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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) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 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 Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi 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 Damhil: Jurnal Pengabdian kepada Masyarakat Pengabdian: Jurnal Abdimas
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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Analisis Perbandingan Metode SAW, WP, dan TOPSIS Untuk Optimasi Sistem Pendukung Keputusan Proses Seleksi Beasiswa Lazizmu Ike Yunia Pasa; Nur Wachid Adi Prasetya; Ratih Hafsarah Maharrani
INTEK : Jurnal Informatika dan Teknologi Informasi Vol. 6 No. 1 (2023)
Publisher : Universitas Muhammadiyah Purworejo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37729/intek.v6i1.3147

Abstract

Sistem pendukung keputusan seleksi beasiswa yang berjalan saat ini di Universitas Muhammadiyah Purworejo (UMP)menerapkan metode Simple Additive Weighting (SAW). Berdasarkan pengujian sistem, tingkat akurasi sistem sebesar 80%. Hasil ini dirasa kurang efisien, sehingga perlu ditingkatkan, agar hasil keputusan pemilihan seleksi beasiswa Lazizmu lebih optimal. Tujuan penelitian ini yaitu membandingkan beberapa metode, antara lain Simple Additive Weighting (SAW), Weighted Product (WP), dan Technique For Others Reference by Similarity to Ideal Solution (TOPSIS), untuk menentukan metode yang paling relevan dari tiga metode tersebut, melalui pengujian sensitivitas. Hasil pengujian sensitivitas terhadap 3 metode tersebut menunjukkan nilai sensitivitas dari metode SAW adalah -0,009 %, metode WP adalah 0,003 %, dan metode TOPSIS adalah 0,085 %. Sehingga, metode TOPSIS merupakan metode yang paling optimal untuk diterapkan pada sistem pendukung keputusan seleksi beasiswa Lazizmu di Universitas Muhammadiyah Purworejo (UMP), karena tingkat sensitivitasnya yang lebih tinggi dari metode lainnya.
Pelatihan SIPAKPRIH untuk Deteksi Dini Preeklamsia sebagai Dukungan Peningkatan Kinerja IBI Kabupaten Cilacap Linda Perdana Wanti; Nur Wachid Adi Prasetya; Lina Puspitasari; Laura Sari; Annisa Romadloni
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 3 (2023): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v7i3.11586

Abstract

IBI (Indonesian Midwives Association) Cilacap Regency is a forum for the association of midwife medical personnel in the Cilacap Regency. The performance of midwives can be continuously improved through training that supports all health service activities in the community. One of them is training in the use of information systems to detect the presence of preeclampsia in pregnant women (SIPAKPRIH) from the first to the third trimester by selecting the causative factors experienced by pregnant women. Midwives can take advantage of the expert system to support the performance of midwives in terms of health services for the community, especially pregnant women and the babies/fetus they contain. The solution proposed through this PkM activity is to improve the performance of midwives, especially midwives in Cilacap Regency in supporting health service activities to the community that are useful for monitoring the health of mothers and babies during pregnancy. The output target of this PkM activity is to increase the skills and knowledge of midwives for monitoring the health of pregnant women who are detected with preeclampsia through optimizing SIPAKPRIH.
Expert System for Diagnosing Inflammatory Bowel Disease Using Certainty Factor and Forward Chaining Methods Linda Perdana Wanti; Nur Wachid Adi Prasetya; Oman Somantri
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 2 (2023): JINITA, December 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i2.2096

Abstract

Identification of inflammatory bowel disease quickly and accurately is motivated by the large number of patients who come with pain in the abdomen and receive minimal treatment because they are considered to be just ordinary abdominal pain. This study aims to identify inflammatory bowel disease which is still considered by some people as a common stomach ache quickly, and precisely and to recommend therapy that can be done as an initial treatment before getting medical action by medical personnel. The method used in this expert system research is a combination of forward chaining and certainty factors. The forward chaining method traces the disease forward starting from a set of facts adjusted to a hypothesis that leads to conclusions, while the certainty factor method is used to confirm a hypothesis by measuring the amount of trust in concluding the process of detecting inflammatory bowel disease. The results of this study are a conclusion from the process of identifying inflammatory bowel disease which begins with selecting the symptoms experienced by the patient so that the diagnosis results appear using forward chaining and certainty factor in the form of a percentage along with therapy that can be given to the patient to reduce pain in the abdomen. A comparison of the diagnosis results using the system and diagnosis by experts, in this case, specialist doctors, shows an accuracy rate of 82,18%, which means that the expert system diagnosis results can be accounted for and follow the expert diagnosis.
Fuzzy expert system design for detecting stunting Linda Perdana Wanti; Oman Somantri; Nur Wachid Adi Prasetya; Lina Puspitasari
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp556-564

