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Showing 615 articles found for "Quantitative"

Sosialisasi Ilmu Statistik dalam Penelitian Bagi Mahasiswa Di Kota Palembang

Ulum, Muhammad Bahrul, Syaputri, Ayu Geby Gisela
Abstract: Abstract: Statistics and research are two things that cannot be separated. Although there are types of research that do not require the dominant role of statistics (qualitative research), but to be able to produce conclusions… sions that can be generalized to a wider population, statistics is needed. Such research is quantitative research with a positivistic paradigm, ie a phenomenon is real if it can be seen, measured, and classified. The application of statistical science which is generally needed by students in writing research such as theses and theses, will have a positive impact, especially in improving the quality of the research. To achieve this goal, it is necessary to conduct socialization to students. The socialization was carried out to several students from both state universities and private universities in the city of Palembang. The socialization was done by introducing and giving tutorials on how to use statistical applications such as SPSS and Eviews, because several lecturers at several universities in Palembang complained about the poor quality of research and some said that their students did not really understand how to use SPSS and Eviews. The first result of this service is that students' understanding of SPSS and Eviews can be seen from discussions and questions and answers, second, namely the ability of students to apply the use of SPSS and Eviews in research. Keywords: research; socialization; statistics Abstrak: Statistik dan penelitian merupakan dua hal yang tidak bisa dipisahkan. Meskipun ada jenis penelitian yang tidak membutuhkan peranan statistika yang dominan (penelitian kualitatif), namun untuk dapat menghasilkan kesimpulan yang dapat digeneralisasikan ke populasi yang lebih luas diperlukan ilmu statistika. Penelitian yang demikian adalah penelitian kuantitatif dengan paradigma yang positivistik, yakni suatu gejala itu adalah nyata jika bisa dilihat, diukur, dan diklasifikasikan. Penerapan ilmu statistik yang umumnya dibutuhkan mahasiswa dalam penulisan penelitian seperti skripsi dan tesis, akan berdampak positif terutama dalam meningkatan kualitas penelitian tersebut. Untuk mencapai tujuan tersebut maka perlu diadakan sosialisasi kepada mahasiswa. Sosialisasi dilakukan pada beberapa mahasiswa baik dari perguruan tinggi negeri maupun perguruan tinggi swasta di Kota Palembang. Sosialisasi dilakukan dengan cara mengenalkan dan memberikan tutorial bagaimana penggunaan aplikasi statistic seperti, SPSS dan Eviews, karena beberapa dosen di beberapa universitas di Palembang mengeluhkan buruknya kualitas penelitian dan ada juga yang mengatakan bahwa mahasiswa mereka tidak begitu mengerti cara penggunaan SPSS dan Eviews. Hasil dari pengabdian ini yang pertama adalah pemahaman mahasiswa mengenai SPSS dan Eviews dapat dilihat dari diskusi dan tanya jawab, kedua yaitu kemampuan mahasiswa dalam menerapkan penggunaan SPSS dan Eviews dalam penelitian. Kata Kunci: penelitian; sosialisasi; statistik

