Abstract:Perkembangan pesat teknologi Artificial Intelligence (AI) telah mengubah lanskap pendidikan tinggi secara signifikan, terutama dengan hadirnya tutor virtual berbasis AI yang mampu memberikan umpan balik cepat, tepat, dan…
personal. Analisis Real merupakan salah satu mata kuliah yang paling menantang dalam program pendidikan matematika karena sifat abstraknya sering menyebabkan rendahnya self-efficacy mahasiswa. Penelitian ini bertujuan menganalisis pengaruh pemanfaatan AI sebagai tutor virtual terhadap self-efficacy mahasiswa Pendidikan Matematika Universitas Asahan yang menempuh mata kuliah Analisis Real. Penelitian menggunakan pendekatan kuantitatif dengan desain quasi-experimental one-group pretest-posttest, melibatkan 15 mahasiswa yang dipilih melalui purposive sampling. Instrumen angket self-efficacy dikembangkan berdasarkan tiga dimensi Bandura (magnitude, strength, generality), divalidasi melalui expert judgment dengan Cronbach’s Alpha sebesar 0,84. Hasil analisis deskriptif menunjukkan peningkatan rata-rata skor self-efficacy dari 65,67 (pre-test, kategori sedang) menjadi 79,93 (post-test, kategori tinggi), dengan peningkatan sebesar 21,7%. Uji Wilcoxon Signed-Rank Test menghasilkan nilai Z = −3,408 dengan p-value = 0,001 (p < 0,05), yang mengkonfirmasi terdapat perbedaan signifikan self-efficacy mahasiswa sebelum dan sesudah intervensi enam minggu menggunakan AI tutor virtual.
The rapid development of Artificial Intelligence (AI) technology has significantly transformed higher education, particularly through AI-based virtual tutors capable of providing fast, precise, and personalized feedback. Real Analysis, one of the most challenging mathematics education courses, frequently causes low self-efficacy among students due to its abstract nature and demands for formal proof-writing. This study examines the effect of utilizing AI as a virtual tutor on self-efficacy of mathematics education students at Universitas Asahan. A quantitative quasi-experimental one-group pretest-posttest design was employed with 15 students selected via purposive sampling. The self-efficacy questionnaire was based on Bandura’s three dimensions: magnitude, strength, and generality, validated by expert judgment with Cronbach’s Alpha coefficient of 0.84. Descriptive analysis results showed an increase in mean self-efficacy scores from 65.67 (pre-test, moderate category) to 79.93 (post-test, high category), representing a 21.7% improvement. The Wilcoxon Signed-Rank Test yielded Z = −3.408 with p-value = 0.001 (p < 0.05), confirming a significant difference in student self-efficacy before and after the six-week AI virtual tutor intervention.
Abstract:Sekretariat DPRD Provinsi Jambi masih menggunakan sistem manual dalam pengelolaan surat masuk dan surat keluar sehingga proses pencatatan, pencarian, dan penyusunan laporan kurang efisien. Penelitian ini bertujuan merancang…
ang Sistem Informasi Manajemen Surat Berbasis Web menggunakan metode pengembangan Waterfall. Perancangan sistem dilakukan menggunakan Unified Modeling Language (UML), sedangkan implementasi sistem menggunakan Framework Laravel. Hasil penelitian menunjukkan bahwa sistem yang dirancang mampu mendukung pengelolaan surat masuk dan keluar, pengarsipan dokumen, pencarian data, serta penyajian laporan secara lebih cepat, efektif, dan akurat.
The Secretariat of DPRD Jambi Province still uses a manual system for managing incoming and outgoing mail, resulting in inefficient recording, retrieval, and reporting processes. This study aims to design a web-based mail management information system using the Waterfall software development method. The system was designed using Unified Modeling Language (UML) and implemented using the Laravel Framework. System design employed Unified Modeling Language (UML), while implementation was carried out using the Laravel Framework. The results show that the proposed system supports mail management, document archiving, data retrieval, and report generation more quickly, effectively, and accurately.
Abstract:Dinas Perhubungan Provinsi Jambi saat ini menggunakan aplikasi absensi berbasis mobile yang diterapkan secara terpusat di lingkungan Pemerintah Provinsi Jambi. Namun, sistem tersebut masih memiliki keterbatasan dalam pengelolaan…
gelolaan data absensi dan laporan internal. Penelitian ini bertujuan merancang Sistem Informasi Absensi Kepegawaian berbasis website menggunakan metode Prototype. Perancangan sistem dilakukan dengan Use Case Diagram dan Activity Diagram. Hasil penelitian menunjukkan bahwa sistem mampu mendukung absensi masuk dan pulang, pengelolaan data pegawai, rekapitulasi kehadiran, serta penyajian laporan secara lebih efektif dan terintegrasi.
