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Firdaus Annas
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Knowbase : International Journal of Knowledge in Database
Published by Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi
ISSN : 27980758     EISSN : 27977501     DOI : https://www.doi.org/10.30983/knowbase
Core Subject : Science,
Computer Science & IT
Knowbase : International Journal of Knowledge in Database is a peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia to focus on understanding Modern developments in this field, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results that describe significant advances in the areas of Database management systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 150 Documents
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Application of the Fuzzy Sugeno Method in a Decision Support System for Teacher Performance Assessment Rezeki, Muhammad; Putra, Nursaka
Knowbase : International Journal of Knowledge in Database Vol. 1 No. 2 (2021): December 2021
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/ijokid.v1i2.5043

Abstract

The teacher is a professional educator who has essential duties, functions, and roles in the nation's intellectual life. In order for the functions and duties attached to the functional positions of teachers to be carried out following applicable regulations, it is necessary to assess teacher performance which ensures a quality learning process at all levels of education. Currently, teacher performance evaluation uses a manual assessment system, which causes the evaluation process to be relatively long. For this reason, a decision support system is needed that can take into account all the criteria that support decision making in order to assist, speed up and simplify the decision-making process. In determining teacher performance assessment, the method used is Fuzzy Takagi-Sugeno Kang (Fuzzy Sugeno). This method was chosen because the Fuzzy Sugeno method is a decision support model where the main input uses the basic concept of finding the weighted summation. The Fuzzy Sugeno method for assessing teacher performance uses three stages: the Fuzzification Stage, the Implication Function Stage, and the Defuzzification Stage. The level of validity with Sugeno's Fuzzy Inference Systems (FIS) method for assessing teacher performance is very good.
Design of Waste Treatment Applications at PT. Rifansi Dwi Putra Using Visual Basic.Net and MySQL Database Jannah, Miftahul; Rosalina, Jenny; Yubarda, Erliza
Knowbase : International Journal of Knowledge in Database Vol. 1 No. 1 (2021): June 2021
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/ijokid.v1i1.5079

Abstract

PT. Rifansi Dwi Putra is a company that operates in the Oil and Gas Industry, especially in the Waste Handling Transportation (WHT) Project regarding Waste Transportation. PT. Rifansi Dwi Putra especially at the Sand Management Facility (SMF) in processing waste volume data already uses a computer and is supported by Microsoft Excel software. However, doing data input, searching, processing, and reporting takes a relatively long time. So that the resulting information is less accurate, thus requests for fast and accurate information are often late in presenting their reports. In this regard, to facilitate the process of data accuracy, it is better to create an application for data collection of waste volumes using Visual Basic Programming Language and MySQL database. To facilitate the operations department, especially in recording the volume of waste transported to the Sand Management Facility (SMF) and making reports on the volume of waste to control, repair, and process data based on information technology and help the obstacles faced. To produce applications in waste volume data collection to facilitate structured data input in the data entry process, make it easier to search waste volume data, and help the management team produce accurate waste volume reports, making it easier to make decisions. The user of this application is only owned by one person because it is still a single user or stand alone (desktop-based) and this application produces three reports, namely reports per day, reports per month and reports per unit.
Heavy Equipment Rental Schedule Report Application Using Visual Basic.Net and MySQL Database Annisa, Syerlie; Delvianti, Yurita
Knowbase : International Journal of Knowledge in Database Vol. 1 No. 2 (2021): December 2021
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/ijokid.v1i2.5096

Abstract

The heavy equipment business in Indonesia is again excited in line with the increasing demand for heavy equipment by various sectors such as the mining sector, the agro-industry sector, and the construction sector. PT. Petronesia Benimel is one of the business fields engaged in renting heavy equipment. The management of the heavy equipment rental schedule to other companies has been carried out using a computerized system, namely using the Microsoft Excel application which is still not optimal in integrating, calling and processing data at once. Using these applications independently results in the management of heavy equipment rental reports being constrained because tenant data and rental management are often out of sync. The application uses Visual Basic programming language and MySQL database supported by research and product development methods and waterfall development models. Based on the trial results of using a schedule report application that can make it easier for staff to manage heavy unit rental schedules from various partner companies (stakeholders) so that better reports are obtained.
Information System Design for Water Maintenance Activities at PT. Rezeki Surya Intimakmur Derisfy, Fahmizal; Gebrina, Lusiana; Annisa, Syerlie
Knowbase : International Journal of Knowledge in Database Vol. 1 No. 1 (2021): June 2021
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/ijokid.v1i1.5104