PEMBELAJARAN BUTA AKSARA BERBASIS INOVASI DI DESA AIR HITAM

Putra, Anshari
Abstract: Abstract: Literacy education is education for anyone who is illiterate, whether children or parents or even the elderly. What must be considered in this matter is that literacy education is a very sensitive education, an… attitude that seems to be patronizing tends to be responded negatively. They tend to avoid, reject and feel offended when treated like children. They will reject learning situations that conflict with their self-concept as independent individuals. the method is carried out after observation and study of the material, the results achieved after the presentation of the material read, write, count are quantitative results. The ability of citizens to learn after functional literacy learning in the advanced literacy sector was assessed in the good category. This can be seen from the results that show that the results obtained by residents from those who are not yet fluent in reading, writing, and arithmetic, are now fluent in reading, writing, and arithmetic. Keywords: illiterate Abstrak: Pendidikan keaksaraan merupakan pendidikan bagi siapa saja yang menyandang buta aksara, baik anak-anak maupun orang tua atau lansia sekalipun. Harus diperhatikan dalam persoalan ini adalah pendidikan keaksaraan merupakan pendidikan yang sangat sensitif, sikap yang terkesan menggurui cenderung ditanggapi negative. Mereka cenderung menghindar, menolak dan merasa tersinggung apabila diperlakukan seperti anak-anak. Mereka akan menolak situasi belajar yang bertentangan dengan konsep dirinya sebagai individu yang mandiri. metode yang dilakukan setelah observasi dan pengajian materi, maka hasil yang dicapai setelah penyajian materi baca, tulis, hitung ialah hasil secara kuantitaif. Kemampuan warga belajar setelah pembelajaran keaksaraan fungsional bidang buta aksara lanjutan dinilai dalam kategori baik. Hal ini dapat dilihat dari hasil yang menunjukkan bahwa hasil yang diperoleh oleh warga dari yang belum lancar membaca, menulis, dan berhitung, sekarang menjadi lancar membaca, menulis, dan berhitung. Kata kunci: buta aksara

ANALYSIS OF MAXIM APPLICATION ACCEPTANCE AND SATISFACTION USING THE UTAUT2 MODEL IN MANOKWARI

Tedang, Vilna Wati, Marini, Lion Ferdinand, Kweldju, Alex De
Abstract: Abstract: The increasing use of the Maxim ride-hailing application in Manokwari highlights the need to understand the factors influencing user acceptance and satisfaction. However, the growing number of users does not necessarily&#8230; cessarily reflect a high level of technology acceptance and user satisfaction. This study aims to examine the effects of performance expectancy, effort expectancy, facilitating conditions, and habit on behavioral intention, as well as the effect of behavioral intention on user satisfaction among Maxim users in Manokwari. A quantitative approach based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed. Data were collected through questionnaires using a purposive sampling technique from 156 valid respondents and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The results show that performance expectancy (β = 0.343, p < 0.001), effort expectancy (β = 0.191, p = 0.002), facilitating conditions (β = 0.142, p = 0.029), and habit (β = 0.359, p < 0.001) positively and significantly influence behavioral intention. Furthermore, behavioral intention positively and significantly affects user satisfaction (β = 0.771, p < 0.001). These findings confirm the applicability of the UTAUT2 model and provide practical insights for Maxim management and application developers to improve service quality and user satisfaction.   Keywords: behavioral intention; effort expectancy; facilitating conditions; habit; performance expectancy; user satisfaction.     Abstrak: Meningkatnya penggunaan aplikasi transportasi daring Maxim di Manokwari mendorong perlunya memahami faktor-faktor yang memengaruhi penerimaan teknologi dan kepuasan pengguna. Namun, peningkatan jumlah pengguna belum tentu mencerminkan tingginya tingkat penerimaan teknologi dan kepuasan pengguna. Penelitian ini bertujuan menganalisis pengaruh performance expectancy, effort expectancy, facilitating conditions, dan habit terhadap behavioral intention, serta pengaruh behavioral intention terhadap user satisfaction pada pengguna aplikasi Maxim di Manokwari. Penelitian ini menggunakan pendekatan kuantitatif berdasarkan model Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Data dikumpulkan melalui kuesioner menggunakan teknik purposive sampling terhadap 156 responden dan dianalisis menggunakan Partial Least Squares Structural Equation Modeling (PLS-SEM) dengan SmartPLS 4.0. Hasil penelitian menunjukkan bahwa performance expectancy (β = 0,343; p < 0,001), effort expectancy (β = 0,191; p = 0,002), facilitating conditions (β = 0,142; p = 0,029), dan habit (β = 0,359; p < 0,001) berpengaruh positif dan signifikan terhadap behavioral intention. Selanjutnya, behavioral intention berpengaruh positif dan signifikan terhadap user satisfaction (β = 0,771; p < 0,001). Temuan ini menegaskan penerapan model UTAUT2 serta memberikan masukan bagi manajemen Maxim dan pengembang aplikasi untuk meningkatkan kualitas layanan dan kepuasan pengguna.   Kata kunci: behavioral intention; effort expectancy; facilitating conditions; habit; performance expectancy; user satisfaction.  

