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Hendra Kurniawan
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Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Published by Institut Informatika dan Bisnis Darmajaya
ISSN : 26157292     EISSN : 26210827     DOI : http://dx.doi.org/10.30873/simada.xxxx.xxxx
Core Subject : Science,
Computer Science & IT
1. Sistem Informasi ((Human Computer Interaction, E-Business, E-Government, Decision Support System (DSS), Enterprise System, dll) 2. Manajemen Basis Data (Business Intelligence, Big Data, Data Warehouse, Distributed Database, Data Mining, Information Retrieval, Knowledge Management System, dll)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 120 Documents
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PERANCANGAN SISTEM INFORMASI REGISTRASI LOMBA PEKAN OLAHRAGA DAN SENI DENGAN PEMANFAATAN INTEGRASI PAYMENT GATEWAY DI SMAN 15 BANDAR LAMPUNG firdhayanti, ayu; Agarina, Melda; Sutedi, Sutedi; Suryadi , Arman; Fauzi Maulana, Muh Royan
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 7 No. 2 (2024): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Abstract

This research aims to design a web-based information system to facilitate the registration process for competitions in Sports and Arts Week (PORSENI) at SMAN 15 Bandar Lampung. This research was motivated by the complexity of the manual registration process that involved many participants from different schools, especially those from out of town. The designed information system integrates an online payment function through the Xendit payment gateway. This system is expected to increase the efficiency of the registration process, reduce the committee's workload, and provide convenience for participants to register and pay online. The results showed that the developed information system successfully simplified the registration and payment process of the competition. Participants can register and pay independently without coming directly to the committee. In addition, this system can automate several processes that were previously done manually, thus increasing the efficiency of the committee's work. Implementing this information system has positively contributed to the organisation of PORSENI at SMAN 15 Bandar Lampung.
PERANCANGAN ARSITEKTUR CLOUD SISTEM INFORMASI SEKOLAH MA AL FALAH PESAWARAN BERBASIS ROADMAP CLOUD COMPUTING ADOPTION (ROCCA) Meiliza; Rahardi, Agus; Nurjoko; Abdurahim
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 7 No. 2 (2024): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Abstract

This study examines the design of cloud architecture for school information systems at MA Al Falah Pesawaran based on the Roadmap Cloud Computing Adoption (ROCCA) and the implementation of the Software as a Service (SaaS) model. The main objective of this study is to develop efficient, scalable, and cost-effective information technology solutions to improve school operational performance and effectiveness. The methods used include needs analysis, cloud architecture design, and implementation and evaluation of system prototypes. The results of the study indicate that the implementation of ROCCA and the SaaS model can accelerate the adoption of cloud technology in the school environment, reduce operational costs, and increase the flexibility and accessibility of school information systems. The implementation of this cloud architecture also allows for better integration with other existing systems, and provides a more secure and well-managed platform.   Keywords: Cloud Architecture, School Information Systems, ROCCA, SaaS   Abstrak Penelitian ini mengkaji perancangan arsitektur cloud untuk sistem informasi sekolah di MA Al Falah Pesawaran dengan berbasis pada Roadmap Cloud Computing Adoption (ROCCA) dan penerapan model Software as a Service (SaaS). Tujuan utama penelitian ini adalah untuk mengembangkan solusi teknologi informasi yang efisien, scalable, dan cost-effective, guna meningkatkan kinerja dan efektivitas operasional sekolah. Metode yang digunakan meliputi analisis kebutuhan, perancangan arsitektur cloud, serta implementasi dan evaluasi prototipe sistem. Hasil penelitian menunjukkan bahwa penerapan ROCCA dan model SaaS dapat mempercepat adopsi teknologi cloud di lingkungan sekolah, mengurangi biaya operasional, serta meningkatkan fleksibilitas dan aksesibilitas sistem informasi sekolah. Implementasi arsitektur cloud ini juga memungkinkan integrasi yang lebih baik dengan sistem-sistem lain yang ada, serta menyediakan platform yang lebih aman dan terkelola dengan baik.   Kata Kunci: Arsitektur Cloud, Sistem Informasi Sekolah, ROCCA, SaaS
AUDIT SISTEM INFORMASI APLIKASI PAJAK PBB P2 BADAN PENDAPATAN DAERAH KABUPATEN WAY KANAN MENGGUNAKAN FRAMEWORK COBIT 2019 Adison; Sutedi, Sutedi
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Abstract

The PBB-P2 tax application in the Revenue Agency of Way Kanan Regency has a critical limitation: it cannot record actual coordinate data, causing tax assessments to rely on predetermined strategic-location values rather than precise geographic information. This study aims to evaluate the information system governance of the PBB-P2 tax application using the COBIT 2019 framework. The research employed a quantitative method with questionnaires distributed to 15 respondents consisting of staff and management of the Revenue Agency. Sampling used purposive sampling, and data validity and reliability were tested using Pearson correlation and Cronbach’s alpha. The assessment covered five COBIT 2019 processes: APO04, APO07, APO13, DSS02, and DSS03. Results show that all five processes are at capability level 3 (Predictable Process) with an average current score of 3.47, while the expected level is 4.49, yielding a gap of approximately 1.02. This gap indicates that the system requires significant improvements in innovation management, human resource competence, information security, and service request management. Recommendations include structured training programs, security system upgrades, and formalized incident management procedures
ANALISIS PENERIMAAN TEKNOLOGI SISTEM INFORMASI JASA KONSTRUKSI PADA DINAS PUPR KABUPATEN WAY KANAN MENGGUNAKAN METODE TAM Ahyar, Ahyar; Hasibuan, M.Said
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Abstract

