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All Journal International Journal of Electrical and Computer Engineering Natural Science: Journal of Science and Technology JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Sistemasi: Jurnal Sistem Informasi JURNAL ILMIAH MATEMATIKA DAN TERAPAN Communication in Biomathematical Sciences Fraktal: Jurnal Matematika dan Pendidikan Matematika IJoICT (International Journal on Information and Communication Technology)

Agus Indra Jaya

Tadulako University

Author-ID : 291762

Computer Science & IT Electrical & Electronics Engineering Environmental Science Mathematics Social Sciences

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OPTIMALISASI PENDISTRIBUSIAN BERAS DI PENGGILINGAN PADI KARDI JAYA UTAMA TOLAI DENGAN MENGGUNAKAN METODE GOAL PROGRAMMING Fatmayoni, Raisan; Jaya, Agus Indra; Resnawati, Resnawati
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 13 No. 1 (2016)
Publisher : Program Studi Matematika, Universitas Tadulako

OPTIMALISASI PENDISTRIBUSIAN BERAS DI PENGGILINGAN PADI KARDI JAYA UTAMA TOLAI DENGAN MENGGUNAKAN METODE GOAL PROGRAMMING

MENGEFISIENSIKAN PENGGUNAAN ENERGI LISTRIK : STUDI KASUS PADA MODEL ALIRAN PANAS PADA WATER COOKER (PEMANAS AIR ELEKTRIK) Husnah, Siti; Jaya, Agus Indra; Ratianingsih, Rina
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 13 No. 1 (2016)
Publisher : Program Studi Matematika, Universitas Tadulako

MENGEFISIENSIKAN PENGGUNAAN ENERGI LISTRIK : STUDI KASUS PADA MODEL ALIRAN PANAS PADA WATER COOKER (PEMANAS AIR ELEKTRIK)

Penerapan Model Antrian Untuk Mengoptimalisasikan Pelayanan Pada Loket Pengambilan Obat Di Puskesmas Desa Meko Molanu, Irmawati; Jaya, Agus Indra; Nacong, Nasria
Fraktal : Jurnal Matematika dan Pendidikan Matematika Vol 5 No 2 (2024): November 2024
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/fractal.v5i2.17264

Queuing is a waiting line state where a number of entrants are involved to get services from a service providing facility. One example of queuing activities that are common in the community is taking medicine at the Meko Village Health Center. The purpose of this study was to obtain an optimal queuing model at the drug collection counter at the Meko Village Health Center. Based on the analysis, at this time the service at the drug collection counter at the Meko Village health center that uses queues with a single channel single phase (M/M/1) model is not optimal. To optimize services, the application of the multi-channel single phase multiple line queue model (M/M/c) where c = 3 results in a measure of system performance, namely the probability of no customers in the system ( ) is 0.034 = 3.4%, the service utility rate (ρ) is 0.866 = 86.6%, number patient in the queue ( ) is 5 customers, number patient in the system ( ) is 8 customers, waiting time in the queue ( ) is 22,38 minutes, and waiting time in the system ( ) is 34,38 minutes. By applying the multi-channel single phase (M/M/c) multiple line queue model, it becomes an alternative solution in providing good and optimal service to patients at the Meko Village health center.

Low-dose computed tomography image denoising using graph wavelet transform with optimal base Setiawan, Iwan; Hidayat, Rachmat; Najar, Abdul Mahatir; Jaya, Agus Indra; Rosiyadi, Didi
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1696-1708

Noise in electronic components of computed tomography (CT) detectors behaves like a virus that infects visual quality of CT scans and might distort clinical diagnosis. Modern CT detector technology incorporates high-quality electronic components in conjunction with signal and image processing to ensure optimal image quality while retaining benign doses of x-rays. In this study, a new strategy in signal and image processing directions is proposed by finding the most optimal wavelet base for denoising low-dose CT scan data. The process begins by selecting the appropriate wavelet bases for CT image denoising, followed by a wavelet decomposition, thresholding, and reconstruction. Other methods, such as graph wavelet and learning-based, are used to assess the consistency of the outcomes. The wavelet base of biorthogonal 5.5 achieves the highest optimum performance for CT image denoising. Meanwhile, the Daubechies wavelet base is inconsistent and performs poorly compared to the optimum base. This research highlights the importance of wavelet properties such as orthogonality, regularity, and the number of vanishing moments in selecting an appropriate wavelet basis for noise reduction in CT images.

