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All Journal Jurnal Media Infotama Jurnal Inspiration International Journal of Artificial Intelligence Research JUKI : Jurnal Komputer dan Informatika Journal of Innovation Information Technology and Application (JINITA) Indonesian Journal of Engineering Research Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Digital Transformation Technology (Digitech) Journal of Informatics and Electronics Engineering SATIN - Sains dan Teknologi Informasi Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Jurnal Kewirausahaan dan Bisnis Jurnal Komputer, Informasi dan Teknologi
Fredricka, Jhoanne
Universitas Dehasen Bengkulu
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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Implementasi Metode Simple Additive Weighting (SAW) Pada Sistem Pendukung Keputusan Untuk Seleksi Calon Petugas Sensus Di Badan Pusat Statistik Seluma Deko Aribowo; Yupianti Yupianti; Jhoanne Fredricka
Jurnal Media Infotama Vol 20 No 2 (2024): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i2.6853

Abstract

Central Bureau of Statistics is an institution tasked with providing quality statistical data through statistical activities that are integrated and have national and international standards. The purpose of this research is to produce a decision support system application for selecting prospective census officers at Central Bureau of Statistics of Seluma using Simple Additive Weighting (SAW) method. SAW is one of the methods used to solve problems. A decision Support System for the selection of prospective census officers at Central Bureau of Statistics of Seluma was created using PHP Programming Language and MySQL Database. This application can accommodate data on prospective census officers who will be assessed. This application can be used to facilitate the selection of prospective census officers at Central Bureau of Statistics of Seluma by applying SAW method which can rank the assessment results.
Implementasi Algoritma Probabilitas Symetric Dalam Mendiagnosa Penyakit Akibat Gangguan Gizi Devi Risianti; Maryaningsih Maryaningsih; Jhoanne Fredricka
Jurnal Media Infotama Vol 21 No 1 (2025): April 2025
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i1.8030

Abstract

This research aims to implementation the symetric probability algorithm in building an expert system to diagnose diseases due by nutritional disorders. Disturbances in nutritional balance can cause a person's performance in activities to be not optimal and can even cause diseases that will interfere with daily routines. The lack of knowledge and concern for nutritional balance in the body is the cause of the emergence of health problems, in addition to the difficulty of access to consult a doctor also causes people to be less concerned about nutritional balance disorders. To overcome these problems, it is necessary to build an expert system to help someone diagnose diseases due to nutritional disorders and solutions that can be done online so that it is expected to facilitate users. The implementation of symetric probability used in this expert system can provide diagnoses of nutritional disorders expressed as a percentage to measure the certainty value of a hypothesis against a fact of disease due to nutritional disorders experienced by adults. This expert system was built using PHP programming language and MySQL database. This expert system can be used as a tool that makes it easier for people to diagnose early symptoms of diseases due to nutritional disorders because it can be accessed online.
Sistem Pendukung Keputusan Dalam Kelayakan Penerima Bantuan PKH Menggunakan Metode Multi Objective Optimization On The Basic Of Rat Io Analysis (MOORA) Widia Sari; Herlina Latipa Sari; Jhoanne Fredricka
Jurnal Media Infotama Vol 21 No 2 (2025): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i2.9185

Abstract

The Family Hope Program (PKH) is one of the government's efforts to overcome poverty by providing social assistance to poor families. However, selecting the right and objective recipients of assistance is an important challenge to ensure that the assistance is right on target. This study aims to develop a decision support system (DSS) in determining the eligibility of PKH assistance recipients using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method. The MOORA method was chosen because of its ability to process several criteria simultaneously, So that it can provide more accurate and objective decisions. The system considers various criteria such as income level, number of family members, and socio-economic status to calculate the eligibility score of aid recipients. The results of this system are expected to provide recommendations for PKH aid recipients that are more efficient, fair, and in line with government priorities. The trials conducted on aid recipient data are expected to demonstrate the accuracy and effectiveness of the system in facilitating more precise and transparent decision-making.
Penerapan Metode K-Means Dalam Pengelompokan Data Siswa Berdasarkan Masalah Akademik Di SMA Negeri Selangit Chindy Asher; Jhoanne Fredricka; Rizka Tri Alinse
Jurnal Media Infotama Vol 21 No 2 (2025): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i2.9370

Abstract

Selangit State High School does not yet have a system that can help identify students' academic problems. Until now, the school has only manually recorded each student's disciplinary violations as a point system by observing the violations committed by students, and at the end of the semester, all violation points are calculated. However, this process takes a considerable amount of time, as each student's violation points must be calculated individually, resulting in a lengthy process to determine the appropriate sanctions for each student. The application of the k-means method in grouping student data based on academic issues at Selangit State Senior High School can help the school obtain more specific information regarding students' academic issues and can be used as a benchmark in assisting with evaluations and counseling for students grouped based on academic issues. Based on the test data used in the odd semester of the 2024/2025 academic year, involving 30 students who committed violations, the results showed that cluster C1 had 12 students with sanctions in the form of reprimands, cluster C2 had 10 students with written warnings, cluster C3 had 0 students with suspension warnings, cluster C4 had 5 students with disciplinary action, and cluster C5 had 3 students.
Sistem Pakar Diagnosis Gangguan Jiwa Dengan Metode Case Base Reasoning (CBR) Dan Similarity Probabilistic Symmetric M Zuhri; Yupianti Yupianti; Jhoanne Fredricka
Jurnal Media Infotama Vol 22 No 1 (2026): April 2026
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v22i1.10276