Abstract

PT. Rezeki Surya Intimakmur is a company engaged in home and building maintenance. Currently PT. Rezeki Surya Intimakmur is currently under a work contract with PT. Chevron Pacific Indonesia (PT. CPI) in terms of clean water maintenance activities in the company environment and the housing for employees of PT. CPI. In managing clean water maintenance data every day, the company uses a manual method by recording, which is filling out a work assignment form. This method results in the management of clean water maintenance work being hampered because data on workers and work results are often inconsistent with the actual situation—applications designed using research and product development methods with the waterfall model. The application design process uses Visual Basic.Net programming language and MySQL database. The resulting can make it easier for admin staff to manage clean water maintenance activities to produce maintenance reports.
BFV Homomorphic Encryption Algorithm as a Proposed Encryption Mechanism for the Votenow System of PT XYZ Muhamad Ikmal Wiawan; Agi Agus Setiawan Sufyan
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10132

Abstract

Confidentiality and integrity of voting results constitute major challenges in web-based e-voting systems, as vote tallying in conventional approaches still requires data decryption. This condition potentially enables intervention by private key holders and reduces trust in election outcomes. The votenow e-voting platform of PT XYZ does not yet support vote tallying in an encrypted state; therefore, an alternative encryption mechanism is required that does not significantly alter the existing system workflow. This study aims to evaluate the BFV (Brakerski–Fan–Vercauteren) Homomorphic Encryption algorithm as a proposed encryption mechanism for the PT XYZ e-voting system (product name anonymized). A controlled experimental method was applied using a testing prototype with encryption and decryption modules implemented in C++ based on the Microsoft SEAL library, while a PHP-based web interface was employed for data input and visualization. The evaluation assessed the time required to input 50,000 encrypted votes, vote tally accuracy using both decryption-based counting and direct ciphertext computation without decryption, total ciphertext size, verification time for encrypted data validity, ciphertext decryption time, and vote result presentation time. The results indicate that the input of 50,000 votes was completed within 5 minutes, meeting the 10-minute target. Vote tally accuracy reached 100% for both counting methods, and the ciphertext size of 383.4 MB remained below the 512 MB threshold. Furthermore, the encrypted data verification time was recorded at 225.8 seconds, ciphertext decryption time at 5 minutes and 15 seconds, and vote result presentation time via decryption at 13.816 seconds, all of which fall within acceptable operational limits. Based on these findings, the BFV algorithm is considered suitable for adoption as an encryption mechanism in the PT XYZ e-voting system, as it enables vote tallying in the encrypted domain while preserving the confidentiality and integrity of voter data.
Classification of Referral Decision Recommendations in Community Health Centers Using the K-Nearest Neighbor Approach Ningrum, Leny; Salsabila, Nisrina
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10137

Abstract

management, including determining patient referral decisions at community healthcenters. However, these decisions often still depend on the subjective assessment ofmedical personnel, resulting in an inaccurate and ineffective process of identifyingdiabetes patient management. The purpose and objective of this research anddevelopment is to identify diabetes patient management for referral decisionrecommendations at Puskesmas using the K-Nearest Neighbor (KNN) approach toobtain a more accurate and effective process and results so that Puskesmas can morequickly provide appropriate follow-up based on patient laboratory test results. Thedata used in this study was diabetes patient data at Puskesmas, using variables suchas age, systolic and diastolic blood pressure, glucose tests, and referral to hospitals asthe target class. The results of the research and classification evaluation using theConfusion Matrix in KNN modeling based on this data showed that the number ofpatients included in TP=41, TN=38, FP=1, and FN=4, with an accuracy of 94.02%,precision of 97.62%, recall of 91.11%, and F1-Score of 94.25%. These values arecategorized as very good because they are able to predict classes correctly at themodeling stage. Thus, this study is considered feasible as a support for referraldecision recommendations in identifying the treatment of diabetic patients atPuskesmas
Human Emotion Classification Based on EEG Using FFT Band Power and LSTM Classifier Prabowo, Dwi Wahyu
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10145

