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All Journal International Journal of Electrical and Computer Engineering Voteteknika (Vocational Teknik Elektronika dan Informatika) Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) Dinamisia: Jurnal Pengabdian Kepada Masyarakat INTEK: Informatika dan Teknologi Informasi Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Applied Technology and Computing Science Journal Infotekmesin Indonesian Journal of Electrical Engineering and Computer Science Journal of Innovation Information Technology and Application (JINITA) Journal of Community Development Jurnal Ekonomi dan Teknik Informatika Jurnal Abdi Panca Marga Pengabdian Jurnal Abdimas Damhil: Jurnal Pengabdian kepada Masyarakat
Nur Wachid Adi Prasetya
Politeknik Negeri Cilacap
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Journal : Infotekmesin

 1 
Sistem Pakar Deteksi Dini Penyakit Preeklamsia pada Ibu Hamil Menggunakan Metode Certainty Factor Nur Wachid Adi Prasetya; Linda Perdana Wanti; Laura Sari; Lina Puspitasari
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.1050

Abstract

Preeclampsia is a disease in pregnant women characterized by high blood pressure and positive urine protein. The disease has a high risk of maternal and fetal death, so there is a need for early detection of mothers at risk of preeclampsia. Early online detection of preeclampsia is the best solution during the Covid-19 pandemic by analyzing the influencing factors. The purpose of this study is to build an expert system for early detection of preeclampsia in pregnant women using the Certainty Factor method and the waterfall system development model in order to provide the possibility of pregnant women suffering from preeclampsia. Testing the accuracy of 30 medical record data for pregnant women resulted in a system accuracy level of 90%, while usability testing resulted in a user satisfaction level of 55 with the System Usability Testing (SUS) score criteria being "Poor", therefore improvements are needed on expert system in the future.
Implementasi Profile Matching Pada Seleksi Ketua dan Wakil Ketua OSIS Alif Iftitah; Linda Perdana Wanti; Dwi Novia Prasetyanti; Nur Wachid Adi Prasetya; Andriansyah Zakaria
Infotekmesin Vol 13 No 2 (2022): Infotekmesin: Juli, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i2.1536

Abstract

The OSIS chairman is the highest leader in the OSIS management structure and is accompanied by a vice-chairman. Therefore, a selection with several criteria is needed to determine the best candidate. Things that are considered in this selection are realism, maturity, organizational experience, public speaking, discipline, character, organizational activity, and responsibility. By utilizing a decision support system, the best candidates are obtained for the candidate for chairman and vice-chairman of the student council. This system is made with the method used to assist the selection process, namely, profile matching. Profile matching is used to find the profile of a job that is sought from a predetermined specification. This method provides a solution and has a clear objective in decision-making. On the other hand, the method used to develop a decision support system is the incremental method. The selection of the incremental method is based on the fact that this method has an iterative nature, which can adapt to the many repetitions that occur during the development process. The novelty of this research is the recommendations generated from the developed decision support system. There are notifications about the results of decisions to users, in this case, the candidates for the OSIS chairman and vice chairman who are alternatives in the election process. This study resulted in recommendations in the form of candidates for OSIS chairman and vice chairman by the candidate's profile.
Indonesia Nur Wachid Adi Prasetya; Linda Perdana Wanti; Lina Puspitasari
Infotekmesin Vol 14 No 1 (2023): Infotekmesin: Januari, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i1.1635

Abstract

Preeclampsia is a disease of pregnant women, causing many complaints, including dizziness. Massage is the right solution to reduce dizziness since the use of analgesic drugs is not recommended. Submission of massage information can be more effective through digital technology. The purpose of this research is to build an application based on Augmented Reality (AR) as a guide for facial massage movements for midwives and pregnant women to deal with complaints of dizziness for pregnant women. The method used is the Multimedia Development Life Cycle (MDLC), which consists of the stages of making a concept, making a design, collecting materials, combining materials, testing, and distribution. Black box testing on 10 scenarios produces a value of 100%, which means the application can run properly. In addition, usability testing using the System Usabilities Scale (SUS) method shows a value of 69.5, which means that the application has the "good" criteria and is acceptable to users.
Comparison of The Dempster Shafer Method and Bayes' Theorem in The Detection of Inflammatory Bowel Disease Linda Perdana Wanti; Nur Wachid Adi Prasetya; Oman Somantri
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.1797