ANALYSIS OF USER EXPERIENCE OF THE M-TIX APPLICATION IN MANOKWARI REGENCY USING THE UEQ AND TAM METHODS

Ikawanti, Fellisia ayu, Leonardo Sumendap, Andreas, Juita, Ratna
Abstract: Abstract: Digital technology has expanded the usage of mobile apps like M-Tix for movie ticket booking. The success of an app depends on its features, user experience, and technical acceptability. The User Experience Questionnaire&#8230; stionnaire (UEQ) and Technology acceptability Model (TAM) will be used to examine how user experience affects technology acceptability and M-Tix application usage in Manokwari Regency. Quantitative methods were used with 149 respondents. SmartPLS 4 was used to analyse data using PLS-SEM. Researchers found that Hedonic Quality positively impacts Perceived Usefulness (β=0.288; p=0.005). Pragmatic Quality significantly impacts Perceived Ease of Use (β=0.651; p<0.001) and Usefulness (β=0.372; p=0.002). Additionally, Perceived Ease of Use (β=0.180; p=0.043) and Usefulness (β=0.453; p<0.001) favourably impact Behavioural Intention. However, Perceived Ease of Use does not substantially impact Perceived Usefulness (β=0.105; p=0.265). These data show that user experience is crucial to technological adoption and M-Tix application usage.   Keywords: m-tix; PLS-SEM; technology acceptance model (TAM); user experience; user experience questionnaire (UEQ).   Abstrak: Teknologi digital telah memperluas penggunaan aplikasi seluler seperti M-Tix untuk pemesanan tiket film. Keberhasilan suatu aplikasi bergantung pada fitur-fiturnya, pengalaman pengguna, dan penerimaan teknis. Kuesioner Pengalaman Pengguna (UEQ) dan Model Penerimaan Teknologi (TAM) akan digunakan untuk meneliti bagaimana pengalaman pengguna memengaruhi penerimaan teknologi dan penggunaan aplikasi M-Tix di Kabupaten Manokwari. Metode kuantitatif digunakan dengan 149 responden. SmartPLS 4 digunakan untuk menganalisis data menggunakan PLS-SEM. Peneliti menemukan bahwa Kualitas Hedonik berdampak positif pada Kegunaan yang Dirasakan (β=0,288; p=0,005). Kualitas Pragmatis berdampak signifikan pada Kemudahan Penggunaan yang Dirasakan (β=0,651; p<0,001) dan Kegunaan (β=0,372; p=0,002). Selain itu, Kemudahan Penggunaan yang Dirasakan (β=0,180; p=0,043) dan Kegunaan (β=0,453; p<0,001) berdampak positif terhadap Niat Perilaku. Namun, Kemudahan Penggunaan yang Dirasakan tidak berdampak signifikan terhadap Kegunaan yang Dirasakan (β=0,105; p=0,265). Data ini menunjukkan bahwa pengalaman pengguna sangat penting untuk adopsi teknologi dan penggunaan aplikasi M-Tix.   Kata kunci: m-tix; PLS-SEM; technology acceptance model (TAM); user experience; user experience questionnaire (UEQ).

