment classes.
Abstract:Digital transformation is the process of bringing technology into the work of organisations. The main goal is to make things work better, be more open and make decisions. Internal audits are important to make sure organisations…
sations are running smoothly and safely. This means audits need to be able to watch over control and manage risks properly. This is very important for organisations to achieve their goals. Stopping fraud is about finding and preventing actions that can hurt the organisation. This research is trying to figure out how digital transformation affects audits and stopping fraud. The researchers used a method called a 'systematic literature review'. This research is about describing things in detail. They got their information from international journals. They used Google Scholar, Scopus and Sinta to find articles from 2022 to 2025. What they found out is that technology like intelligence looking at data, blockchain, robotic process automation and electronic auditing can make internal audits better. These technologies can also make things more transparent. Help stop fraud. However, digital transformation is not easy to do. There are some problems, like auditors not being good enough with technology risks to cybersecurity and organisations not being ready. Digital transformation and internal audits are. Digital transformation can affect fraud prevention. Digital transformation is important for organisations. It can help with internal audits and fraud prevention.
Abstract:Appendicitis is an acute inflammatory condition of the appendix that requires prompt surgical intervention and comprehensive perioperative nursing care to prevent complications. This study aims to describe the application…
n of perioperative pain management in a patient with appendicitis at UPT RSUD Labuang Baji Makassar. A descriptive case study design is employed using a perioperative nursing care approach covering preoperative, intraoperative, and postoperative phases. The subject is a 44-year-old male patient diagnosed with appendicitis who undergoes appendectomy. Data are collected through interviews, observation, physical examination, and documentation, with pain assessed using the Numeric Rating Scale. Nursing interventions focus on non-pharmacological pain management, including deep breathing relaxation in the preoperative phase and Benson relaxation therapy in the postoperative phase. The results show a decrease in pain intensity and anxiety before surgery, effective control of intraoperative bleeding, and gradual reduction of postoperative pain accompanied by improved tissue integrity and patient knowledge. This case study demonstrates that appropriate non-pharmacological nursing interventions effectively support perioperative pain management and enhance patient recovery in appendicitis cases.
Abstract:Indonesia faces a dualism within the Islamic fiscal system, where zakat and taxes operate separately without clear integration. This condition raises fundamental questions regarding the relationship between the two from…
a sharia perspective and their implications for fiscal justice among Indonesian Muslims. This study aims to examine and formulate the relationship between zakat and taxes from the perspective of the Qur’an and Hadith in order to produce an applicable reformulation model within the context of Indonesia’s fiscal system. This research employs a qualitative approach using a thematic (maudhu‘i) method applied to primary Islamic texts. Qur’anic verses and Hadiths related to zakat, taxation (kharaj, jizyah, ‘usyur), and fiscal obligations were collected, classified, and comprehensively analyzed to identify the underlying connection between the two. The analysis is further supported by a study of maqashid al-shariah and contemporary ijtihad of Indonesian scholars. This study seeks to produce a reformulation model of the zakat–tax relationship through three possible schemes: (1) a partial substitution model, in which zakat can serve as a deduction for income tax up to a certain limit; (2) a complementary model, positioning zakat as a religious obligation and tax as a civic obligation with distinct functions; and (3) a progressive integrative model, integrating zakat into the national fiscal system through a more comprehensive tax incentive mechanism. The findings indicate that the Qur’an and Hadith provide a flexible foundation for all three models, depending on the context of maslahah and public interest.
Abstract:The independent curriculum provides opportunities for educators and students at SMP Muhammadiyah 51 Sidikalang to obtain information. Non-formal education can be obtained by participating in various activities, one of which…
ich is socialization outside of school. This socialization provides additional knowledge, it turns out that mathematics and biology can be connected, for example regarding learning Biomathematics which can help model populations from the spread of disease, in this case the model for the spread of Covid-19. The aim of this event is so that educators and students can apply and model the spread of disease and read real phenomena through data. The method used in this event is assistance which helps in explaining the modeling of the Covid-19 disease and analyzing the data so that conclusions can be drawn on the spread of the population so that the spread can be stopped. The results of this event were that 85% of educators and students were able to take part in this socialization by being able to form and model in a simple way the formation of disease models both by analyzing data.
Abstract:This study examines the effectiveness of the Presbyterian-Synodal system of church governance in shaping an inclusive, participatory, and contextual ministry within the Indonesian Protestant Church in Papua (GPI Papua).…
Employing a qualitative approach and contextual case study, the research focuses on the relationship between church governance structures and Papuan communal culture, which emphasizes deliberation, egalitarianism, and communal living. The findings indicate that, in principle, the Presbyterian-Synodal system possesses the potential to accommodate the collective character of Papuan society and to support congregational participation in ecclesiastical decision-making processes. However, implementation at the local level faces several challenges, including inconsistent understanding of ecclesiastical roles and responsibilities, limited human resource capacity, and misalignment between synodal policies and the contextual needs of congregations. These issues reveal a gap between the theological-structural design of the system and the pastoral realities on the ground. Therefore, this study recommends institutional renewal based on local contexts, the development of transformative church leadership models, and the strengthening of ecclesiological education rooted in Papuan cultural and social dynamics. Theoretically and practically, this research contributes to the development of contextual ecclesiology and church management in multicultural settings, emphasizing the importance of synthesizing Reformed theology with local values. As such, this study not only offers a constructive critique of current church governance practices but also opens space for reflection and innovation, enabling the church to become more relevant, just, and empowering in addressing contemporary challenges and contextual realities.