In its daily operations, the Public Works and Spatial Planning Office (Dinas PUPR) of Way Kanan Regency utilizes several systems as tools to assist with activities and store important institutional data. One of the systems used in the Dinas PUPR office is the Construction Services Information System, which functions as a provider of construction services data and information, supported by information and telecommunication technology, and regulated by legal provisions. This system allows the Head of the Office or the Regent of Way Kanan Regency to easily monitor the ongoing projects handled by Dinas PUPR.Hypothesis 1 (Attitude Toward Using → Behavioral Intention to Use the Construction Services Information System of Dinas PUPR Way Kanan Regency)Based on the coefficient parameter Attitude Toward Using → Behavioral Intention to Use (original sample) of 0.631, there is a POSITIVE influence between these two variables. This indicates that the higher the Attitude Toward Using, the better the Intention to Use. Additionally, the T-statistic value of 3.996 is considered SIGNIFICANT, as it is greater than the T-table value (3.996 > 1.96). Thus, the hypothesis is accepted.Based on the coefficient parameter Attitude Toward Using → Behavioral Intention to Use (original sample) of 0.157, there is a NEGATIVE influence between these two variables. This means that a lower Attitude Toward Using leads to a lower Behavioral Intention to Use. Furthermore, the T-statistic value of 1.116 is considered NOT SIGNIFICANT, as it is less than the T-table value (1.116 < 1.96). Thus, the hypothesis is not accepted
ANALISIS PERBANDINGAN ALGORITMA KLASIFIKASI UNTUK PREDIKSI DIABETES MELLITUS MENGGUNAKAN PENDEKATAN MACHINE LEARNING Shelawati, Erina; Nursiyanto, Nursiyanto
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Diabetes Mellitus is a chronic disease with an increasing prevalence worldwide and poses serious health risks if not detected early. Early prediction of diabetes is crucial to support preventive actions and improve healthcare decision-making. This study aims to analyze and compare the performance of several machine learning classification algorithms in predicting Diabetes Mellitus based on clinical data. The dataset used in this research is the Pima Indians Diabetes dataset, which consists of medical attributes such as glucose level, blood pressure, insulin, body mass index, and age. Data preprocessing was conducted to handle missing values and improve data quality. Three classification algorithms, namely Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN), were implemented and evaluated using k-fold cross-validation. The performance of each algorithm was measured using accuracy, precision, recall, F1-score, and confusion matrix. The experimental results show that the Random Forest algorithm achieved the highest performance compared to SVM and KNN, with superior accuracy and more balanced classification results. This indicates that ensemble-based methods are more effective in handling medical data with complex patterns. In conclusion, machine learning algorithms can be effectively applied to predict Diabetes Mellitus, and Random Forest is recommended as the most suitable algorithm for this dataset. The results of this study are expected to contribute to the development of intelligent decision support systems in the healthcare domain. Keywords: Classification; Diabetes Mellitus; Machine Learning; Random Forest; Support Vector Machine; K-Nearest Neighbor
KLASIFIKASI TINGKAT RISIKO PENYEBARAN COVID-19 DI PROVINSI INDONESIA MENGGUNAKAN ALGORITMA NAÏVE BAYES Nurhidayat, Taufiq; Halimah, Halimah
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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The rapid spread of COVID-19 across Indonesian provinces has created significant challenges for government authorities indetermining appropriate mitigation priorities. Accurate classification of regional risk levels is therefore essential to supporteffective decision-making. This study aims to classify the risk level of COVID-19 transmission in Indonesian provinces using theNaïve Bayes algorithm based on publicly available data from the KawalCOVID-19 dataset. The dataset consists of daily confirmedcases aggregated at the provincial level and is processed through data cleaning, normalization, and feature selection stages. Risklevels are categorized into low, medium, and high classes based on cumulative cases and daily case growth indicators. The NaïveBayes classifier is applied due to its simplicity and effectiveness in handling probabilistic classification problems. Modelperformance is evaluated using k-fold cross-validation and standard classification metrics, including accuracy, precision, recall,and confusion matrix analysis. The experimental results indicate that the proposed model is able to classify provincial COVID-19risk levels with satisfactory accuracy, demonstrating consistent performance across validation folds. The findings show that NaïveBayes can effectively capture patterns in COVID-19 case distribution and growth trends among provinces. Compared to previousstudies, such as Azhari et al. (2023) who applied K-Means Clustering and Gunawan & Purwayoga (2022) who used K-Means forCOVID-19 spread analysis, this study offers a supervised classification approach that produces more interpretable and labelspecific risk categories. Moreover, while Thaib & Betrisandi (2025) demonstrated Naïve Bayes effectiveness for respiratory diseaseclassification at the patient level, this study extends its application to provincial-scale epidemiological risk mapping. In conclusion,this study provides a practical and interpretable data mining approach that can assist policymakers in identifying high-risk regionsand prioritizing public health interventions during pandemic conditions
IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI UNTUK ANALISIS POLA PEMBELIAN MENU PADA KAFE TOKOPI LEIPE Elismawati, Elismawati; Agarina, Mleda
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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The rapid growth of cafes has led to an increase in transaction data that is often underutilized. This study aims toimplement data mining using the Apriori algorithm to analyze menu purchasing patterns at TOKOPI LEIPE Cafe. Thedata used are real transaction data collected over a three-month period and anonymized to protect privacy. The researchmethod follows the Knowledge Discovery in Database (KDD) stages, including data collection, data cleaning, datatransformation, modeling, and evaluation. The results show association rules that describe combinations of menusfrequently purchased together based on support and confidence values. These findings are expected to assist cafemanagement in developing menu bundling strategies, promotions, and inventory planning
PENERAPAN TEXT MINING UNTUK ANALISIS TOPIK KELUHAN PENGGUNA APLIKASI ACCESS BY KAI MENGGUNAKAN METODE LATENT DIRICHLET ALLOCATION (LDA) Mulyanto, Mulyanto; Purnomo, Hendri
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Abstract