COMPARATIVE ANALYSIS OF B-TREE AND HASH INDEXES FOR POSTGRESQL QUERY OPTIMIZATION

Ramdhani, Angga, Widodo, Suprih
Abstract: Abstract: Query performance is a critical factor in managing large-scale databases. One of the most widely used optimization techniques is indexing. This study aims to analyze the impact of indexing on query performance&#8230; in PostgreSQL, compare the effectiveness of B-Tree and Hash indexes, and evaluate their influence on query planner decisions. A quantitative experimental approach was employed using the TPC-H benchmark dataset at scale factors SF0.1, SF1, and SF10. Experiments were conducted using EXPLAIN ANALYZE on exact match, range, and join queries under three conditions: without indexing, with B-Tree indexing, and with Hash indexing. The results demonstrate that indexing significantly improves query performance. For exact match queries on the SF10 dataset, execution time decreased from 93.36 ms without indexing to 0.034 ms using B-Tree and 0.045 ms using Hash indexes. For join queries, execution time was reduced from 857.77 ms to 0.180 ms using B-Tree and 0.079 ms using Hash indexes. B-Tree showed consistent performance across different query types, while Hash achieved the best results for equality-based queries. Furthermore, index usage influenced query planner decisions in selecting more efficient execution strategies. These findings indicate that appropriate index selection can substantially improve data access efficiency in PostgreSQL.        Keywords: b-tree index; hash index; PostgreSQL; query optimization; query planner     Abstrak: Performa query merupakan faktor penting dalam pengelolaan basis data berskala besar. Salah satu teknik optimasi yang umum digunakan adalah indexing. Penelitian ini bertujuan menganalisis pengaruh penggunaan indexing terhadap performa query pada PostgreSQL, membandingkan efektivitas B-Tree dan Hash index, serta mengevaluasi pengaruhnya terhadap keputusan query planner. Penelitian menggunakan metode eksperimen kuantitatif dengan dataset benchmark TPC-H pada skala SF0.1, SF1, dan SF10. Pengujian dilakukan menggunakan EXPLAIN ANALYZE pada exact match query, range query, dan join query dalam kondisi tanpa index, menggunakan B-Tree index, dan Hash index. Hasil penelitian menunjukkan bahwa indexing meningkatkan performa query secara signifikan. Pada exact match query dataset SF10, execution time menurun dari 93,36 ms tanpa index menjadi 0,034 ms menggunakan B-Tree dan 0,045 ms menggunakan Hash index. Pada join query, execution time berkurang dari 857,77 ms menjadi 0,180 ms menggunakan B-Tree dan 0,079 ms menggunakan Hash index. B-Tree menunjukkan performa yang konsisten pada berbagai jenis query, sedangkan Hash index memberikan performa terbaik pada query berbasis equality. Selain itu, penggunaan index memengaruhi keputusan query planner dalam memilih strategi eksekusi yang lebih efisien. Hasil penelitian menunjukkan bahwa pemilihan metode indexing yang tepat dapat meningkatkan efisiensi akses data pada PostgreSQL   Kata kunci: b-tree index; hash index; optimasi query; PostgreSQL; query planner

