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Journal of Engineering and Science Application
Published by Institute Of Advanced Knowledge and Science
ISSN : 30470544     EISSN : 30469627     DOI : https://doi.org/10.69693/jesa
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT
Journal of Engineering and Science Application (JESA) is published by the Institute Of Advanced Knowledge and Science in helping academics, researchers, and practitioners to disseminate their research results. JESA is a blind peer-reviewed journal dedicated to publishing quality research results in the fields of Applied Sciences, Engineering and Information Technology. All publications in the JESA Journal are open access which allows articles to be available online for free without any subscription. JESA is a national journal with e-ISSN: 3046-9627, and is have fee of charge in the submission process and review process. Journal of Engineering and Science Application publishes articles periodically twice a year, in April and October. JESA uses Turnitin plagiarism checks, Mendeley for reference management and supported by Crossref (DOI) for identification of scientific paper.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 50 Documents
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Comparison of Naive Bayes Method and Support Vector Machine in Classifying Diabetes Mellitus Disease Sari, Indah Kusuma; Wijaya, Rizky Putra
Journal of Engineering and Science Application Vol. 2 No. 2 (2025): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i2.33

Abstract

Diabetes mellitus is a chronic disease that occurs due to excessively high blood glucose levels resulting in the absence of insulin. In the period of data at the Siti Khadijah Islamic Hospital in Palembang, which is influenced by the number of patients undergoing health checks such as diabetes mellitus, it affects the classification of data that will complicate the hospital. So by utilizing data mining, classification to determine patients who have undergone examinations including diabetes sufferers or not. With these problems, the author conducted a comparative analysis of two algorithms, namely the naïve Bayes algorithm and the support vector machine algorithm for the classification of diabetes by using the WEKA tool with the Cross Validation and Confusion Matrix options tools with the highest accuracy results, namely the support vector machine algorithm with a polynomial kernel, the results of which are 96.2704% and an error rate of 3.7296%, it can be concluded that the most accurate algorithm in the classification of diabetes is the support vector machine algorithm with a polynomial kernel.
Evaluating Imputation Approaches and Support Vector Regression Parameters in Weather Forecasting Priyatno, Arif Mudi; Ningsih, Yunia
Journal of Engineering and Science Application Vol. 2 No. 2 (2025): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i2.34

Abstract

Rainfall plays a vital role in various sectors such as transportation, agriculture, and industry. Having accurate rainfall information enables stakeholders in these fields to take proper measures and minimize potential losses caused by inaccurate data. This study focuses on identifying an effective method for rainfall forecasting by examining imputation techniques in data preprocessing and parameter settings within Support Vector Regression (SVR). The experimental findings indicate that the most effective imputation method for SVR is determined using the Mean Squared Error (MSE) and Mean Absolute Error (MAE) evaluation metrics. Based on MSE, the k-nearest neighbor method proves to be the most reliable approach for data imputation preprocessing. The preprocessing results were then applied to Polynomial SVR with parameters C = 1000, tolerance = 0.001, epsilon = 0.01, and unlimited iterations. Conversely, MAE results highlight Artificial Neural Network (ANN) as the optimal imputation method. ANN, when combined with a radial basis function kernel, gamma = 0.001, C = 1000, tolerance = 0.001, and unlimited iterations, was further tested using RBF SVR under the same parameter settings.
Predictive Modeling of Unilever Indonesia’s Stock Prices with Linear Regression: A RapidMiner-Based Approach Ependi, Zulfan; Firmananda, Fahmi Iqbal
Journal of Engineering and Science Application Vol. 2 No. 2 (2025): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i2.35

Abstract

Investment decision-making in the capital market requires accurate analysis to minimize risk and maximize returns. This study focuses on PT Unilever Indonesia Tbk, a leading Fast-Moving Consumer Goods (FMCG) company listed on the Indonesia Stock Exchange, to evaluate its stock price prediction using the linear regression method supported by RapidMiner software. Historical stock data were collected from January 2, 2018, to June 27, 2023, including attributes such as opening price, closing price, lowest price, highest price, and trading volume. The dataset was processed using data screening and modeling techniques to construct a linear regression model for prediction. Various scenarios with different proportions of training and testing data (70/30, 80/20, 60/40, and 90/10) were tested to analyze the impact of data distribution on model performance. The evaluation results showed that the 80% training and 20% testing scenario provided the lowest Root Mean Squared Error (RMSE) of 56.699, indicating better predictive accuracy compared to other scenarios. Nevertheless, the linear regression model still produced a relatively high error rate, with the best RMSE value suggesting limitations of this approach for complex market prediction. This study concludes that while linear regression can provide a basic framework for stock price forecasting, incorporating additional economic, fundamental, and external factors could significantly improve predictive reliability. The findings offer practical insights for investors and researchers in understanding the potential and limitations of linear regression in stock market analysis
Analisis Earned Value Terhadap Biaya dan Waktu Pada Proyek Pembangunan Nusantara Internasional Convention dan Exhibition Bagus Bimoseno; Reynold Andika Pratama
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.38

