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Moch. Syahrir
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Unit Publikasi Ilmiah, Pusat Penelitian dan Pengabdian Masyarakat, Politeknik Negeri Bali, Kampus Jimbaran, Badung, Bali, Indonesia
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INDONESIA
MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA
Published by Politeknik Negeri Bali
ISSN : 25805630     EISSN : 25805630     DOI : http://dx.doi.org/10.31940/matrix.v13i2.52-67
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Managing the rapid changes in information technology Emerging advances in electrical and electronics and new applications Implications of digital convergence and growth of electronics technology Project management in electrical, mechanical, or civil engineering
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 121 Documents
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Predicting financial default risks: A machine learning approach using smartphone data Shinta Palupi; Gunawan; Ririn Kusdyawati; Richki Hardi; Rana Zabrina
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 3 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i3.107-118

Abstract

This study leverages machine learning (ML) techniques to predict financial default risks using smartphone data, providing a novel approach to financial risk assessment. Data were collected from 1,000 individuals who had taken personal loans, focusing on key behavioral parameters such as app usage frequency, GPS location data, and communication patterns over a six-month period prior to loan application. The analysis employed Logistic Regression, Decision Trees, and Random Forest models to determine correlations between these parameters and default risks. The Random Forest model demonstrated superior performance, achieving 85% accuracy. Key findings show that high usage of financial apps was associated with lower default risks, while irregular communication patterns and erratic mobility were significant indicators of higher risk. These results suggest that smartphone-derived behavioral data can significantly enhance traditional credit scoring methods. The study not only contributes to predictive analytics in financial risk management but also raises ethical considerations around privacy and data security.
Voltage drop comparison in Lead-acid and Lithium-ion batteries on electric scooters Sapteka, Anak Agung Ngurah Gde; Narottama, Anak Agung Ngurah Made; Widyatmika, Komang Agus
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 1 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i1.43-49

Abstract

This article compares the voltage drop on Lead-acid and Lithium-ion batteries used as an energy source for electric scooters. An experiment was conducted with five electric scooter users weighing 60.25 Kg, 70.60 Kg, 83.20 Kg, 95.40 Kg, and 103.75 kg to obtain data on voltage drop. Each user of this electric scooter carried out three experiments by circling about 1.07 Km at the Politeknik Negeri Bali area. This study proves that the voltage drop on the Lead-acid and Lithium-Ion batteries has a linear relationship to the weight of an electric scooter user with a 36V 400-watt BLDC motor load. The linear equation has an intercept value of -1.36766 and a slope value of 0.04791 for the Lead-acid battery. In contrast, the linear equation has an intercept value of -2.47064 and a slope value of 0.05417 for Lithium ion batteries. The average voltage drop across lead acid is 25% higher than that across Lithium-ion
Design and implementation of IoT-based motorcycle keyless ignition and starter using RFID and Blynk Budiada, I Made; Ida Bagus Irawan Purnama; Putri Alit Widyastuti Santiary; I Ketut Swardika; I Nyoman Kusuma Wardana
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 3 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i3.119-127

Abstract

Motorcycles are one of the most widely used means of transportation in the community. However, this widespread usage has led to an increase in thefts, especially when motorcycles are not equipped with adequate security systems. Statistical data shows that motorcycles have the highest theft rate compared to other vehicles. To address this issue, an enhanced security system is necessary. This study proposes the use of Radio Frequency Identification (RFID) sensor and the Blynk application to provide additional security for motorcycles. The RFID system will only be accessible using the motorcycle owner's e-KTP (electronic Indonesian Identity Card) or other registered cards to start the vehicle. Additionally, the Blynk mobile application allows for vehicle control (ON and OFF) via Wi-Fi and provides real-time monitoring of the vehicle's status. This application enables motorcycle activation remotely via Wi-Fi, with a range of approximately 10 meters. Meanwhile, there is a 4-second delay to start the motor starter using e-KTP. Test results indicate that this IoT-based keyless ignition and starter system is effective in enhancing motorcycle security. With this system, motorcycles have a dual-layer security mechanism to minimize theft attempts.
Designing an e-report system as a digital portfolio in early childhood education in Surabaya using the waterfall method Alifkhan, Mochammad Vaif Dwi; Laga, Sinarring Azi
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 3 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i3.146-161

Abstract

This study focuses on the design and implementation of an E-Report system as a digital portfolio for Early Childhood Education in Genteng District, Surabaya. The current manual process using Excel and Canva for generating learning reports limits efficiency and accuracy in tracking children’s developmental progress. To address this, a web-based E-Report system was developed using the Waterfall method to streamline reporting processes, allowing educators to manage children’s data digitally while providing parents accessible, real-time progress reports. Development stages included requirement analysis, system design, and implementation, leveraging modern web technologies for optimal performance. User satisfaction assessments reveal high satisfaction levels, particularly in the system's format (average score of 3.80) and content (average score of 3.65), indicating a strong alignment with user needs. The implementation of the E-Report system is expected to elevate Early Childhood Education services in Genteng District by delivering a more efficient, accurate, and collaborative reporting tool.
Ontology-based data framework for the digital preservation cultural heritage: A case of Subak Hariyanti, Ni Kadek Dessy; Linawati; I Made Oka Widyantara; Gede Sukadarmika
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 3 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i3.135-145