Abstract

This study discusses the comparison of the Dempster-Shafer method and Bayes' theorem in the process of early detection of inflammatory bowel disease. Inflammatory bowel disease, better known as intestinal inflammation, attacks the digestive tract in the form of irritation, chronic inflammation, and injuries to the digestive tract. Early signs of inflammatory bowel disease include excess abdominal pain, blood when passing stools, acute diarrhea, weight loss, and fatigue. The Dempster-Shafer method is a method that produces an accurate diagnosis of uncertainty caused by adding or reducing information about the symptoms of a disease. Meanwhile, Bayes' theorem explains the probability of an event based on the factors that may be related to the event. This study aims to measure the accuracy of disease detection using the Dempster-Shafer method compared to the probability of occurrence of the disease using Bayes' theorem. The results of calculating the level of accuracy show that the Bayes Theorem method is better at predicting inflammatory bowel disease with a probability of occurrence of disease in the tested data of 75.9%.
Sistem Pakar Deteksi Dini Penyakit Preeklamsia pada Ibu Hamil Menggunakan Metode Certainty Factor Adi Prasetya, Nur Wachid; Perdana Wanti, Linda; Sari, Laura; Puspitasari, Lina
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.1050

Abstract

Preeclampsia is a disease in pregnant women characterized by high blood pressure and positive urine protein. The disease has a high risk of maternal and fetal death, so there is a need for early detection of mothers at risk of preeclampsia. Early online detection of preeclampsia is the best solution during the Covid-19 pandemic by analyzing the influencing factors. The purpose of this study is to build an expert system for early detection of preeclampsia in pregnant women using the Certainty Factor method and the waterfall system development model in order to provide the possibility of pregnant women suffering from preeclampsia. Testing the accuracy of 30 medical record data for pregnant women resulted in a system accuracy level of 90%, while usability testing resulted in a user satisfaction level of 55 with the System Usability Testing (SUS) score criteria being "Poor", therefore improvements are needed on expert system in the future.
Implementasi Profile Matching Pada Seleksi Ketua dan Wakil Ketua OSIS Alif Iftitah; Linda Perdana Wanti; Dwi Novia Prasetyanti; Nur Wachid Adi Prasetya; Andriansyah Zakaria
Infotekmesin Vol 13 No 2 (2022): Infotekmesin: Juli, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i2.1536

Abstract

The OSIS chairman is the highest leader in the OSIS management structure and is accompanied by a vice-chairman. Therefore, a selection with several criteria is needed to determine the best candidate. Things that are considered in this selection are realism, maturity, organizational experience, public speaking, discipline, character, organizational activity, and responsibility. By utilizing a decision support system, the best candidates are obtained for the candidate for chairman and vice-chairman of the student council. This system is made with the method used to assist the selection process, namely, profile matching. Profile matching is used to find the profile of a job that is sought from a predetermined specification. This method provides a solution and has a clear objective in decision-making. On the other hand, the method used to develop a decision support system is the incremental method. The selection of the incremental method is based on the fact that this method has an iterative nature, which can adapt to the many repetitions that occur during the development process. The novelty of this research is the recommendations generated from the developed decision support system. There are notifications about the results of decisions to users, in this case, the candidates for the OSIS chairman and vice chairman who are alternatives in the election process. This study resulted in recommendations in the form of candidates for OSIS chairman and vice chairman by the candidate's profile.
Indonesia Prasetya, Nur Wachid Adi; Linda Perdana Wanti; Lina Puspitasari; Indonesia
Infotekmesin Vol 14 No 1 (2023): Infotekmesin: Januari, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i1.1635

Abstract

Preeclampsia is a disease of pregnant women, causing many complaints, including dizziness. Massage is the right solution to reduce dizziness since the use of analgesic drugs is not recommended. Submission of massage information can be more effective through digital technology. The purpose of this research is to build an application based on Augmented Reality (AR) as a guide for facial massage movements for midwives and pregnant women to deal with complaints of dizziness for pregnant women. The method used is the Multimedia Development Life Cycle (MDLC), which consists of the stages of making a concept, making a design, collecting materials, combining materials, testing, and distribution. Black box testing on 10 scenarios produces a value of 100%, which means the application can run properly. In addition, usability testing using the System Usabilities Scale (SUS) method shows a value of 69.5, which means that the application has the "good" criteria and is acceptable to users.
Comparison of The Dempster Shafer Method and Bayes' Theorem in The Detection of Inflammatory Bowel Disease Wanti, Linda Perdana; Adi Prasetya, Nur Wachid; Somantri, Oman
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.1797