Abstract

Proyek konstruksi dengan tingkat kompleksitas tinggi membutuhkan sistem pengendalian yang efektif untuk memastikan pencapaian sasaran waktu dan biaya sesuai dengan rencana pelaksanaan. Ketidaksesuaian antara progres aktual dengan rencana dapat menyebabkan keterlambatan penyelesaian proyek serta peningkatan biaya pelaksanaan. Oleh karena itu, diperlukan metode pengendalian yang mampu mengevaluasi kinerja proyek secara komprehensif. Penelitian ini bertujuan untuk menganalisis pengendalian proyek pembangunan Gedung NICE di PIK 2 menggunakan metode Critical Path Method (CPM) dan Earned Value Management (EVM). Metode CPM digunakan untuk mengidentifikasi aktivitas yang berada pada lintasan kritis, sedangkan metode EVM digunakan untuk mengevaluasi kinerja biaya dan waktu melalui indikator Cost Variance (CV), Cost Performance Index (CPI), Schedule Variance (SV), dan Schedule Performance Index (SPI). Hasil analisis CPM menunjukkan bahwa dari 84 aktivitas pekerjaan terdapat 14 aktivitas yang termasuk dalam lintasan kritis dan memerlukan pengendalian lebih intensif karena berpengaruh langsung terhadap durasi penyelesaian proyek. Hasil evaluasi EVM menunjukkan bahwa kinerja biaya proyek berada dalam kondisi efisien, ditunjukkan dengan nilai Cost Variance (CV) positif dan Cost Performance Index (CPI) lebih besar dari satu selama periode pengamatan. Sementara itu, kinerja waktu mengalami fluktuasi dengan adanya keterlambatan sementara pada minggu ke-16 hingga minggu ke-25 yang ditunjukkan melalui nilai Schedule Variance (SV) negatif dan Schedule Performance Index (SPI) kurang dari satu. Berdasarkan hasil proyeksi EVM, proyek diperkirakan dapat diselesaikan dalam durasi 49,99 minggu dengan estimasi biaya sebesar Rp49.854.436.514,00. Hasil penelitian menunjukkan bahwa integrasi CPM dan EVM dapat digunakan sebagai metode pengendalian proyek untuk mengidentifikasi aktivitas kritis serta memantau kinerja waktu dan biaya secara terpadu
Application of the K-Means Algorithm for the Grouping of Regional Income Patterns in Kudus Regency Alif Miftachul Nasikhah; Ade Ima Afifa Himayati; Findasari Findasari
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.39

Abstract

Regional revenue is one of the indicators of regional financial ability that needs to be analyzed to determine the realization of revenue. Analyses that are still descriptive have not been able to group data based on similar characteristics. This study aims to apply the K-Means algorithm to classify the regional income pattern of Kudus Regency based on monthly income realization data. The research uses a quantitative approach with secondary data in the form of the realization of regional revenue in Kudus Regency in 2020–2024 obtained from the Regional Revenue, Finance, and Asset Management Agency (BPPKAD) of Kudus Regency. Data processing is carried out using the RapidMiner application through the Read Excel, Set Role, Normalize, K-Means Clustering, and Performance stages, The number of clusters is set to three (k = 3). The results of the study showed that the K-Means algorithm succeeded in grouping data into three Cluster 0 clusters consisting of 4 data, namely September, October, November, and December. Cluster 1 consists of 1 data, namely August, while Cluster 2 consists of 7 data, namely January, February, March, April, May, June, and July.  Centroid analysis showed that each cluster had different characteristics, while evaluation using Performance Vector yielded a Davies-Bouldin Index value of -0.444 which showed good grouping results based on the RapidMiner evaluation. The results of this study are expected to be supporting information in the evaluation and planning of regional revenue management in Kudus Regency
SkyStore Web Inventory Management for Aircraft Spare Parts at GMF AeroAsia Muhamad Iqbal; Meidy Fajar Wahyu
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.41