Abstract

Stunting is a chronic nutritional problem that occurs in toddler due to lack of nutritional intake which results in impaired growth toddler. Usually, toddler who experience stunting are characterized by not increasing weight over a long period of time. Application utilization health which makes it easier for users to access information, one of which can be used to identify toddler who are stunted by selecting symptoms. The symptoms experienced by toddlers go through a system known as the system expert. In this research an expert system will be developed that is capable of early detection developmental disorders in toddlers using the Mamdani fuzzy method. The results obtained from this research are an expert system design for early detection of stunting using the Mamdani fuzzy method. The Mamdani fuzzy method was implemented to group the criteria for toddlers who fall into the stunting category or not from the initial data which is still gray because they are still unsure whether to categorize the toddler as having stunting or not. The detection accuracy rate using the Mamdani fuzzy method is 80.87% compared to expert diagnosis.
Combination certainty factor method and fuzzy expert system module to determine the dose of leukemia drugs Krisbiantoro, Dwi; Wanti, Linda Perdana; Adi Prasetya, Nur Wachid
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i3.pp1915-1923

Abstract

Leukemia is a type of blood cancer. Treatment for leukemia patients can last for years because the dose of medication given is adjusted to the patient's immune system. The aim of this research is the use of information technology through a combination of certainty factors and the development of a fuzzy expert system (FES) module to determine the therapeutic schedule for administering leukemia drugs. The urgency of this research is to help medical personnel in measuring the dose of leukemia medication to be given to patients so as to increase the cure rate for leukemia patients. The method used is certainty factor and fuzzy logic. The combination of the certainty factor method and the FES module which is carried out using input variables in the form of the severity of the leukemia suffered by the patient is to produce an appropriate therapeutic schedule for administering leukemia drugs. The result of this research is a combination of the factor certainty method and the FES module which has been tested and the accuracy level is 95.17%, the same as recommendations from experts.
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%.
Application of data mining for diagnosis of ENT diseases using the Naïve Bayes method with genetic algorithm feature selection Wanti, Linda Perdana; Adi Prasetya, Nur Wachid; Awaludin, Ihza; Aditya Saputra, Muhammad Bintang; Furi, Syamaidzar Nadifa; Dwi Kumara, Dimas Maulana
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp398-405

Abstract

Ear, nose, and throat (ENT) disease is a disorder that occurs in the eustachian tube in one of the organs, be it the ear, nose, or throat. Early signs of ENT disease include sore throat, painful swallowing, swollen and red tonsils, runny nose, nosebleeds, blocked nose, discharge from the ears, and others. To determine the diagnosis, it is necessary to carry out a physical examination of the ears, nose, and throat as recommended by an expert, namely an ENT doctor. The research carried out was implementing data mining for the diagnosis of ENT diseases using the Naïve Bayes (NB) method. This method was chosen because it can increase the accuracy, efficiency, and accessibility of health services and is also easy to understand and apply to classify ENT disease symptom data. The NB method was used to build an ENT diagnosis classification model and the model performance was evaluated using accuracy, precision, and recall metrics. To increase the accuracy of the NB algorithm predictions, feature selection using a genetic algorithm can be used. Genetic algorithms can help select the most relevant and significant features, improving the accuracy of NB models by eliminating irrelevant or noisy features. By applying this method, predictions for ENT diseases can be produced with an accuracy of 95.67%.
Pelatihan Pengelolaan dan Pemilahan Sampah Pada BUMDes Banjarwaru Sejahtera Untuk Menunjang Kemandirian Masyarakat Desa Banjarwaru Wanti, Linda Perdana; Ariawan, Radhi; Prasetya, Nur Wachid Adi
Damhil: Jurnal Pengabdian kepada Masyarakat Vol 3, No 2: December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/damhil.v3i2.28153