RANDOM FOREST BASED SYSTEM FOR PREDICTING AND RECOMMENDING INMATE REHABILITATION PROGRAMS

Syahrul Farhan, Nurul Rahmadani, Mardalius
Abstract: Abstract: Rehabilitation programs are essential in correctional systems to equip inmates with the skills and behavioral readiness required for social reintegration. However, rehabilitation program assignment in many correctional&#8230; ectional institutions remains dependent on manual and subjective assessments, which may result in inconsistent decisions. This study develops a Random Forest–based prediction system to support objective and data-driven rehabilitation program determination. A quantitative approach was applied using historical inmate data from January 2023 to January 2025, comprising 2,023 records. The research process included data preprocessing, an 80:20 training–testing split, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results show that the model achieved an accuracy of 86.17% during training in Google Colab and 68.83% when deployed within the application system. This performance gap reflects real-world deployment and computational constraints rather than model failure. The proposed system provides consistent and objective rehabilitation program recommendations, thereby supporting more effective rehabilitation planning and decision-making in correctional institutions. Keywords: correctional institutions; inmate rehabilitation programs; machine learning; random Forest; prediction system   Abstrak: Program pembinaan narapidana memiliki peran penting dalam sistem pemasyarakatan untuk membekali warga binaan dengan keterampilan serta kesiapan perilaku dalam proses reintegrasi ke masyarakat. Namun, pada banyak lembaga pemasyarakatan, penentuan program pembinaan masih bergantung pada penilaian manual yang bersifat subjektif, sehingga berpotensi menimbulkan ketidakkonsistenan dalam pengambilan keputusan. Penelitian ini mengembangkan sistem prediksi program pembinaan narapidana berbasis algoritma Random Forest guna mendukung pengambilan keputusan yang objektif dan berbasis data. Pendekatan kuantitatif diterapkan menggunakan data historis narapidana periode Januari 2023 hingga Januari 2025 sebanyak 2.023 data. Tahapan penelitian meliputi prapemrosesan data, pembagian data latih dan uji dengan rasio 80:20, pelatihan model, serta evaluasi performa menggunakan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model mencapai akurasi sebesar 86,17% pada tahap pelatihan di Google Colab dan 68,83% saat diimplementasikan pada sistem aplikasi. Perbedaan performa tersebut mencerminkan keterbatasan lingkungan operasional, bukan kegagalan model. Secara keseluruhan, sistem yang dikembangkan mampu memberikan rekomendasi program pembinaan yang lebih objektif dan konsisten, sehingga mendukung perencanaan pembinaan yang lebih efektif. Kata kunci: mesin pembelajaran; program pembinaan narapidana; random Forest; sistem pemasyarakatan; sistem prediksi

DIGITAL IMAGE QUALITY OPTIMIZATION USING DEEP NEURAL NETWORK

Arifanto, Bachtiar, Abdul Chamid , Ahmad, Nindyasari , Ratih
Abstract: Abstract: One of the main challenges in digital image processing is limited resolution, which makes it difficult to preserve visual details when images are enlarged. Conventional methods such as Bilinear Interpolation are&#8230; e commonly used for image upscaling; however, these approaches often produce blurred images, lose fine textures, and fail to reconstruct complex visual structures. This study aims to enhance digital image resolution by employing a deep learni based approach using a Low-Light Convolutional Neural Network (LLCNN) built upon a Deep Neural Network (DNN) architecture. The dataset used in this study is the DIV2K dataset, which consists of 1,000 high-resolution images. These images were downsampled using scaling factors of ×2, ×3, and ×4 to generate paired Low Resolution–High Resolution (LR–HR) data for training and evaluation. The proposed LLCNN is designed to extract important features such as edges, textures, and local patterns through multiple convolutional layers, followed by non-linear mapping to reconstruct high-resolution images more accurately. Quantitative performance evaluation was conducted using the Peak Signal-to-Noise Ratio (PSNR) and the Structural Similarity Index (SSIM). Model performance was evaluated quantitatively using the Peak Signal-to-Noise Ratio (PSNR) metric. Experimental results showed that the proposed method improved image quality compared to the bilinear method. These results indicate that the deep learning based approach effectively improves image sharpness and structural fidelity, thereby demonstrating its potential for digital image resolution enhancement.             Keywords: deep neural network; image resolution; low-light convolutional neural network; machine learning   Abstrak: Permasalahan utama dalam pengolahan citra digital adalah keterbatasan resolusi yang menyebabkan detail visual sulit dipertahankan ketika citra diperbesar. Metode konvensional seperti Bilinear Interpolation masih banyak digunakan, namun sering menghasilkan citra buram, kehilangan tekstur halus, serta tidak mampu merekonstruksi struktur visual yang kompleks. Penelitian ini bertujuan untuk meningkatkan kualitas resolusi citra digital dengan memanfaatkan pendekatan deep learning berbasis Low-Light Convolutional Neural Network (LLCNN) yang dibangun di atas arsitektur Deep Neural Network (DNN). Data yang digunakan dalam penelitian ini berasal dari dataset DIV2K, yang terdiri dari 1000 citra beresolusi tinggi. Citra tersebut diturunkan menjadi resolusi rendah menggunakan faktor downsampling ×2, ×3, dan ×4 untuk membentuk pasangan data Low Resolution–High Resolution (LR–HR) sebagai data pelatihan dan pengujian. LLCNN dirancang untuk mengekstraksi fitur-fitur penting seperti tepi, tekstur, dan pola lokal melalui beberapa lapisan konvolusi, kemudian melakukan pemetaan non-linear guna merekonstruksi citra resolusi tinggi secara lebih presisi. Evaluasi performa model dilakukan secara kuantitatif menggunakan metrik Peak Signal-to-Noise Ratio (PSNR). Hasil eksperimen menunjukkan bahwa metode yang diusulkan mampu meningkatkan kualitas citra dibandingkan metode bilinear. Hasil ini membuktikan bahwa pendekatan berbasis deep learning efektif dalam meningkatkan ketajaman dan kesesuaian struktur citra digital.   Kata kunci: deep neural network; low-light convolutional neural network; machine learning; resolusi citra