Abstract

PT GMF AeroAsia Tbk uses SAP as the primary material transaction system, but daily inventory activities at the Satellite Store still rely on spreadsheets, creating risks of input errors, duplicated data, delayed reporting, and limited automated shelf-life monitoring. This study developed SkyStore, a web-based inventory information system for aircraft spare-part operations. Data were collected through non-participant observation, directed interviews, and literature study. Development followed Rapid Application Development and was implemented using Laravel and MySQL. SkyStore centralizes incoming and outgoing materials, Return to Warehouse, in-transit tracking, bin mapping, shelf-life control, analytical dashboards, notifications, and role-based user management. Black Box Testing covered 59 functional scenarios across 15 modules, and all scenarios were successful. White Box Testing examined login, incoming, and shelf-life logic with cyclomatic complexities of 3, 5, and 5, respectively; all 13 independent paths produced the expected results. The system therefore supports more structured, traceable, and timely Satellite Store inventory monitoring.
Sistem Kontrol PLC dan Inverter pada Vacuum Mesin Industri Wisnu Budiarjo; Didik Sugiyanto
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.42

Abstract

Perkembangan teknologi otomasi industri menuntut adanya sistem kontrol yang andal, efisien, dan mudah dioperasikan untuk mendukung proses produksi. Salah satu penerapan otomasi tersebut adalah penggunaan Programmable Logic Controller (PLC) dan inverter pada mesin vacuum industri. PLC berfungsi sebagai pengendali utama yang mengatur logika kerja sistem, sedangkan inverter berperan dalam mengatur kecepatan dan torsi motor listrik agar sesuai dengan kebutuhan proses. Laporan kerja praktik ini membahas sistem kontrol PLC dan inverter pada vacuum mesin industri di PT. DNP Indonesia. Metode yang digunakan dalam penyusunan laporan ini meliputi observasi langsung di lapangan, studi literatur, serta konsultasi dan bimbingan dengan pembimbing lapangan dan dosen pembimbing. Pembahasan difokuskan pada prinsip kerja PLC, prinsip kerja inverter, sistem mesin vacuum, serta alur kerja sistem kontrol yang diterapkan. Hasil dari kegiatan kerja praktik ini menunjukkan bahwa penerapan sistem kontrol PLC dan inverter mampu meningkatkan efisiensi, kestabilan, dan keandalan pengoperasian mesin vacuum industri. Selain itu, penggunaan inverter memungkinkan pengaturan kecepatan motor secara fleksibel sehingga dapat menghemat energi dan memperpanjang umur peralatan. Dengan demikian, sistem kontrol PLC dan inverter sangat berperan penting dalam menunjang kelancaran dan efektivitas proses produksi di PT. DNP Indonesia
Efficiency of Material Procurement, Time, and Cost Control in the Canopy Construction Project at RSKD Duren Sawit Muhammad Naufal Rif'at; Reynold Andika Pratama
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.44

Abstract

Material procurement plays a critical role in determining the cost and schedule performance of hospital-based construction projects, where limited storage space and active medical operations constrain logistics. This study evaluates the efficiency of the material procurement system and its relationship with cost and time performance in the canopy construction project at RSKD Duren Sawit, East Jakarta. A descriptive quantitative case study approach was applied, combining field observation, structured interviews, and secondary project documents (purchase orders, bill of quantity, budget plan, and weekly progress reports). Cost and schedule performance were analyzed using Earned Value Analysis (EVA), while the Critical Path Method (CPM) was used to identify the activities controlling total project duration. The results show a Cost Performance Index (CPI) of 1.316 and a Schedule Performance Index (SPI) of 1.071 at week 10, indicating that the project was completed under budget and ahead of schedule, with an estimated cost saving of approximately IDR 461 million against the total budget. CPM analysis identified the motorcycle parking canopy works as the critical path, with zero float, while the ICU canopy works and K3 (occupational safety) activities had considerable float (30-75 days). Procurement efficiency was found to be influenced by accurate material volume planning, effective vendor price negotiation, Just-in-Time (JIT) delivery scheduling adapted to hospital operating hours, and strict incoming-material quality control. These findings provide a practical reference for managing material procurement in construction projects located within active healthcare facilities.
Analisis Market Basket Berbasis Web Menggunakan Algoritma FP-Growth untuk Bundling Produk Toga Micolasdo Sitanggang; Dede Sahrul Bahri
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.45