The Jambi Provincial Transportation Agency currently uses a centralized mobile-based attendance application. However, the system still has limitations in managing attendance data and internal reports. This study aims to design a web-based Employee Attendance Information System using the Prototype method. The system was modeled using Use Case Diagrams and Activity Diagrams. The results show that the system supports employee check-in and check-out processes, employee data management, attendance recapitulation, and reporting more effectively and in an integrated manner.
Abstract:Dinas Perhubungan Provinsi Jambi masih menghadapi kendala dalam pengelolaan surat masuk, surat keluar, dan disposisi yang dilakukan secara konvensional sehingga kurang efisien dan berisiko menimbulkan penumpukan dokumen.…
Penelitian ini bertujuan merancang Sistem Informasi Persuratan berbasis website untuk meningkatkan efektivitas pengelolaan administrasi. Sistem dikembangkan menggunakan metode Prototype dengan pemodelan Use Case Diagram dan Activity Diagram. Hasil penelitian menunjukkan bahwa sistem mampu mempermudah pengelolaan surat, disposisi digital, pengarsipan dokumen, serta penyampaian informasi secara lebih cepat dan terintegrasi.
The Jambi Provincial Transportation Agency still faces challenges in managing incoming mail, outgoing mail, and dispositions through conventional processes, resulting in inefficiency and document accumulation risks. This study aims to design a web-based Correspondence Information System to improve administrative management effectiveness. The system was developed using the Prototype method and modeled with Use Case Diagrams and Activity Diagrams. The results show that the system facilitates correspondence management, digital disposition, document archiving, and information delivery in a faster and more integrated manner.
Abstract:Komisi Informasi Provinsi Jambi masih menggunakan proses pendaftaran sengketa informasi publik secara manual sehingga menyebabkan keterlambatan pelayanan, risiko kehilangan berkas, dan kesulitan dalam pengelolaan data. Penelitian…
enelitian ini bertujuan merancang Sistem Informasi Pendaftaran Sengketa Informasi Berbasis Website untuk mempermudah masyarakat dalam mengajukan permohonan sengketa secara daring. Metode pengembangan yang digunakan adalah Waterfall yang meliputi analisis kebutuhan, perancangan, implementasi, dan pengujian. Sistem dirancang menggunakan PHP, MySQL, dan pemodelan UML. Hasil penelitian menunjukkan bahwa sistem mampu mempermudah proses pendaftaran, pengelolaan data, serta pemantauan status permohonan secara lebih efektif dan efisien.
The Information Commission of Jambi Province still uses a manual public information dispute registration process, resulting in service delays, risk of document loss, and difficulties in data management. This study aims to design a web-based information dispute registration system to facilitate online application submissions. The system was developed using the Waterfall method, which includes requirements analysis, design, implementation, and testing stages. The application was designed using PHP, MySQL, and UML modeling. The results show that the system simplifies the registration process, data management, and application status monitoring more effectively and efficiently.
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:Masalah pengelolaan parkir di Politeknik Jambi sering menyebabkan ketidakefisienan akibat sistem penghitungan manual yang rentan human error. Penelitian ini bertujuan merancang sistem penghitungan kendaraan otomatis berbasis…
asis pengolahan citra digital. Metode yang digunakan adalah Background Subtraction dengan algoritma MOG2 dan OpenCV menggunakan video kamera smartphone. Sistem mengintegrasikan proses preprocessing citra, operasi morfologi, dan Euclidean Distance Tracker untuk melacak serta menghitung kendaraan secara real-time. Hasil penelitian menunjukkan sistem mampu membedakan kendaraan yang bergerak dengan objek statis secara akurat melalui Virtual Counting Line. Dengan beban komputasi yang ringan dan biaya rendah, sistem ini efektif menjadi solusi otomatisasi manajemen parkir di lingkungan kampus.
Parking management issues at Politeknik Jambi often lead to inefficiencies due to manual counting systems prone to human error. This study aims to design an automatic vehicle counting system based on digital image processing. The method utilizes Background Subtraction with the MOG2 algorithm and OpenCV using smartphone video input. The system integrates image preprocessing, morphological operations, and Euclidean Distance Tracker to track and count vehicles in real-time. The results demonstrate that the system can accurately distinguish between moving vehicles and static objects via a Virtual Counting Line. With low computational requirements and cost-effectiveness, this system offers an efficient automation solution for campus parking management.