Abstract

This study investigates human emotion recognition using electroencephalogram (EEG) signals, focusing on the Shanghai Jiao Tong University Emotion EEG Dataset (SEED), which consists of recordings from 62 EEG channels categorized into three emotion classes: positive, neutral, and negative. The main challenges in EEG-based emotion classification include the limited amount of available data and the nonlinear, non-stationary nature of EEG signals. To address these challenges, this study evaluates the effectiveness of the Fast Fourier Transform (FFT) band power as input features and employs a stacked Long Short-Term Memory (LSTM) network as the classifier. Model validation was conducted using stratified 10-fold cross-validation, and performance was assessed using accuracy, F1-score, and Cohen’s kappa metrics. Experimental results show that the proposed method achieved an average accuracy of 89.87%, an F1-score of 90.10%, and a Cohen’s kappa value of 0.848, with minimal variation across folds, demonstrating high model stability. Unlike many recent studies that rely on image-based representations or Generative Adversarial Networks (GAN)-driven data augmentation, this study demonstrates that FFT band power combined with a sequential LSTM classifier can achieve strong performance without synthetic data generation or complex feature transformations. These findings indicate that the combination of FFT band power features and the LSTM classifier can serve as a solid baseline for further research.
Implementation of Genetic Algorithm for Automatic Course Scheduling Optimization Rakhmi Khalida; Situmorang; Dwi; Setiawati, Siti
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10260

Abstract

Course scheduling in vocational high schools (SMK) constitutes a complex combinatorial optimization problem involving multiple hard and soft constraints related to teacher availability, class allocation, and time-slot distribution. Although Genetic Algorithms (GA) have been extensively applied in educational timetabling, existing studies largely emphasize standalone optimization or desktop-based solutions, with limited analytical evaluation of refinement strategies and system-level applicability. This study addresses this gap by empirically evaluating a hybrid GA–Local Search (LS) approach embedded within a web-based scheduling framework. GA is utilized as a global search mechanism to generate feasible schedules that satisfy all hard constraints, while LS is applied as a post-optimization phase to improve solution quality by reducing soft constraint violations. Experiments were conducted using real scheduling data from SMK Yadika 13 Bekasi, involving 3 subjects, 3 teachers, 4 classes, and 12 time slots within a single-day scenario. Although limited in scale, this configuration was deliberately selected to enable transparent analysis of the optimization dynamics and refinement impact of the proposed hybrid approach. The results show that the pure GA produces five soft constraint violations, mainly due to suboptimal placement of cognitively demanding subjects and uneven subject distribution. After applying LS, violations were reduced to two cases, with the fitness value improving from 0.873 to 0.946 and only a marginal increase in computation time (5–7 seconds). These findings demonstrate that local refinement significantly enhances schedule quality beyond conflict-free feasibility. This study contributes scientifically by providing an empirical assessment of GA–LS hybridization for soft-constraint optimization and by establishing a scalable web-based framework that supports future extensions to full-week scheduling and adaptive academic systems
Integration of Machine Learning and Web-Based Expert Systems for Diabetes Risk Analysis in Pagar Alam Syahri, Riduan; Puspita, Desi; Masdalipa, Risnaini
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10268

Abstract

This study aims to develop an integrated system combining Machine Learning (ML) and a Web-Based Expert System for genomic and clinical data analysis to mitigate the rising diabetes cases in Pagar Alam City. The research adopts the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology, encompassing business understanding, data understanding, data preparation, modeling, evaluation, and deployment phases. Unlike previous studies relying on standard public datasets, this research integrates genomic profiles (TCF7L2 and KCNQ1 SNPs) alongside local clinical parameters from five sub-districts in Pagar Alam. Quantitative data from 640 samples were analyzed using the Support Vector Machine (SVM) algorithm. Evaluation results during the modeling phase show that the SVM model achieved a superior accuracy of 99.07%, demonstrating that integrating genomic data significantly enhances predictive precision. The web-based expert system implemented in the deployment phase provides personalized prevention recommendations based on individual risk profiles. This application is expected to serve as a strategic tool for the Pagar Alam government to enhance the effectiveness of prevention programs through localized and genetic-based interventions.
The The Mapping of Waste Management Facilities in Bogor Regency Using a K-Means Irmayansyah; Nadhira Faza Fatiha
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10338

Abstract

Waste is the solid residue of human activities or natural processes that is considered useless. If not managed properly, it can have a negative impact on the environment and health. When waste management facilities such as transport fleets, waste banks, and TPS3R (3R waste management sites) are insufficient to handle the volume of waste effectively, waste accumulation will occur, which can pollute the air, soil, and water, and increase the risk of disease spread. Therefore, new data-driven thinking is needed to improve more targeted and efficient waste management. The application of the K-Means clustering technique in waste management can be done, as demonstrated by the results of regional clustering in Bogor Regency with recommendations for appropriate facilities. The use of variables such as uncollected waste volume, distance to landfill sites, number of villages and population, as well as the stages of determining the number of clusters, initial centroid point determination, calculation of data distance to centroid points, and grouping of data according to minimum distance to centroid points were carried out to produce the clustering. The variables and stages were then applied to a prototype decision support system to assist the Bogor District Environmental Agency in placing waste management facilities more effectively. The prototype system developed has undergone

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