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All Journal Pena Teknik : Jurnal Ilmiah Ilmu-ilmu Teknik Jurnal Teknik Industri Terintegrasi (JUTIN) Journal of Computer and Information System (J-CIS) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Ceddi Journal of Information System and Technology (JST) Journal of Embedded Systems, Security and Intelligent Systems Journal of Mathematics and Applied Statistics
Arsan Kumala Jaya
Politeknik Negeri Samarinda
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Transportation

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Development of Client Server-Based Queuing Applications at The Samsat Gowa Office Arsan Kumala Jaya; Akbar Hendra; Muhammad Sabirin Hadis; Muhammad Rizal; Randy Angriawan; Annisa Nurul Puteri
Ceddi Journal of Information System and Technology (JST) Vol. 1 No. 2 (2022): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (925.604 KB) | DOI: 10.56134/jst.v1i2.19

Abstract

The government has established a SAMSAT (One-Stop Manunggal Administration System) office which has duties in the motor vehicle tax service. Queuing activities make people spend their time waiting. Therefore, it is necessary to create a queuing system that can inform the estimated queue time remotely. The queuing system does not require users to wait physically, so the waiting time needed to queue can be used by taxpayers to carry out their own personal and work activities that are more useful. Queuing application development aims to develop queuing service features from previous applications which only provide queued information on taxpayers. Features developed in the form of queuing data processing with different activities, monitoring information on time and queue status periodically. The research method used is SDLC (Software Development Life Cycle) with a prototype model. The test results using the Gray Box Testing method show that queuing applications in government agencies providing motorized vehicle tax services have been successfully developed.
Development of Client Server-Based Queuing Applications at The Samsat Gowa Office Kumala Jaya, Arsan; Hendra, Akbar; Muhammad Sabirin Hadis; Muhammad Rizal; Randy Angriawan; Annisa Nurul Puteri
Ceddi Journal of Information System and Technology (JST) Vol. 1 No. 2 (2022): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v1i2.19

Abstract

The government has established a SAMSAT (One-Stop Manunggal Administration System) office, which has duties in the motor vehicle tax service. Queuing activities make people spend their time waiting. Therefore, it is necessary to create a queuing system that can inform the estimated queue time remotely. The queuing system does not require users to wait physically, so the waiting time needed to queue can be used by taxpayers to carry out their own personal and work activities that are more useful. Queuing application development aims to develop queuing service features from previous applications, which only provide queued information on taxpayers. Features developed in the form of queuing data processing with different activities, monitoring information on time, and queue status periodically. The research method used is SDLC (Software Development Life Cycle) with a prototype model. The test results using the Gray Box Testing method show that queuing applications in government agencies providing motorized vehicle tax services have been successfully developed.
Bayesian Intelligent Tutoring System for Vocational High Schools Muhammad Ikhwan Burhan; Arsan Kumala Jaya; Luthon Adira
PENA TEKNIK: Jurnal Ilmiah Ilmu-Ilmu Teknik VOLUME 9 NUMBER 1 MARCH 2024
Publisher : Faculty of Engineering, Andi Djemma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51557/pt_jiit.v9i1.2415

Abstract

The absence of individualized tutorials during regular school hours has resulted in a suboptimal learning method at Vocational High Schools(SMK), limiting students' ability to reach their optimum competency. Several Computerized self-study systems have been created as potential solutions to these challenges. Regrettably, a notable drawback of the system lies in its failure to address students' diverse range of abilities adequately. This study presents a proposed model for an Intelligent Tutoring System (ITS) utilizing the Bayesian Network (BN) at Vocational High Schools. The model aims to assess students' proficiency levels and deliver skill-based instructional materials tailored to individual students' abilities. This type of research is called research and development (RD), to develop and know the validity of a product. The system under development will undergo trials within the Computer and Network Engineering (TKJ) program at SMK Negeri 4 Gowa. These trials will employ a quasi-experimental approach, explicitly utilizing a one-group pretest-posttest design.The findings indicated that there were notable disparities in the learning outcomes of students following the implementation of the proposed ITS. To put it otherwise, the proposed ITS has improved students' proficiency in Vocational High Schools. The evaluation outcomes suggest that the BN model had a significant level of accuracy, reaching 84%.
Identifikasi Status Stunting menggunakan Metode Klasifikasi Pemrosesan Citra: Systematic Literature Review Putri, Mindi Richia; Putra, Ahmad Fatoni Dwi; Asmaul Husna; Arsan Kumala Jaya; Muhammad Ari Rifqi
Journal of Computer and Information System ( J-CIS ) Vol 8 No 1 (2025): J-CIS Vol. 8 No. 1 Tahun 2025
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jcis.v8i1.5061