Abstract:Abstract: Education is only one area that has felt the effects of the exponential growth in computing power. Data processing and decision-making have grown more dependent on the use of information technology systems. Manually…
ually selecting extracurricular activities at Panti Budaya Private High School causes kids to lose sight of what interests them and what they're good at. Because of this, kids may stop participating in extracurricular activities and never discover their true passions. Hence, it is necessary to have a decision-support system that can appropriately suggest extracurricular activities to kids according to their abilities. The purpose of this study is to develop and construct a recommendation system that makes use of the MCDM technique, more especially the ELCTRE method, which stands for the Elimination and Choice Translation Reality. By applying predefined criteria to a set of alternatives, this approach can choose the optimal one. The goal of this approach is to help students reach their full potential by recommending extracurricular activities that are both relevant and accurate.
Keywords: decision support system; extracurricular activities; student potential; MCDM; ELECTRE
Abstrak: Pendidikan merupakan salah satu bidang yang merasakan dampak dari pertumbuhan eksponensial dalam daya komputasi. Pemrosesan data dan pengambilan keputusan semakin bergantung pada penggunaan sistem teknologi informasi. Memilih kegiatan ekstrakurikuler secara manual di SMA Swasta Panti Budaya menyebabkan anak-anak kehilangan minat pada apa yang mereka sukai dan apa yang mereka kuasai. Karena hal ini, anak-anak mungkin berhenti berpartisipasi dalam kegiatan ekstrakurikuler dan tidak pernah menemukan gairah sejati mereka. Oleh karena itu, diperlukan sistem pendukung keputusan yang dapat secara tepat menyarankan kegiatan ekstrakurikuler kepada anak-anak sesuai dengan kemampuan mereka. Tujuan dari penelitian ini adalah untuk mengembangkan dan membangun sistem rekomendasi yang memanfaatkan teknik MCDM, khususnya metode ELCTRE, yang merupakan singkatan dari Elimination and Choice Translation Reality. Dengan menerapkan kriteria yang telah ditentukan sebelumnya pada serangkaian alternatif, pendekatan ini dapat memilih yang optimal. Tujuan dari pendekatan ini adalah untuk membantu siswa mencapai potensi penuh mereka dengan merekomendasikan kegiatan ekstrakurikuler yang relevan dan akurat.
Kata kunci: sistem pendukung keputusan; kegiatan ekstrakurikuler; potensi siswa; MCDM; metode ELECTRE
Abstract:Abstract: In this study, an analysis of the use of the Naive Bayes algorithm for sentiment analysis of reviews from Shopee app users on the Google Play Store was conducted, with classification divided into three categories:…
es: positive, negative, and neutral. To improve data quality, a preprocessing process was carried out with stages of cleaning, case folding, normalization, stop word removal, stemming, and tokenizing. Next, the text is formatted using the TF-IDF method to facilitate classification. For this data, the Naive Bayes model is used, which has an accuracy rate of 87% in detecting sentiment. Positive and negative categories can be easily identified compared to neutral sentiments due to the smaller amount of neutral data. Overall, the Naive Bayes algorithm successfully analyzed user sentiments well. The research can be developed with other algorithm methods, such as SVM, K-NN, or Decision Tree, in order to compare the performance of various algorithms.
Keywords: sentiment analysis; naive bayes; user reviews; e-commerce; shopee
Abstrak: Dalam penelitian ini dilakukan analisis penggunaan algoritma Naive Bayes untuk analisis sentimen review dari pengguna aplikasi Shopee di Google Play Store, klasifikasi dibagai menjadi 3 kategori yaitu positif, negatif, dan netral. Untuk meningkatkan kualitas data, dilakukam proses preprocessing dengan tahap cleanimg, case folding, normalisasi, stopword removal, stemming, dan tekonezing. Selanjutnya, teks diformat menggunakan metode TF-IDF untuk memudahkan klasifikasi. Untuk data ini, model Naive Bayes digunakan, yang memiliki tingkat akurasi 87% dalam mendeteksi sentimen. Kategori positif dan negatif dapat dengan mudah diidentifikasi dibadingkan sentiemen netral karena jumlah data netral yang lebih sedikit. Secara keseluruhan, algoritma Naive Bayes berhasil menganalisis perasaan pengguna dengan baik. Penelitian dapat dikembangkan dengan algoritma metode lain, seperti SVM, K-NN, atau Decision Tree, guna membandingkan kinerja berbagai algoritma.
Kata kunci: analisis sentiment; naive bayes; ulasan pengguna; e-commerce; shopee