Abstract

Cultural heritage is increasingly fading due to the influence of globalization and social changes that shift traditional values. Digitalization is critical to addressing the degradation of cultural heritage knowledge by enabling more accessible storage and documentation and facilitating preservation and education efforts for future generations. Subak, as a unique traditional agricultural system in Bali, Indonesia, has a wealth of valuable knowledge and culture, but it is still scattered and unstructured. An ontology-based Knowledge Management System is designed to capture, organize, and utilize knowledge within a domain using ontologies as a fundamental component. Ontologies explicitly represent knowledge by providing meaning, properties, and relationships with related concepts. This paper proposes data modelling with the Ontology Development framework for the knowledge base. The methodological framework consists of knowledge externalization, including identifying and collecting knowledge based on data modelling through interviews and observations. The second steps are modelling and development of ontology, based on the knowledge that has been previously disclosed, including the hierarchical structure, properties, and relationships that form the knowledge base. The third stage is the Implementation and evaluation, which involves evaluating the quality of ontology using onto metrics and implementing the ontology into the KMS. The result of this study is data modeling for the knowledge base and the Ontology Development framework. The data modelling is a form of data mapping based on a combination of traditional philosophy and modern management principles that underlie Subak activities and artefacts, namely Tri Hita Karana, Desa Kala Patra, and POAC. The proposed framework can be a reference in developing new ontologies from scratch on unstructured cultural heritage data.
Food Journal: An application for allergy early detection Ciptayani, Putu Indah; Ni Gusti Ayu Putu Harry Saptarini; Ni Wayan Wisswani
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 3 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i3.128-134

Abstract

Allergies are now increasingly common, due to public awareness and lifestyle changes. Although antibody tests and skin pricks can detect allergies, their accuracy is not always 100%, causing some cases of false negatives. Observing the reactions caused by food is an alternative approach, but people often forget the food they consume, especially if the allergic reaction is indirect. Therefore, tools are needed to record foods and reactions, allowing traceability to undetected allergy triggers. This study is applied research that aims to develop a prototype application for recording daily food and tracking the history of eating activities based on the allergy symptoms entered. The software development method used is the Agile method with the Scrum framework. The Scrum framework is used considering that the development of this application requires speed in its provision, and is susceptible to change, so flexibility in development is an absolute must. The software testing was conducted by User Acceptance Testing (UAT) to ensure it meets the user’s needs and requirements. The UAT results are ease of use 3.8, functionality 3.99, user interface (UI) design 3.8, utility 4, and support and help 4. UAT results indicate that the ease of use and UI design have the worst scores and need to be improved, while the utility and support have the best results.
Analysis of financial feasibility installing parking meters in Gianyar Regency (case study: Jalan Ngurah Rai – Gianyar) Tapa, I Gede Fery Surya; Kumara, I Nyoman Indra; Indrashwara, Decky Cipta; Sutapa, I Ketut; Susila, I Nengah Darma
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 15 No. 1 (2025): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v15i1.1-8

Abstract

The increase in the number of motorized vehicles in Gianyar Regency has an impact on parking needs, as is the case on Jalan Ngurah Rai, Gianyar Regency. The data used in this research includes primary data obtained through parking inventory surveys, parking patrol surveys, and secondary data in the form of parking PD income data, parking meter price data, obtained from the Gianyar Regency Transportation Service. Parking characteristics for motorcycles are: parking inventory 95 SRP, parking volume in the 14-hour survey was 2147 vehicles, parking duration was 0.9318 hours, the parking capacity is 102 vehicles/hour, the parking provision is 1356 vehicles, and the parking index is 1,148. Parking characteristics for light vehicles are: parking inventory 88 SRP, parking volume in the 14-hour survey was 837 vehicles, parking duration was 1.0182 hours, the parking capacity is 85 vehicles/hour, the parking provision is 1128 vehicles, and the parking index is 0.92. The financial feasibility analysis for scenario 1 (fixed rate LV= 2000/one parking, MC= 1000/one parking) it is obtained that NPV = 3,153,280,747 > 0, BCR = 1,634 > 1, and IRR = 51% > MARR= 20%. For scenario 2 (fixed parking rate, LV=3000/hour, MC= 2000/hour) we get NPV = 8,998,418,237 > 0, BCR = 2,810 > 1, and IRR = 136%> MARR= 20%. For scenario 3 (fixed parking rate, first hour LV= 3000, MC= 2000, 1 hour later increase in LV= 2000/hour, MC= 1000/hour) obtained NPV = 11,625,402,449 > 0, BCR= 3,338 > 1, and IRR= 174%> MARR= 20%.
Analysis of corn production in Indonesia using business intelligence technology based on Power BI Adesyahputra, Muh Kevin; Rachmawati, Eka Putri
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 15 No. 1 (2025): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v15i1.21-31