Abstract

The Community Service (PKM) activity carried out in Banjarwaru Village aims to empower the community through structured and effective waste management. The partner in this program, namely BUMDes "Banjarwaru Sejahtera," is at the forefront of efforts to realize village economic independence by utilizing waste as one of the economic resources. This activity was initiated with the background of problems faced by the community, especially the low awareness of waste management which results in the accumulation of waste in the surrounding environment which has a negative impact on health and environmental aesthetics. Another problem found is the lack of facilities and infrastructure for waste management. To overcome this, the PKM program that is being run carries various solutions designed according to the needs and potential in Banjarwaru Village. The solutions implemented in this program include education and counseling to increase public awareness of the importance of waste management. This educational activity is carried out through counseling and campaigns that directly involve the village community. The PKM team of Cilacap State Polytechnic also provided additional trash bins at strategic points so that people can easily dispose of trash according to its type. With the implementation of these solutions, the main target to be achieved is to increase public awareness of the importance of waste management and the formation of a more structured waste management system. Through education and provision of facilities, it is hoped that the community can consistently separate waste and actively participate in maintaining the cleanliness of the village environment.
Perbandingan Metode Pembobotan Teks dari Algoritma Winnowing dan TF-IDF dikombinasikan Algoritma Cosine Similarity Santi Purwaningrum; Oman Somantri; Nur Wachid Adi Prasetya
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 12, No 4 (2024): Vol. 12, No 4, Desember 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v12i4.130627

Abstract

Tugas akhir di perguruan tinggi adalah syarat kelulusan untuk mendapatkan gelar sarjana atau ahli madya. Tingginya keinginan mahasiswa untuk segera lulus terkadang membuat mahasiswa melakukan tindakan plagiarisme. Plagiarisme adalah tindakan meniru dan mengutip bahkan menyalin atau mengakui hasil karya orang lain sebagai hasil karya dirinya sendiri. Penelitian ini bertujuan untuk mengembangkan sistem yang mendeteksi kesamaan antar dokumen teks berbahasa Indonesia dengan membandingkan dua metode pembobotan teks. Algoritma Winnowing dan TF-IDF adalah metode pembobotan teks yang dikombinasikan dengan metode Cosine Similarity. Cosine Similarity merupakan algoritma yang berfungsi untuk mencari nilai kesamaan antar dokumen dari hasil pembobotan algoritma winnowing dan TF-IDF. Hasil penelitian menunjukkan bahwa algoritma Winnowing memiliki nilai kesamaan rata-rata 66%, lebih tinggi dibandingkan TF-IDF yang hanya memiliki rata-rata 57%. Performa algoritma diukur menggunakan akurasi dan RMSE. Nilai akurasi pada algoritma Winnowing adalah 90.47% dan algoritma TF-IDF 81.84%. Nilai RMSE pada algoritma Winnowing sebesar 5,44 dan TF-IDF sebesar 5,34.Kata kunci : Winnowing, TF-IDF, Cosine Similarity.The final project at a higher education institution is a graduation requirement to obtain a bachelor's or associate degree. The strong desire of students to graduate quickly sometimes leads them to commit plagiarism. Plagiarism is the act of imitating, quoting, or even copying or acknowledging someone else's work as their own. This research aims to develop a system that detects similarities between Indonesian text documents by comparing two text weighting methods. The Winnowing and TF-IDF algorithms are text weighting methods combined with the cosine similarity method. Cosine similarity is an algorithm used to find the similarity value between documents based on the weighting results of the Winnowing and TF-IDF algorithms. The results of the study showed that the Winnowing algorithm had an average similarity value of 66%, higher than TF-IDF which only had an average of 57%. The performance of the algorithm uses measurements and RMSE. The algorithm's performance was measured using accuracy and RMSE. The accuracy value of the winnowing algorithm is 90.47% and the TF-IDF algorithm is 81.84%. The RMSE value of the Winnowing algorithm is 5.44 and TF-IDF is 5.34.Keywords: Winnowing, TF-IDF, Cosine Similarity. 
Sistem Pakar Fuzzy Modular untuk Identifikasi Dosis Obat Leukemia Wanti, Linda Perdana; Prasetya, Nur Wachid Adi; Nafisa, Zahrun; Ramadani, Muhammad; Hidayat, Rahmat
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 2: April 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025129545