Abstract

This study develops an expert system for diagnosing mental disorders using the Case Based Reasoning (CBR) method and the Symmetric Similarity Method to detect types of psychiatric disorders based on patient symptoms. The CBR method is used to reason about new cases by comparing them to past cases stored in the knowledge base, while the Symmetric Similarity Method is used to calculate the degree of similarity between those cases. The research was conducted at Soeprapto Psychiatric Hospital (RSJ Soeprapto) in Bengkulu and developed the diagnostic expert system using Laravel and MySQL. With this system, the diagnostic process can be carried out more quickly and efficiently, and it can be used by the public for early detection before receiving a direct examination from a psychiatric specialist.
Expert System For Diagnosing Mental Disorders At Soeprapto Special Psychiatric Hospital Bengkulu Province Using The Forward Chaining Method Ahmad Syukron Ali; Siswanto Siswanto; Jhoanne Fredricka
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.9034

Abstract

Expert systems are a branch of artificial intelligence designed to mimic the ability of an expert to make decisions or solve problems in a particular field. This study aims to develop a web-based expert system capable of performing diagnoses using the forward chaining method as an inference mechanism. This system is intended to help the public recognize specific problems, particularly in the field of health. Unfortunately, people often lack access to professional psychological services. This study aims to build web-based expert system that can help make an initial diagnosis of mental disorders using forward chaining method. This system is designed to collect symptoms from users, process them using a rule base determined by experts, and provide automatic diagnosis results. In its development, the system uses the PHP programming language and MySQL database to store symptom data, disease information, and consultation results. The inference process is conducted sequentially (forward chaining) based on the symptoms selected by the user until a conclusion is reached regarding the type of mental disorder and its likelihood. Testing results indicate that the system can provide reasonably accurate results in identifying users' mental conditions based on the symptoms entered. This system is expected to serve as a useful initial consultation tool, particularly in communities with limited access to mental health services. However, this system is not intended to replace the role of professionals but rather as a form of technological support to aid in early detection.
The Implementation Of Mamdani Fuzzy Inference In Expert System For Diagnosing Hyperthyroid Disease Rinaldi Rinaldi; Masterjon Masterjon; Jhoanne Fredricka
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.9094

Abstract

Hyperthyroid disease is a type of cancer in which cancer cells multiply in the thyroid issue. Diagnosis of hyperthyroid disease is difficult because the symptoms of thyroid disease can vary depending on the rise and fall of thyroid hormones which inscrease the use of oxygen by body cells. However, the limited number of doctors in handling this disease make it difficult for user to consult directly about this hyperthyroid disease. So to overcome this problem, an expert system is needed to diagnose thyroid disease based on patient clinical data online to help patients or the public to consult independently. This expert system use fuzzy mamdani Method using PHP programming language and MySQL database. The result of expert system can provide convenience for useer to diagnose early hyperthyroid disease.
Expert System for Diagnosing Mental Disorders at Soeprapto Psychiatric Hospital in Bengkulu Province Using Forward Chaining Method Ahmad Syukron Ali; Siswanto Siswanto; Jhoanne Fredricka
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.9426

Abstract

Expert systems are a branch of artificial intelligence designed to mimic the ability of an expert to make decisions or solve problems in a particular field. This study aims to develop a web-based expert system capable of performing diagnoses using the forward chaining method as an inference mechanism. This system is intended to help the public recognize specific problems, particularly in the field of health. Unfortunately, people often lack access to professional psychological services. This study aims to build web-based expert system that can help make an initial diagnosis of mental disorders using forward chaining method. This system is designed to collect symptoms from users, process them using a rule base determined by experts, and provide automatic diagnosis results. In its development, the system uses the PHP programming language and MySQL database to store symptom data, disease information, and consultation results. The inference process is conducted sequentially (forward chaining) based on the symptoms selected by the user until a conclusion is reached regarding the type of mental disorder and its likelihood. Testing results indicate that the system can provide reasonably accurate results in identifying users' mental conditions based on the symptoms entered. This system is expected to serve as a useful initial consultation tool, particularly in communities with limited access to mental health services. However, this system is not intended to replace the role of professionals but rather as a form of technological support to aid in early detection.
Implementasi Metode Certainty Factor pada Sistem Pakar untuk Mendiagnosa Karies Gigi pada Klinik Gigi Drg. Haikal Mendalia Hasanah; Jhoanne Fredricka; Devina Ninosari
Digital Transformation Technology Vol. 6 No. 1 (2026): Periode Maret 2026
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v6i1.8637