Abstract

Corn production trends in Indonesia from 2020 to 2024 were analyzed to address regional disparities and enhance data-driven agricultural decision-making. Datasets from the Ministry of Agriculture and the Central Bureau of Statistics were integrated, transformed, and visualized using Microsoft Power BI, with a focus on evaluating fluctuations in harvested area, production volume, and productivity. Key objectives included identifying challenges linked to fragmented data and external disruptions. An Extract-Transform-Load (ETL) framework harmonized pre-2023 and post-2023 datasets, enabling standardized comparisons across 38 provinces. Results indicated a production peak of 486,000 tons in 2022, followed by a 4.5% decline in 2023 due to adverse climatic conditions and supply chain instability, and partial recovery to 15.2 million tons in 2024. Pronounced regional disparities emerged:  West Java recorded 80 quintals per hectare productivity, while urbanized regions like Jakarta reported negligible output. The analysis underscores the efficacy of Business Intelligence (BI) tools in converting raw agricultural data into strategic insights, offering policymakers pathways to optimize resource allocation, mitigate inequities, and strengthen climate-resilient practices. These outcomes highlight BI’s transformative potential in advancing sustainable agricultural development and adaptive governance frameworks.
Development of a hybrid model for website functional evaluation based on ISO/IEC 25010 and SERVQUAL Prameswari, Ardiva Putri Tava; Setyawan, Muhammad Yusril Helmi
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 15 No. 1 (2025): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v15i1.32-39

Abstract

This study developed a hybrid model based on ISO/IEC 25010 and SERVQUAL to evaluate website quality holistically by combining technical dimensions and user perceptions. ISO / IEC 25010 is an international standard for evaluating the quality of software, including websites, based on technical characteristics such as Functional Suitability, Usability, Reliability, and Security. SERVQUAL, on the other hand, is used to measure quality based on user perception through five main dimensions: Tangibles, Reliability, Responsiveness, Assurance, and Empathy. This study aims to identify the gaps between user expectations and the reality of website performance by using both frameworks. The research method combines quantitative and qualitative approaches, with user surveys and direct observation as data collection tools. The results of the analysis showed that most website quality dimensions, such as Functional Suitability, Usability, Reliability, Responsiveness, and Security, were in the category of "very adequate," with a relatively small gap between actual and expected scores. This study also tested the validity and reliability of constructs using convergent and discriminant analysis, as well as hypothesis testing to identify significant influences between variables. Hypothesis test results show that usability, reliability, and satisfaction variables have a significant influence on user experience. At the same time, factors such as functional fit and physical appearance do not directly affect user experience. This hybrid model provides theoretical contributions by enriching the literature on website Quality Evaluation and practical contributions by providing guidance for website managers to improve the quality of their services based on the identification of gaps between actual performance and user expectations.
Lightweight CNN with wavelet-attention for fingerprint liveness detection Dharma, I Gede Teguh Satya; Astari, Ni Made Ayu Juli
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 15 No. 1 (2025): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v15i1.40-49

Abstract

Fingerprint authentication has been extensively employed as a biometric method in diverse applications, including smartphones and embedded systems. Despite its advantages, this technology is susceptible to spoofing attacks using materials such as gelatin, posing a significant security risk. Numerous solutions have been proposed, but deep learning-based approaches often face challenges due to their large model sizes, limiting deployment in resource-constrained environments. To address this issue, we developed a lightweight and efficient fingerprint liveness detection model by integrating wavelet-attention with inverted-bottleneck convolution. The proposed method balances computational efficiency with high accuracy, enabling its practical implementation on low-resource devices.The model was designed with only 874,000 parameters and a memory footprint of 4 MB, representing a significant reduction in size compared to conventional deep learning models. The use of wavelet-attention enhances feature extraction by focusing on multi-scale spatial details crucial for distinguishing live and spoof fingerprints. Extensive experiments were conducted on the LivDet dataset and a custom dataset, encompassing fingerprints captured from multiple sensors.The results demonstrated robust performance, achieving an average classification error (ACE) of 2.27 across various sensors, which is competitive with state-of-the-art methods. Additionally, the model exhibited consistent performance in scenarios with limited computational resources, highlighting its efficiency and scalability.These findings suggest that the proposed approach is a viable solution for enhancing the reliability of fingerprint liveness detection, particularly in applications requiring lightweight and resource-efficient models.

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