Abstract

This study discusses the comparison of the Dempster-Shafer method and Bayes' theorem in the process of early detection of inflammatory bowel disease. Inflammatory bowel disease, better known as intestinal inflammation, attacks the digestive tract in the form of irritation, chronic inflammation, and injuries to the digestive tract. Early signs of inflammatory bowel disease include excess abdominal pain, blood when passing stools, acute diarrhea, weight loss, and fatigue. The Dempster-Shafer method is a method that produces an accurate diagnosis of uncertainty caused by adding or reducing information about the symptoms of a disease. Meanwhile, Bayes' theorem explains the probability of an event based on the factors that may be related to the event. This study aims to measure the accuracy of disease detection using the Dempster-Shafer method compared to the probability of occurrence of the disease using Bayes' theorem. The results of calculating the level of accuracy show that the Bayes Theorem method is better at predicting inflammatory bowel disease with a probability of occurrence of disease in the tested data of 75.9%.
Evaluasi Kinerja Model Machine Learning dalam Klasifikasi Penyakit THT: Studi Komparatif Naïve Bayes, SVM, dan Random Forest Prasetya, Nur Wachid Adi; Wanti, Linda Perdana; Purwanto, Riyadi; Bahroni, Isa; Listyaningrum, Rostika
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2798

Abstract

Classification of Ear, Nose, and Throat (ENT) diseases is essential to support faster and more accurate diagnosis. However, no prior studies have specifically compared the performance of Naïve Bayes, Support Vector Machine (SVM), and Random Forest algorithms in ENT cases. This study aims to evaluate and compare the three classification models in identifying ENT diseases with or without comorbidities. Medical record data were processed through preprocessing, feature selection using ANOVA, and class balancing with SMOTE. The results showed that SVM outperformed the other models with the highest accuracy (59%), followed by Random Forest (57%), and Naïve Bayes (48%). SVM demonstrated superior performance due to its consistent scores across all evaluation metrics. The study concludes that the choice of classification model significantly impacts the accuracy of ENT disease diagnosis.
Co-Authors Aditya Saputra, Muhammad Bintang Agus Susanto Alif Iftitah Alif Iftitah Andesita Prihantara Andriansyah Zakaria Andriansyah Zakaria Annas Setiawan Prabowo Annisa Romadloni Awaludin, Ihza Dwi Krisbiantoro, Dwi Dwi Kumara, Dimas Maulana Dwi Novia Prasetyanti Dwi Novia Prasetyanti Eka Tripustikasari Fadillah Fadillah Furi, Syamaidzar Nadifa Ganjar Ndaru Ikhtiagung Girawan, Bayu Aji Hastuti, Hety Dwi Hijriah Fajar Muhammad Insan Ike Yunia Pasa Ikhtiagung, Ganjar Ndaru Ilham Aditya Pangestu Indonesia Isa Bahroni, Isa Jati, Unggul Satria Johanna, Anne Kristiningsih, Ari Laura Sari Lina Puspitasari Linda Perdana Wanti Linda Perdana Wanti Listyaningrum, Rostika Muhammad Nur Faiz Muhammad Ramadani Nafisa, Zahrun Nur Akhlis Sarihidaya Laksana, Nur Akhlis Sarihidaya Nur Wahyu Rahadi Oman Somantri Perdana Wanti, Linda Prih Diantono Abda`u Purwaningrum, Santi Puspitasari, Lina Radhi Ariawan Rahmat Hidayat Rahmat Mulyadi Ramadani, Muhammad Ratih Hafsarah Maharrani Riyadi Purwanto Roy Aries Permana Tarigan Santi Purwaningrum Sari, Laura Sarihidaya Laksana, Nur Akhlis Sarihidaya, Nur Akhlis Sri Kusumadewi Wanti, Linda Perdana Wittriansyah, Khoeruddin Wittriansyah, Khoerudin Zahrun Nafisa