Abstract

PT Aqualuxe Perkasa Abadi merupakan perusahaan manufaktur produk home care skala kecil yang belum memanfaatkan data transaksi harian untuk strategi pemasaran. Penelitian ini bertujuan mengimplementasikan algoritma FP-Growth (Frequent Pattern Growth) untuk menganalisis pola penjualan dan merancang sistem informasi berbasis web multi-role yang menghasilkan rekomendasi bundling produk secara otomatis. Pengembangan sistem menggunakan model Waterfall, meliputi analisis kebutuhan, praproses data, serta implementasi FP-Growth melalui library mlxtend Python yang dipanggil dari backend PHP melalui mekanisme subprocess. Sistem membedakan dua peran pengguna, yaitu Admin dan Owner, yang diatur melalui Role-Based Access Control. Pengujian terhadap data transaksi aktual selama satu bulan (7.994 transaksi unik, 36 SKU) dengan minimum support 0,05, minimum confidence 0,5, dan minimum lift 1,0 menghasilkan 10 frequent itemset dan 3 rekomendasi bundling yang valid. Rule terkuat, Rubber Sealant Spray ke Lem Anti Bocor 1kg, memiliki confidence 0,87 dan lift 1,84. Pengujian black box pada tujuh modul fungsional membuktikan sistem berjalan sesuai kebutuhan. Temuan ini menunjukkan bahwa FP-Growth dapat memberikan landasan berbasis data bagi perusahaan skala kecil untuk merancang strategi bundlingnya.
Analisis Perhitungan Volume dan Detail Penulangan Balok Beton Bertulang Menggunakan Tekla Structures pada Proyek Gedung 3 Lantai (Studi Kasus: Wijaya Guest House) Muhammad Rifki; Era Agita Kabdiyono
Journal of Engineering and Science Application Vol. 3 No. 2 (2026): Mei-Oktober
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v3i2.46

Abstract

Perhitungan volume dan berat tulangan balok beton bertulang secara manual rentan terhadap kesalahan akibat keterbatasan visualisasi dua dimensi, terutama pada bangunan dengan variasi tipe balok yang kompleks. Penelitian ini bertujuan membandingkan hasil perhitungan berat tulangan balok antara metode manual dan metode Building Information Modeling menggunakan Tekla Structures pada proyek Wijaya Guest House, bangunan tiga lantai dengan dak atap di Jakarta. Metode yang digunakan adalah kuantitatif komparatif, dengan data primer berupa hasil pemodelan tiga dimensi pada Tekla Structures dan data sekunder berupa gambar kerja serta Bar Bending Schedule dari kontraktor pelaksana. Perhitungan manual mengelompokkan balok ke dalam sembilan hingga sebelas tipe per lantai berdasarkan asumsi bentang bersih seragam, sedangkan Tekla Structures menghasilkan data quantity take off otomatis untuk dua puluh satu hingga tiga puluh dua cast unit individual per lantai sesuai geometri aktual di lapangan. Hasil penelitian menunjukkan total berat tulangan balok hasil perhitungan manual mencapai 21.248,10 kilogram, sedangkan hasil pemodelan Tekla Structures menghasilkan 14.948,50 kilogram, dengan selisih rata-rata 29,65 persen lebih rendah pada data aktual dibandingkan perhitungan manual. Selisih terbesar terjadi pada Lantai 2 sebesar 37,35 persen dan terkecil pada Dak Atap sebesar 11,53 persen. Analisis lanjutan terhadap estimasi Rencana Anggaran Biaya menunjukkan bahwa penggunaan hasil perhitungan manual berpotensi menyebabkan kelebihan anggaran pengadaan besi tulangan hingga 42,14 persen dibandingkan kebutuhan aktual. Penelitian ini menyimpulkan bahwa pemodelan BIM berbasis Tekla Structures memberikan estimasi volume dan berat tulangan yang lebih presisi, efisien, dan andal sebagai dasar pengendalian biaya proyek dibandingkan metode konvensional.

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