Access by KAI is the primary digital platform used by the Indonesian public for train ticket reservations. Although thenumber of application downloads continues to increase, the application still receives numerous negative reviews onGoogle Play Store, primarily related to system performance issues. The large volume of user reviews makes manualanalysis inefficient, highlighting the need for an automated approach to identify the main problems experienced byusers. This study aims to analyze the dominant complaint topics in Access by KAI user reviews using a Text Miningapproach with the Latent Dirichlet Allocation (LDA) method. The dataset consists of 2,000 recent low-rated userreviews (1- to 3-star ratings) collected through web scraping techniques. The research stages include data collection,text preprocessing (cleaning, case folding, stopword removal, and stemming), corpus construction, and topic modelingusing LDA. The results identify four dominant complaint topics: (1) delayed payment verification, (2) applicationinstability (crashes/errors) on Android devices, (3) malfunction of application features after software updates, and (4)difficulties accessing ticket purchasing services during peak demand periods (ticket wars). The identified topics providevaluable insights for application developers to prioritize improvements in system stability and the reliability of paymenttransaction services.
PEMANFAATAN DATA MINING DALAM PENGAMBILAN KEPUTUSAN STRATEGIS PADA PENGELOLAAN BADAN USAHA MILIK DESA (BUMDes) Azhar, Fuad; Pambudi, Randi Estian
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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Abstract

Village-Owned Enterprises (BUMDes) play a strategic role in promoting rural economic growth through the management ofbusiness units based on local potential. However, in practice, strategic decision-making in BUMDes management is oftenconducted conventionally and has not fully utilized available data. This study aims to examine the use of data mining as adecision support tool for strategic decision-making in BUMDes management. The research adopts a quantitative approach usingthe clustering method applied to BUMDes operational data, including revenue, number of transactions, and business operationalperiods. The research stages follow the Knowledge Discovery in Databases (KDD) process, consisting of data selection, datacleaning, data transformation, data mining implementation, and result evaluation. The findings indicate that the application of theclustering method successfully classifies BUMDes business units into several performance categories, providing objective andrelevant information to support managerial decision-making. Therefore, data mining can be effectively utilized as a strategicdecision support system in data-driven BUMDes management.
VISUALISASI DATA UPTD PUSKEMAS DALAM BENTUK INFOGRAFIS DI KECAMATAN METRO PUSAT Utami, Winda Afrilia; Muharni, Sita
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 8 No. 1 (2025): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

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This study aims to improve the effectiveness of health information delivery through data visualization in infographic form at the UPTD Public Health Center (Puskesmas) of Metro Pusat District, Indonesia. Conventional health reports are often too long and complex for stakeholders and the public to interpret, so the underlying data is rarely used to its full potential in planning and decision-making. This research applies the Visual Data Mining (VDM) method, covering project planning, data preparation, and data analysis, with Tableau used as the visualization tool. The dataset consists of new-case and existing-case records for the ten most frequent diseases registered at Puskesmas Metro Pusat from 2021 to 2024, drawn from 45 recorded disease categories. The resulting dashboard shows that Hypertension (ICD-10 I10) is consistently the most frequent diagnosis across all four years, while several respiratory and metabolic conditions show distinct rising or falling trends between 2021 and 2024. These findings indicate that infographic-based visualization can present multi-year health trends in a more interactive, accurate, and easily interpreted format than narrative reports, supporting more responsive, evidence-based decision-making at the primary care level. The study recommends infographic-literacy training for Puskesmas staff, development of digital dissemination tools, and cross-sector collaboration to widen public access to health information.

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