Abstract

Stunting adalah masalah kesehatan yang signifikan di Indonesia yang memengaruhi pertumbuhan fisik, perkembangan kognitif, dan kualitas sumber daya manusia di masa depan. Laporan dari Organisasi Kesehatan Dunia (WHO) menyatakan bahwa prevalensi stunting di Indonesia mencapai 21,6% pada tahun 2022. Untuk mengklasifikasikan stunting, metode konvensional seperti pengukuran antropometri manusal masih digunakan, tetapi memiliki keterbatasan seperti bergantung pada tenaga medis, memiliki kemungkinan kesalahan, dan sulit diakses di daerah terpencil. Tujuan dari penelitian ini adalah untuk mengevaluasi teknologi dan pemrosesan citra sebagai alternatif untuk metode deteksi stunting yang lebih akurat dan efektif. Hasil penelitian menunjukkan bahwa teknologi dan algoritma seperti MediaPipe Pose memiliki akurasi 98,48%, Deep Neural Nets (DNN) 93,83%, dan Support Vector Machine (SVM) 91,1%. Algortima CNN lebih efektif dalam menganalisis gambar secara otomatis terutama untuk dataset besa dan algortima SVM efektif untuk dataset kecil-menengah dengan dukungan ekstraksi fitur. Peneliti merekomendasikan untuk menggabungkan kedua metode ini untuk membuat sistem deteksi stunting yang lebih cepat, akurat, dan efisien. Temuan ini diharapkan dapat berfungsi sebagai titik acuan penting dalam proses pengembangan inovasi di bidang kesehatan anak di Indonesia.
Designing a Web Application for Recognizing Past Learning Using the Laravel Framework Jaya, Arsan Kumala; Hanif, Abdullah; Triadi, Fara; Biabdillah, Fajerin
Journal of Mathematics and Applied Statistics Vol. 2 No. 2 (2024): December 2024
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/mathstat.v2i2.239

Abstract

This study aims to provide information on the application design process using the Laravel framework. This study aims to design a web application that can help higher education institutions manage students who take prior learning recognition (RPL) classes effectively and efficiently. The problem often faced by universities is the difficulty in recording the formal/non-formal education history of RPL students. This application is expected to provide a solution by providing features such as recording education history, training history, conference history, award history, organizational history, and employment history. The system development method used in the design is the System Development Life Cycle (SDLC) by utilizing the Laravel framework as a framework for the system development process. The expected results of this study are a web application that is user-friendly, reliable, and able to increase the efficiency of student data collection in universities.
Impulsive Purchase with Vision Transformer Prediction of Vehicular Perception System for Fast-Food Outlets in Urban Traffic Congestion Biabdillah, Fajerin; Ismayanti, Rika; Hartanto, Subhan; Jaya, Arsan Kumala
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 8 No. 4 (2025): October
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v8i4.53140

Abstract

Urban traffic congestion creates a unique environment where drivers are often captive audiences to roadside fast-food outlets and advertisements. This paper proposes a vision-driven impulsive purchase prediction system that simulates human-like vehicle vision using a Vision Transformer (ViT) model to detect fast-food outlet visibility, crowd levels, and promotional banner exposure in real-time. By integrating these visual cues, our system predicts the likelihood of impulsive stopping behavior (the “impulse score”) of drivers in heavy traffic. We collected and analyzed visual data from congested thoroughfares in major Indonesian cities (Jakarta, Surabaya, Bandung) known for severe traffic jams. The proposed ViT-based model was trained to identify key features such as recognizable outlet signage, drive-thru queue lengths, and promotional signage, mirroring the attention patterns of human drivers. Experimental results demonstrate that the model achieves high accuracy in detecting relevant cues and predicting impulsive purchase decisions, with a mean absolute percentage error (MAPE) of around 12% in forecasting impulse stop rates. This work is the first to leverage a transformer-driven computer vision approach for modeling consumer impulsivity in traffic, bridging automotive perception and marketing analytics. The findings suggest that smart vehicle systems and urban planners can benefit from such technology to anticipate consumer behavior in traffic, optimize roadside advertising, and manage congestion-related demand surges at fast-food outlets.
Identification of Speech Recognition Using K-Nearest Neighbor Method Hanif, Abdullah; Triadi, Fara; Jaya, Arsan Kumala; Hartanto, Subhan; Basir, Azhar
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 1 (2026): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i1.56699

Abstract

Speech is a part of the human that has unique characteristics so that it can be distinguished from one person with someone else. Speech delivered, has a variety of information so that in its application it can be used to carry out voice commands using speech. In signal processing, Mel Frequency Cepstrum Coefficient (MFCC) is a method used for feature extraction. In this study, MFCC is used as a feature extraction method using Matlab R2017a and K-Nearest Neighbor (KNN) software used to identify and classify voice commands spoken by the speaker using speech pattern patterns obtained from the MFCC. This study uses 10 training data for each voice command word consisting of open, close, message and gallery, and 5 test data for each voice command word. Voice data is used using different words and different speakers. This research yields an accuracy level of 60% in voice Buka, 60% in voice Tutup, 60% in voice Pesan and 65% in voice Galeri.
Carbon Emission Simulation at the Slamet Riyadi Three-Way Intersection in Samarinda City Using Urban Mobility Simulation Arsan Kumala Jaya; Fara Triadi; Abdullah Hanif
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 2 (2025): June 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i2.8212