Revealing the Relationship of Batik Motifs Using Convolutional Neural Network Najar, Abdul Mahatir; Abu, Maulidyani; Ratianingsih, Rina; Jaya, Agus Indra
Sistemasi: Jurnal Sistem Informasi Vol 13, No 5 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i5.4480

This study explores the use of Convolutional Neural Network to identify and classify regional batik motifs, a significant aspect of Indonesian cultural heritage. The CNN model was optimized with Adam optimizer and used to extract distinctive features from the batik patterns. Subsequently, a hierarchical clustering method was employed to construct a relationship tree depicting the link between batik motifs based on their region. The research findings demonstrate that the CNN model effectively classifies batik motifs with an accuracy of up to 88%. The study provides insights into the intricate connections between regional batik designs and contributes to the preservation and understanding of Indonesia's cultural heritage.

StuntCare: Digital Innovation for Early Warning of Stunting-Risk Families in Sigi Regency Maulidyani Abu; Moh.Al-fath Salsabilah; Juni Wijayanti Puspita; Resnawati; Abdul Mahatir Najar; Rina Ratianingsih; Agus Indra Jaya; Abunawas Tjaija
IJoICT (International Journal on Information and Communication Technology) Vol. 11 No. 1 (2025): Vol. 11 No. 1 Jun 2025
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v11i1.9111

The Prevalence of Stunting in Sigi Regency remains notably high at 36.8%, significantly above the national target. Stunting is frequently caused by recurrent infections, poor sanitation, and chronic nutritional deficiencies. Since stunting is a condition of chronic malnutrition that impairs a child's physical and cognitive development, an early warning system is essential for prevention. This study proposes the development of a web-based application to predict the risk of stunting in vulnerable families. Families are the primary focus as they serve as the first environment where children grow and develop. If risk factors are present within a family, the likelihood of stunting increases. Therefore, early detection is crucial for mapping family health conditions. By predicting stunting risks, families can take preventive measures before the condition severely impacts the child. This early warning system serves as a critical alarm, encouraging families to be more vigilant in maintaining the health of all household members. The stunting prediction system is developed as a web-based application, utilizing 11 variables for early stunting detection and employing the K-Nearest Neighbor (K-NN) method. The model's accuracy is evaluated using a Confusion Matrix, achieving an accuracy rate of 99.991%. Keywords: Early Warning System, Stunting, Classification, K-Nearest Neighbor, Confusion Matrix

Co-Authors Abda Abda Abdul Mahatir Najar Abunawas Tjaija Agusman Sahari Ahmad, M T Akram, Akram Ardilawati, Ni Made Asran, Erni Endang Susilawati Fadilah, R Fadjryani, Fadjryani Fadly, M Fatmayoni, Raisan Febrianti, Ratih Gusni, Gusni Hajar Husnah, Siti I Wati Ica Murwanti Indra Wati Ismawati, Nurul Iwan Setiawan Juni Wijayanti Puspita Maasawet, R R Marwan Marwan Maulidyani Abu Moh.Al-fath Salsabilah Molanu, Irmawati Nasria Nacong Natalia, Heinny Nirmalasari, Ririn Nuranisa, Nuranisa Nurul Ikrima Nurul Ismawati Nyamun, Suwito S Puragombo, Rista RACHMAT HIDAYAT Ratianigsih, Rina Resnawati Resnawati Rina Ratianingsih Rosiyadi, Didi Setiawaty, R Siti Helmyati Wahyuni, Ni Luh Sri

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