ANALYZING STUDENTS’ EXPERIENCE IN LMS SPOT UPI USING THE UEQ

Azhari, Fairuz Azka, Asep Nuryadin, Muhammad Dzikri Ar Ridlo
Abstract: Abstract: The rapid expansion of digital learning environments has increased students’ reliance on Learning Management Systems (LMS), including SPOT UPI. However, limited studies have examined the platform’s overall user&#8230; user experience across all User Experience Questionnaire (UEQ) dimensions. This study aims to evaluate the user experience (UX) of SPOT UPI, identify its strengths and weaknesses, and provide recommendations for system improvement. A quantitative-dominant mixed-method design was applied, involving 81 student respondents for the UEQ survey and two participants for follow-up semi-structured interviews selected through purposive sampling. The UEQ data were analyzed to generate mean scores for six UX dimensions, while interview data were thematically analyzed to support the interpretation of quantitative findings. The results indicate that Perspicuity (1.05) and Efficiency (0.78) achieved the highest scores, reflecting adequate clarity and functionality. In Contrast, Stimulation (0.50) and Novelty (-0.15) were the lowest, indicating limited engagement and innovation. Overall, pragmatic quality (0.84) outperformed hedonic quality (0.17), suggesting that users value functionality more than enjoyment. In conclusion, SPOT UPI is generally usable but lacks aesthetic appeal, emotional engagement, and innovative features, highlighting the need for interface redesign and performance optimization to enhance the overall learning experience.             Keywords: learning management system; user experience; user experience questionnaire     Abstrak: Perkembangan pembelajaran digital membuat mahasiswa semakin bergantung pada Learning Management System (LMS), termasuk SPOT UPI. Meski digunakan secara luas, evaluasi pengalaman pengguna secara komprehensif berdasarkan seluruh dimensi User Experience Questionnaire (UEQ) masih belum banyak dilakukan. Penelitian ini bertujuan untuk mengevaluasi user experience (UX) pada SPOT UPI, mengidentifikasi keunggulan dan kelemahannya, serta memberikan rekomendasi perbaikan sistem. Penelitian menggunakan desain penelitian mixed-method dominan kuantitatif, melibatkan 81 responden pada survei UEQ dan dua partisipan pada wawancara semi-terstruktur yang dipilih melalui purposive sampling. Data UEQ dianalisis untuk memperoleh nilai rata-rata pada enam dimensi UX, sedangkan data wawancara dianalisis secara tematik untuk memperkaya interpretasi temuan kuantitatif. Hasil menunjukkan bahwa Perspicuity (1,05) dan Efficiency (0,78) menjadi dimensi dengan skor tertinggi, mencerminkan bahwa SPOT UPI mudah dipahami dan cukup membantu dalam menyelesaikan tugas. Sebaliknya, Stimulation (0,50) dan Novelty (-0,15) memperoleh skor terendah, menandakan rendahnya tingkat keterlibatan dan inovasi yang dirasakan pengguna. Secara keseluruhan, pragmatic quality (0,84) lebih tinggi dibandingkan hedonic quality (0,17), menunjukkan bahwa pengguna lebih mengutamakan aspek fungsional daripada kenyamanan emosional. Temuan tersebut mengindikasikan bahwa SPOT UPI sudah layak digunakan secara fungsional, tetapi masih memerlukan peningkatan pada interface, pengalaman visual, dan fitur inovatif agar dapat memberikan pengalaman belajar digital yang lebih menarik dan optimal.   Kata kunci: learning management system; pengalaman pengguna; user experience questionnaire