Abstract:Emas merupakan salah satu jenis komoditi yang paling banyak diminati untuk tujuan investasi, karena dipandang sebagai instrumen yang lebih aman dibandingkan saham serta memiliki nilai jual yang selalu bergerak mengikuti…
kondisi pasar. PT Victoeria Vici, sebagai pelaku usaha perhiasan emas custom, menghadapi kendala dalam menentukan estimasi harga jual kepada pelanggan, sebab proses pengerjaan pesanan custom membutuhkan waktu hingga 14 hari, sementara harga emas bergerak fluktuatif dan tidak terstruktur setiap harinya sehingga estimasi harga menjadi tidak akurat dan tidak efektif. Berdasarkan permasalahan tersebut, penelitian ini menerapkan konsep Data Mining dengan algoritma Trend Moment untuk mengestimasi harga emas pada rentang waktu tertentu. Data yang digunakan merupakan data historis harga emas per gram pada PT Victoeria Vici periode Agustus–Oktober 2021 sebanyak 92 data. Tahapan penelitian meliputi pengumpulan data, penentuan variabel X dan Y, eliminasi untuk memperoleh nilai konstanta a dan slope b, serta penerapan persamaan Y = a + bX untuk memperoleh nilai estimasi. Hasil perhitungan menunjukkan nilai a = 720.871,725 dan b = 3,108 sehingga model estimasi mampu menghasilkan proyeksi harga emas yang mendekati pola data historis. Model ini kemudian diimplementasikan ke dalam aplikasi berbasis desktop menggunakan Microsoft Visual Basic 2010 dan basis data Microsoft Access, dilengkapi Crystal Report untuk pencetakan laporan hasil estimasi. Hasil penelitian menunjukkan bahwa algoritma Trend Moment dapat membantu PT Victoeria Vici dalam memperoleh estimasi harga emas secara lebih cepat, konsisten, dan terdokumentasi.
Gold is one of the most sought-after commodities for investment purposes, as it is regarded as a safer instrument compared to stocks and has a selling value that constantly fluctuates with market conditions. PT Victoeria Vici, a custom gold jewelry business, faces difficulty in determining the estimated selling price offered to customers because the production process for custom orders takes up to 14 days, while gold prices move in an unstructured and fluctuating manner every day, making manual price estimation inaccurate and ineffective. Based on this problem, this study applies the concept of Data Mining using the Trend Moment algorithm to estimate gold prices over a certain period of time. The data used is historical daily gold price data per gram from PT Victoeria Vici for the period of August–October 2021, consisting of 92 records. The research stages include data collection, determination of the X and Y variables, elimination to obtain the constant value a and the slope b, and the application of the equation Y = a + bX to obtain the estimated value. The calculation results show a value of a = 720,871.725 and b = 3.108, so that the estimation model is able to produce gold price projections that closely follow the pattern of historical data. This model was then implemented into a desktop-based application using Microsoft Visual Basic 2010 and a Microsoft Access database, equipped with Crystal Report for printing estimation result reports. The results show that the Trend Moment algorithm can help PT Victoeria Vici obtain gold price estimations more quickly, consistently, and in a well-documented manner.
Abstract:Promosi penerimaan mahasiswa baru (PMB) merupakan salah satu faktor penting dalam meningkatkan jumlah dan kualitas calon mahasiswa. Namun, strategi promosi yang belum memanfaatkan data historis secara optimal dapat menyebabkan…
babkan kegiatan promosi kurang tepat sasaran. Penelitian ini bertujuan untuk menganalisis data historis PMB sebagai dasar dalam menyusun strategi promosi yang lebih efektif pada Jurusan Teknologi Informasi dan Komputer Politeknik Negeri Lhokseumawe. Penelitian menggunakan pendekatan kuantitatif deskriptif dengan memanfaatkan data sekunder PMB periode 2023–2025. Analisis dilakukan melalui tahapan data cleaning, transformasi data, statistik deskriptif, segmentasi calon mahasiswa, dan visualisasi data menggunakan dashboard analitik. Variabel yang dianalisis meliputi program studi, asal sekolah, jurusan asal sekolah, kecamatan, kabupaten/kota, provinsi, jalur masuk, dan sumber informasi pendaftar. Hasil penelitian menunjukkan bahwa sebagian besar pendaftar berasal dari Provinsi Aceh, khususnya Kabupaten Aceh Utara dan Kota Lhokseumawe, dengan dominasi lulusan jurusan IPA serta peminat terbesar pada Program Studi Teknik Informatika. Instagram dan website menjadi sumber informasi utama bagi calon mahasiswa. Pemanfaatan data historis melalui visualisasi data mampu memberikan informasi yang lebih komprehensif mengenai karakteristik calon mahasiswa sehingga dapat mendukung pengambilan keputusan dalam penyusunan strategi promosi PMB yang lebih terarah, efektif, dan berbasis data.