Abstract

Karies gigi merupakan penyakit pada jaringan keras gigi yang banyak dialami masyarakat dan dapat menyebabkan kerusakan gigi apabila tidak ditangani sejak dini. Kurangnya pengetahuan masyarakat mengenai gejala karies serta keterbatasan konsultasi dengan dokter gigi menyebabkan proses diagnosis awal sering terlambat dilakukan. Penelitian ini bertujuan untuk merancang dan membangun sistem pakar diagnosis penyakit karies gigi menggunakan metode Certainty Factor dengan bahasa pemrograman PHP dan database MySQL.  Metode Certainty Factor dapat menentukan tingkat keyakinan terhadap hasil diagnosis berdasarkan gejala yang dipilih pengguna dan nilai bobot dari pakar. Sistem ini dirancang menggunakan PHP sebagai bahasa pemrograman dan MySQL sebagai media penyimpanan data gejala, penyakit, aturan, serta nilai kepastian. Pengguna dapat melakukan konsultasi dengan memilih gejala yang dialami, kemudian sistem akan memproses data menggunakan perhitungan Certainty Factor untuk menghasilkan diagnosis penyakit karies beserta persentase tingkat keyakinannya. Hasil penelitian menunjukkan bahwa sistem pakar yang dibangun mampu membantu pengguna dalam melakukan diagnosis awal penyakit karies secara cepat, mudah, dan efisien. Selain itu, sistem dapat memberikan informasi mengenai jenis penyakit karies dan solusi penanganan awal sesuai hasil diagnosis. Dengan adanya sistem ini, masyarakat dapat lebih mudah memperoleh informasi kesehatan gigi serta meningkatkan kesadaran terhadap pentingnya menjaga kesehatan gigi dan mulut
Implementasi Algoritma Naive Bayes Untuk Klasifikasi Data Berbasis Pendekatan Probabilistik Matematis Jhoanne Fredricka; Nofi Qurniati; Desi Mahdalena
Journal of Informatics and Electronics Engineering Vol. 6 No. 01 (2026): Juni 2026
Publisher : Unit Penelitian dan Pengabdian kepada Masyarakat Politeknik TEDC Bandung Jl. Pesantren Km 2 Cibabat Cimahi Utara – Cimahi 40513 Jawa Barat – Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70428/jiee.v6i01.1601

Abstract

Perkembangan teknologi informasi menyebabkan peningkatan volume data yang sangat besar sehingga dibutuhkan metode klasifikasi yang mampu menghasilkan informasi secara cepat dan akurat. Penelitian ini bertujuan untuk mengimplementasikan algoritma Naive Bayes dalam proses klasifikasi data berbasis pendekatan probabilistik matematis. Metode penelitian menggunakan pendekatan kuantitatif eksperimental dengan tahapan pengumpulan dataset, preprocessing data, pembagian data training dan testing menggunakan rasio 80:20, implementasi algoritma menggunakan Python pada Google Colab, dan evaluasi model menggunakan confusion matrix, accuracy, precision, dan recall. Dataset terdiri dari atribut usia, pendapatan, status mahasiswa, dan keputusan pembelian. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes menghasilkan nilai accuracy sebesar 85%, precision sebesar 90,9%, dan recall sebesar 83,3%. Pendekatan matematis diterapkan melalui perhitungan probabilitas posterior berdasarkan Teorema Bayes untuk melakukan penentuan kelas data. Dengan demikian, algoritma Naive Bayes terbukti efektif dalam meningkatkan performa klasifikasi data dan mendukung pengambilan keputusan secara lebih akurat dan efisien.
Co-Authors Ahmad Syukron Ali Aji Sukmo Alianse, Rizka Tri Andre Pranat Andre pranata Anisyah Juniarti Annisa Putri Pratiwi Asnawati Asnawati Aziz Ali Mahendra Castaka Agus Sugianto Chindy Asher Darojatul Kubroh David Tri Julian Deddy Pertan Sagala Deko Aribowo Desi Mahdalena Desi Mahdalena Devi Risianti Devina Ninosari Dewi Suranti Dini Rohmayani Feri Hari Utami Feri Hari Utami, Feri Hari Fezi Fadwa Rendika Herlina Latipa Sari Hermawansa I Putu Yogi Saputra Indah kartika Juju Jumadi Jusuf Wahyudi Kanedi, Indra Kanedi Kristiyo Indriadi Wardoyo Lena Elfianty Leni Natalia Zulita Lindry Dwi Cahyani Liza Yulianti M Zuhri M. Ajis Akbar Kurniawan Maryanigsih, Maryanigsih Maryaningsih Maryaningsih Maryaningsih Maryaningsih Masterjon Masterjon Mendalia Hasanah Migi Migi Mohamed Doheir Muhammad Hafist Khalaf Nofi Qurniati Nofi Qurniati Novita Sari Perlius Septria Reno Supardi Reza Ardiansyah Rinaldi Rinaldi Riska Eka Aprianty Rizka Tri Alinse Roni Ardiwan Sallaby, Achmad Fikri Sapri Sapri Sari, Novita Siswanto Siswanto Siswanto Siswanto, Siswanto, Surya Ramadhan Toibah Umi Kalsum Venny Novita Sari Widia Sari Yupianti, Yupianti