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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.