Abstract

Diagnosis dan pengambilan keputusan tentang penyakit dalam bidang medis menghadapi ketidakpastian yang dapat memengaruhi proses pengobatan. Keputusan ini dibuat berdasarkan pengetahuan pakar dan cara seorang pakar dalam mendefinisikan kondisi pasien, gejala yang dialami dan faktor-faktor lain yang memengaruhi. Hasil definisi setiap pakar mungkin saja terdapat perbedaan berdasarkan faktor-faktor tersebut. Fuzzy modular expert system adalah suatu sistem berbasis pengetahuan yang memanfaatkan logika fuzzy untuk menangani ketidakpastian dan modularitas dalam pengambilan keputusan. Dalam sistem dengan ketidakpastian tinggi dan kompleksitas tinggi, logika fuzzy merupakan metode yang cocok untuk pemodelan. Dalam penelitian ini, fuzzy modular expert system untuk pemodelan ketidakpastian dalam pemberian dosis obat untuk terapi penyakit leukemia.  Variabel output yang digunakan pada penelitian ini adalah tingkat toksisitas yang dihasilkan dari proses pemberian dosis obat yang dibagi menjadi lima kategori yaitu sangat rendah, rendah, sedang, tinggi dan sangat tinggi. Variabel output yang kedua adalah kategori stadium leukemia yang diderita oleh pasien yang dibagi menjadi empat kategori yaitu stadium 1, stadium 2, stadium 3 dan stadium 4. Penelitian ini menggunakan 128 data latih pasien dengan dua variabel output. Hasil yang diperoleh menunjukkan bahwa fuzzy modular expert system dalam mengindentifikasi dosis obat yang diberikan sebagai terapi obat leukemia dengan akurasi rata-rata sekitar 94,8% berdasarkan data yang telah diuji dan dibandingkan dengan informasi dari pakar.   Abstract Diagnosis and decision-making about diseases in the medical field face uncertainties that can affect the treatment process. These decisions are based on expert knowledge and how an expert defines the patient's condition, symptoms experienced, and other influencing factors. The results of each expert's definition may differ based on these factors. A fuzzy modular expert system is a knowledge-based system that utilizes fuzzy logic to handle uncertainty and modularity in decision-making. In systems with high uncertainty and high complexity, fuzzy logic is a suitable method for modeling. In this study, a fuzzy modular expert system for modeling uncertainty in leukemia diagnosis. The output variables used in this study are the level of toxicity resulting from the drug dosing process which is divided into five categories, namely shallow, low, medium, high, and very high. The second output variable is the category of leukemia stage suffered by the patient which is divided into four categories, namely stage 1, stage 2, stage 3, and stage 4. This study used 128 patient training data with 2 output variable. The results indicate that the fuzzy modular expert system can diagnose leukemia with an average accuracy of around 94.8% based on data that has been tested and compared with expert diagnoses.
Co-Authors Aditya Saputra, Muhammad Bintang Agus Susanto Akmal Fauzan Ananta Alif Iftitah Alif Iftitah Andesita Prihantara Andriansyah Zakaria Andriansyah Zakaria Annas Setiawan Prabowo Anne Johanna Annisa Romadloni Awaludin, Ihza Bayu Aji Girawan Dwi Krisbiantoro, Dwi Dwi Kumara, Dimas Maulana Dwi Novia Prasetyanti Dwi Novia Prasetyanti Eka Tripustikasari Erlangga Widhi Pramono 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 Muhammad Nur Faiz Muhammad Ramadani Nafisa, Zahrun Nur Akhlis Sarihidaya Laksana 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 Rostika Listyaningrum Roy Aries Permana Tarigan Santi Purwaningrum Sari, Laura Sarihidaya Laksana, Nur Akhlis Sarihidaya, Nur Akhlis Sri Kusumadewi Unggul Satria Jati Wanti, Linda Perdana Wittriansyah, Khoeruddin Wittriansyah, Khoerudin Zahrun Nafisa