Abstract

This study uses Simulation Urban Mobility (SUMO) to simulate carbon emissions at the Slamet Riyadi Samarinda intersection. One of the big cities in Indonesia, Samarinda, faces major problems related to increasing traffic volume and its impact on air quality, especially carbon emissions. This simulation uses various traffic parameters, such as vehicle density, red light duration, and vehicle type. The purpose of this simulation is to evaluate the level of carbon emissions produced by vehicles passing through the intersection. The simulation begins by collecting traffic data and then converting it into an XML file that can be read by SUMO. This XML file contains information about traffic parameters, road networks, and vehicles. According to the simulation results, trucks contributed the most emissions per vehicle, with a total emission of almost 18,500 grams of CO₂ per hour. Traffic scenarios under real-world conditions were simulated using the SUMO tool with HBEFA-based emission models.. This study is expected to provide a clearer picture of the impact of traffic on the environment as well as recommendations for more effective traffic management strategies to reduce carbon emissions in Samarinda City.
Agile-Based Accreditation Module Design for the P3M Information System at Politeknik Negeri Samarinda Arsan Kumala Jaya; Fara Triadi; Subhan Hartanto; Ahmad Saiful Mutaqi Azis; Priti Shinta
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10320

Abstract

Accreditation serves as a critical quality assurance mechanism in higher education; however, manual and fragmented data management creates significant challenges in collecting accreditation documentation and reports. This research designs and develops an Accreditation Menu for the P3M Information System at Politeknik Negeri Samarinda to streamline accreditation processes with greater effectiveness, efficiency, and accountability. Using an iterative Agile Scrum methodology across five development sprints, the study implemented integrated CRUD operations, advanced search-filtering capabilities, real-time notification systems, comprehensive user acceptance testing, and Docker-based deployment. Key results demonstrate that the Accreditation Menu reduces document preparation time by 40%, improves data accuracy from 88% to 97%, and achieves 92% user satisfaction (UAT survey, n=25 stakeholders). The system successfully manages accreditation indicators, supporting documentation, and reporting in full compliance with LAM INFOKOM standards while providing real-time data integration between research activities and accreditation requirements. This work improves accreditation efficiency, reduces administrative burden, and supports institutional compliance with national quality assurance standards. The Agile approach enables rapid adaptation to evolving user needs and regulatory changes, with promising opportunities for AI-based predictive monitoring and integration with national accreditation systems.
Hybrid Regression–Simulation Model for Evaluating Emission Policies in Oversaturated Urban Corridors: A Case Study of Jakarta Fara Triadi; Arsan Kumala Jaya; Fajerin Biabdillah; Abdul Hanif
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10595

Abstract

Urban traffic emissions continue to escalate in Southeast Asian megacities, particularly along oversaturated central business district corridors where chronic congestion amplifies pollutant accumulation. Previous research often separates statistical emission modelling from microscopic simulation, limiting the ability to evaluate policy impacts under real-world saturation conditions. This study aims to assess whether lane-level transport interventions specifically bus-only lanes and motorcycle restrictions can reduce emissions in a hyper-congested Jakarta corridor through an integrated analytical approach. A hybrid regression–microsimulation framework was developed by combining multiple linear regression with SUMO-based traffic simulation. An hourly dataset of traffic flow and CO emissions (n = 8,760) from the Thamrin–Bundaran HI corridor was used to construct a regression model enriched with temporal and lagged predictors. The resulting emission profiles were embedded into SUMO to simulate baseline, bus-lane, and motorcycle-restriction scenarios. The regression model achieved strong predictive performance (R² = 0.692, RMSE = 0.252), with CO_lag1 confirmed as the dominant predictor. Simulation results showed fully overlapping CO₂ emission trajectories across all scenarios, indicating that lane-based interventions do not alter traffic states or emissions under oversaturated conditions. Structural congestion constrains the effectiveness of lane-level policies. Meaningful emission reductions require systemic strategies such as demand management, modal shift, or network redesign. The proposed hybrid framework provides a replicable tool for evaluating transport policies in dense urban corridors
Co-Authors Abdul Hanif Abdullah Hanif Ade Irawan Agus Triyono Ahmad Fatoni Dwi Putra Ahmad Saiful Mutaqi Azis Akbar Hendra Annisa Nurul Puteri Asmaul Husna RS Basir, Azhar Fajerin Biabdillah Fara Triadi Fara Triadi Hanif, Abdullah Hartanto, Subhan Hendra, Akbar Ismayanti, Rika Luthon Adira Mindi Richia Putri Muhammad Ari Rifqi Muhammad Ikhwan Burhan Muhammad Rizal Muhammad Sabirin Hadis Muhammad Sabirin Hadis Priti Shinta Randy Angriawan Randy Angriawan Rika Ismayanti Rizka Tri Wulandari Putri Subhan Hartanto