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Journal : JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI

Sistem Diagnosa Stunting Menggunakan Teorema Bayes Kamto, Kevin Arsan; Purnomo, Agus Sidiq
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.8040

Abstract

Stunting is a chronic nutritional problem that impacts children's physical and cognitive growth. This research develops an expert system based on Bayes' Theorem to diagnose stunting, and utilizes artificial intelligence (AI) technology. The Bayes Theorem method is used for its ability to overcome data uncertainty and produce more accurate decisions. Data was collected through interviews with pediatricians and medical records from posyandu. The system was designed using flowcharts and DFD, then implemented and tested with samples of 30 children from the Kaligrenjeng Village Posyandu. The results of the diagnosis showed a 100% accuracy rate. Validation of the results shows the expert system according to the expert's diagnosis.
Analisis Kepuasan Pelanggan Terhadap Kinerja Layanan Air Bersih Menggunakan Metode TOPSIS (Studi Kasus PDAM Wilayah Pontianak) Marsela, Dwi; Purnomo, Agus Sidiq
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Regional Drinking Water Company (PDAM) has an important role in providing clean water services for the community. Customer satisfaction is a crucial aspect that needs to be considered to improve PDAM performance. This research aims to analyze customer satisfaction with PDAM performance in Pontianak area and optimize clean water service by using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in decision support system. The TOPSIS method is a multi-criteria decision-making method that can evaluate alternatives based on established criteria. Customer satisfaction data will be collected through surveys and processed using the TOPSIS methodology to produce an alternative ranking of service improvements. The results of this study are expected to provide recommendations for PDAM in optimizing performance and improving the quality of clean water services in Pontianak area based on customer preferences
Sistem Pakar Diagnosa Penyakit Gigi Menggunakan Metode Naive Bayes Fauzyah, Luthfia; Purnomo, Agus Sidiq
JATISI Vol 12 No 3 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i3.12414

Abstract

A Public awareness of the importance of maintaining dental and oral health remains relatively low, even though disorders in this area can lead to serious complications such as infections, abscesses, and systemic diseases. On the other hand, limited access to dental health services due to uneven distribution of medical personnel and high consultation costs presents a significant challenge. To address this issue, this study developed an expert system for diagnosing dental diseases using the Naive Bayes method. This method applies a probabilistic classification approach to predict disease based on observed symptoms. Data were obtained through interviews with dentists and collection of real case data at Puskesmas Imbanagara. The system was tested using 50 patient cases, with results showing 48 diagnoses matched the expert's opinion, achieving an accuracy rate of 96%. These results demonstrate that the Naive Bayes method is effective for early-stage dental disease diagnosis. The system offers a practical solution to assist the public in recognizing symptoms independently before seeking professional consultation.
Co-Authors Ade Fitriadin Agung Prinato Alfian Romadhon Andres Anief Fauzan Rozi Anief Fauzan Rozi Anief Fauzan Rozi Anief Fauzan Rozi Ari Cahyono Arif Wiji Setiyanto Arifi Zulaika Aris Susanto Bagas Irvan Bagaskara Barbo Bero Berita Estu Widodo Bima Pangestu, Danang Bowo Nugroho Dany Suktiawan Irman Fiano Dede Widiyanto, Dede Widiyanto Disantis Dwiki Kurniawan, Yohanes Edwin Rafiza Pradana Nasution Elisabeth Helsi Nggebu Emi Agustina Erlangga Samudera Kencana Fandi Azis Fauzan Rozi, Anief Fauzyah, Luthfia Feby Kristina Butar Butar Fendy Nugraha, Arbiana Fernando Bayu Andika Ficky Septian Ali Gaputra, Raygo Gita Prastianingrum Hafiid Alfayed, Muhammed Herdiansyah, Moch Rizal Hukom, Jessy Indah Susilawati Ismunu, R. Sumarwan Jery Mechael Pentagon Lumbantoruan Jevi Ariyanti Kadek Ayu Puspita Dewi Kali, Steven Kamto, Kevin Arsan Letsoin, Amrul Louis Fernando Sinaga M. Ridwan Nur Septian Malela, Prabu Aji Maria Mitro Wid Eko, Antonius Marsela, Dwi Mohamad Akbar Mokoagow Mutaqin Akbar Muthia Gidriani Maelan Na'imah, Alifatun Nadafi'ah Hari Fitri Natalia Anjela Sagat Nisriina Nuur Hasanah Octy Kartika Dewi Putri, Novita Anggraini Rahmandhita Fikri Sannawira Rahmandhita Fikri Sannawira, Rahmandhita Fikri Ridi Ferdiana Rika Handayani Robi Adi Saputra Rosmeri Maramba Santoso, Muhammad Iqbal Rafid Sembiring, Kristian Eykman Stefanus M Patanduk Subardjo, Ratna Yunita Setiyani Supatman Supatman Susanto, Handy Tri Astuti Prihatin Wahyu A, Shella Widatin Mayasari Wijaya, Andi Atmaja Kusuma Wijayanti, Berlian Rezki Wulan Sari Kaslumin Yasser Yazid Mohammad Yuliana Rahayaan Yulisa Safitri Zelvia Olga Maharani