ANALYSIS OF THE ACCEPTANCE OF THE SINAGA ATTENDANCE APPLICATION AT SMA NEGERI 1 JATILAWANG USING THE TECHNOLOGY ACCEPTANCE MODEL (TAM)

Sabaniyah, Arbangi Puput, Yunita, Ika Romadhoni, Subarkah, Pungkas
Abstract: This study analyzes the acceptance of teachers and ASN employees of the SINAGA (Sistem Informasi Layanan Kepegawaian) attendance application at SMA Negeri 1 Jatilawang using a modified Technology Acceptance Model (TAM).&#8230; The model was extended by incorporating two external variables: Information Quality and Complexity. This explanatory quantitative research employed the Structural Equation Modeling–Partial Least Square (SEM-PLS) method involving 60 respondents who are civil servants, consisting of teachers and administrative staff. The results reveal that Information Quality has a positive and significant influence on both Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), while Complexity does not show a significant effect on either variable. Furthermore, PEOU and PU have a positive impact on Attitude Toward Use (ATU), which subsequently affects Behavioral Intention to Use (BIU). Behavioral intention, in turn, strongly influences Actual Use (AU). These findings indicate that teachers’ acceptance of the SINAGA digital attendance system in educational settings is primarily driven by information quality and users’ positive attitudes rather than by system complexity. Theoretically, this study contributes to the expansion of TAM application in the educational context. Practically, it provides valuable insights for improving the effectiveness of SINAGA implementation through better information quality and enhanced user experience.         

INTEGRATED AHP-TOPSIS DECISION SYSTEM FOR FAIR STUDENT PERFORMANCE EVALUATION

Hafiz, Rahmad, Triyono, Gandung, Assegaf , Noval, Yasmin , Nadia, Effendi , Muhtar
Abstract: Giving awards is essential to motivate students; however, selecting outstanding students at the junior high school level is often conducted manually and subjectively, which can lead to unfairness and prolonged processing&#8230; time. This study develops a Decision Support System (DSS) that integrates the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to support objective and transparent student selection. A quantitative descriptive approach was employed, with data collected through questionnaires, interviews, and documentation at two state junior high schools in Banjarmasin City. Seven assessment criteria were applied: attendance, behavior, uniform neatness, extracurricular participation, academic grades, competition achievements, and disciplinary records. AHP was used to determine the weight of each criterion, while TOPSIS ranked students based on these weights. The web-based system was developed using PHP and MySQL and evaluated using the Technology Acceptance Model (TAM). Results show that academic grades had the highest weight (28.5%), followed by attendance (22.3%) and competition performance (15.2%). The TAM evaluation yielded average scores of 4.32 for Perceived Ease of Use, 4.40 for Perceived Usefulness, 4.15 for Attitudes Towards Use, and 4.28 for Behavioral Intention to Use. The DSS produces accurate rankings, is well-received by users, and offers an efficient, fair, and replicable solution for data-driven educational governance in the digital era.