Jurnal Teknik

Analisis Faktor Keamanan Tanggul Sungai dengan Perkuatan Turap Menggunakan Perangkat Lunak Geo5 di Desa Walangku Kabupaten Hulu Sungai Tengah

Humaira Afrila, Markawie, Wira Lianto (Author) — Mon, 01 Jun 2026 00:00:00 +0000

Walangku Village, Pemangkih District, Hulu Sungai Tengah Regency, is crossed by a river channel located adjacent to a local access road. The river embankment has experienced a landslide, posing a potential risk to public safety and the protective function of the surrounding area. One alternative to improve embankment stability is reinforcement using a sheet pile wall.

This study consisted of soil testing, stability analysis of the existing embankment, and stability analysis of the embankment with sheet pile reinforcement. Soil testing was conducted through field and laboratory investigations, including Standard Penetration Test (SPT), physical property testing, direct shear test and vane shear test. Embankment stability was analyzed using the Software Geo5. The test results indicate that the shallow soil layer has high water content, low shear strength, and soft soil conditions, which contribute to embankment instability. The stability analysis of the existing condition yielded a safety factor of 1.2, indicating that the embankment was unstable. After modeling the sheet pile reinforcement using the Software Geo5, the safety factor increased to 3.36, meeting the required safety criteria. These results show that sheet pile reinforcement is effective in improving embankment stability and may serve as an alternative solution for landslide mitigation at the study site.

Kelayakan Investasi pada Pengembangan Perumahan Permata Regency Lamongan

Cahyo Indra Irawan, Hammam Rofiqi Agustapraja, Samsul Arif (Author) — Mon, 01 Jun 2026 00:00:00 +0000

The growth in housing demand drives residential development, including Permata Regency Lamongan Housing, which faces location constraints in suburban areas and high investment costs. This study aims to analyze investment feasibility using Net Present Value (NPV), Internal Rate of Return (IRR), and Benefit-Cost Ratio (BCR) methods, as well as to determine the influence of location on consumer purchasing decisions. The study employs a quantitative approach utilizing primary data from questionnaires distributed to 33 respondents and secondary data from project documents. Analysis was conducted using NPV, IRR, BCR, simple linear regression, and t-tests. The financial analysis results indicate a contradiction in the 1-year period; while the IRR of 7.59% exceeds the 6% MARR, the NPV of -IDR 483,410,632 and a BCR of 0.85 indicate that the project is not yet feasible in the short term. Therefore, feasibility decision-making must be evaluated over the medium term; within a minimum 2-year projection, the investment demonstrates fulfillment of all feasibility criteria with a positive NPV of IDR 1,995,928,211. Additionally, location has a positive and significant effect on purchasing decisions, with a calculated $t_{\text{value}}$ of 9.52 > $t_{\text{table}}$ of 2.03951 and a coefficient of determination of 74.52%. Consequently, the investment is declared comprehensively feasible in the medium term, and the location factor serves as a vital determinant in enhancing consumer purchasing decisions.

Perbandingan Algoritma Supervised Learning dalam Memprediksi Jalur Seleksi Masuk Mahasiswa di Universitas Negeri Gorontalo

Manda Rohandi, Mukhlisulfatih Latief, Mohamad Ilyas Abas (Author) — Mon, 01 Jun 2026 00:00:00 +0000

The choice of university admission pathway (SNBT, SNBP, or independent selection/Mandiri) is closely related to students' demographic and administrative characteristics, and understanding this pattern benefits higher education institutions in designing more targeted recruitment strategies. This study aims to compare the performance of four supervised learning algorithms Decision Tree, Random Forest, Naïve Bayes, and k-Nearest Neighbor (k-NN) in predicting the admission pathway of Informatics Engineering students at Universitas Negeri Gorontalo (UNG). Data were obtained from UNG's Integrated Academic Information System (SIAT) for 1,237 students from the Information Technology Education and Information Systems study programs (2018–2024 cohorts), which after data cleaning resulted in 1,232 samples across three pathway classes (SNBT = 682, SNBP = 417, Mandiri = 133). Feature selection using information gain identified five informative features: selection type (national/local), age, cohort year, initial registration semester, and gender. Evaluation was conducted through three scenarios: 80:20 hold-out with Synthetic Minority Oversampling Technique (SMOTE), and 10-fold stratified cross-validation, followed by a Friedman significance test. The 10-fold cross-validation results show mean accuracies of 64.61% for Random Forest, 64.37% for Decision Tree, 63.47% for Naïve Bayes, and 61.03% for k-NN. The Friedman test indicated no statistically significant difference in performance among the four algorithms (χ² = 4.39; p = 0.222). The confusion matrix revealed that all algorithms perfectly classified the Mandiri class due to a definitional dependency with the selection-type feature, while most misclassifications occurred between the SNBP and SNBT classes. Applying SMOTE consistently improved minority-class (SNBP) recall across all four algorithms, but its effect on macro F1-score and overall accuracy varied by algorithm and was not uniformly positive. This study recommends incorporating academic behavioral features to improve the model's discriminative ability between national selection pathways.

Pengembangan Sistem Informasi Verifikasi Pemberkasan Ujian Skripsi dan Kerja Praktik Menggunakan Framework Laravel

Mon, 01 Jun 2026 00:00:00 +0000

This web based information system for verifying thesis and internship examination documents was developed to address the challenges associated with the conventional face to face verification process. The manual process is not only time consuming but also results in an uneven distribution of workload among verification lecturers. The system was developed using the Waterfall software development method, which consists of the requirements analysis, system design, implementation, testing, and maintenance phases. The implementation was carried out using PHP with the Laravel framework and MySQL as the database management system. System testing was conducted through unit testing and black box testing to ensure that all system functionalities operated as intended. The testing results showed that all system features functioned properly. User authentication based on assigned roles was successfully performed, document uploads were completed without errors, the document verification process by verification lecturers operated as expected, and all tested functionalities produced the expected results. These findings indicate that the proposed system supports a more efficient, reliable, and well managed document verification process for thesis and internship examinations.