New student admissions (PMB) promotion is an important factor in increasing the number and quality of prospective students. However, promotional strategies that do not optimally utilize historical data can result in less targeted promotional activities. This study aims to analyze historical PMB data as a basis for developing a more effective promotional strategy in the Information and Computer Technology Department of the Lhokseumawe State Polytechnic. The study uses a descriptive quantitative approach utilizing secondary PMB data for the 2023–2025 period. The analysis was carried out through the stages of data cleaning, data transformation, descriptive statistics, prospective student segmentation, and data visualization using an analytical dashboard. The variables analyzed included study program, school of origin, major of origin of school, sub-district, regency/city, province, admission route, and applicant information sources. The results show that most applicants come from Aceh Province, especially North Aceh Regency and Lhokseumawe City, with a predominance of science graduates and the greatest interest in the Informatics Engineering Study Program. Instagram and websites are the main sources of information for prospective students. The use of historical data through data visualization can provide more comprehensive information regarding the characteristics of prospective students so that it can support decision-making in developing more targeted, effective, and data-based PMB promotion strategies.
Abstract:This study aims to determine the effect of using Google Earth media through the Contextual Teaching and Learning (CTL) model on the learning outcomes of social studies on natural phenomena material for fifth-grade students…
ts of SDN Telang 2 in the 2026/2027 academic year. The study used a quantitative approach with the Pre-Experimental Design method and One Group Pretest-Posttest Design. The research subjects were 17 students. Data collection techniques were carried out through tests, observations, and documentation. The research instrument was a multiple-choice test given before and after treatment. Data were analyzed using descriptive statistics and paired sample t-test. The results showed that the average pretest score of 68.82 increased to 79.41 in the posttest, with an increase of 10.59 points. The results of the paired sample t-test showed a significance value (2-tailed) of 0.000 <0.05, so H₀ was rejected and H₁ was accepted. These findings indicate that the use of Google Earth media through the CTL model has a significant effect on the learning outcomes of social studies on natural phenomena material. The integration of Google Earth and CTL provides a more contextual, interactive, and meaningful learning experience, helping students understand the concept of natural features more concretely. Therefore, Google Earth, through the CTL model, can be used as an alternative media and effective learning model to improve social studies learning outcomes in elementary schools.
Penelitian ini bertujuan untuk mengetahui pengaruh penggunaan media Google Earth melalui model Contextual Teaching and Learning (CTL) terhadap hasil belajar IPS materi kenampakan alam pada siswa kelas V SDN Telang 2 Tahun Pelajaran 2026/2027. Penelitian menggunakan pendekatan kuantitatif dengan metode Pre-Experimental Design dan desain One Group Pretest-Posttest Design. Subjek penelitian berjumlah 17 siswa. Teknik pengumpulan data dilakukan melalui tes, observasi, dan dokumentasi. Instrumen penelitian berupa tes pilihan ganda yang diberikan sebelum dan sesudah perlakuan. Data dianalisis menggunakan statistik deskriptif dan uji paired sample t-test. Hasil penelitian menunjukkan bahwa nilai rata-rata pretest sebesar 68,82 meningkat menjadi 79,41 pada posttest, dengan peningkatan sebesar 10,59 poin. Hasil uji paired sample t-test menunjukkan nilai signifikansi (2-tailed) sebesar 0,000 < 0,05, sehingga H₀ ditolak dan H₁ diterima. Temuan ini menunjukkan bahwa penggunaan media Google Earth melalui model CTL berpengaruh signifikan terhadap hasil belajar IPS materi kenampakan alam. Integrasi Google Earth dan CTL mampu memberikan pengalaman belajar yang lebih kontekstual, interaktif, dan bermakna sehingga membantu siswa memahami konsep kenampakan alam secara lebih konkret. Oleh karena itu, Google Earth melalui model CTL dapat dijadikan alternatif media dan model pembelajaran yang efektif untuk meningkatkan hasil belajar IPS di sekolah dasar.