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Gastric disease is a common health problem that can disrupt daily activities if not properly treated. To aid the initial diagnosis process, this study developed a web-based expert system capable of diagnosing various types of gastric disease based on the symptoms experienced by the user. This system uses the Dempster-Shafer method to address uncertainty in decision-making by combining a number of pieces of evidence in the form of symptoms to determine the level of confidence in a disease. The system was developed using the PHP programming language and a MySQL database and designed for easy browser access. Testing demonstrated that the system was able to provide fairly accurate diagnostic results that closely approximated the results of consultations with medical professionals. This system is expected to become an initial solution for the public in quickly and independently recognizing symptoms of gastric disease.

Film and television play a central role in shaping and representing the cultural identity of society. Through artistic expertise manifested by directors, screenwriters, actors, cinematographers, and producers, cultural construction is presented not only as entertainment but also as a social discourse that reflects values, traditions, and the dynamics of collective identity. This study aims to analyze how artistic expertise contributes to constructing cultural identity representation through film and television mediums in Indonesia. The research methodology used is qualitative, employing content analysis and semiotics approaches on selected Indonesian films and TV series that highlight cultural aspects, such as Losmen Bu Broto and Gadis Kretek. These works were chosen because they feature rich local culture while reflecting the role of culture in the dynamics of Indonesian society. The findings indicate that artistic expertise plays a crucial role in constructing cultural representation, both through narrative, visual elements, music, and actors' performances. The representations produced not only affirm local and national identities but also reflect the process of cultural negotiation with global influences. This study underscores that film and television serve as strategic media for cultural diplomacy and the formation of collective identity awareness in Indonesian society. Through this process, these mediums contribute to the preservation of local culture amidst global cultural flows. The research highlights the importance of film and television as tools for maintaining and constructing cultural identity, where local traditions and values are both preserved and adapted to the changing global landscape.   

This study aims to design and develop an expert system to assist in diagnosing diseases in dairy cattle at Cibugary Farm using the Forward Chaining method. The background of this research lies in the limited knowledge of farmers in identifying early symptoms of diseases, which often leads to delays in medical treatment and negatively affects dairy cattle productivity. To address this issue, an expert system was designed to replicate the reasoning process of a human expert through a knowledge base containing diagnostic rules derived from observable symptoms. The Forward Chaining method was chosen because of its capability to trace facts from known symptoms toward a conclusion regarding the type of disease affecting the cattle. The system was developed by incorporating common disease symptoms, inference rules, and a decision-making mechanism that simulates expert analysis. Testing was carried out on several diagnostic scenarios to evaluate the accuracy and efficiency of the system. The results of the study indicate that the expert system can provide an initial diagnosis quickly and accurately, producing outputs consistent with expert assessments. This functionality assists farmers in making timely decisions regarding appropriate medical interventions, thereby reducing treatment delays and minimizing the risk of disease transmission within the herd. Consequently, the Forward Chaining-based expert system is expected to serve as an innovative solution to improve dairy cattle health management and support sustainable livestock productivity at Cibugary Farm.

Typhoid fever is a significant health issue caused by the Salmonella Typhi bacteria, leading to symptoms such as fever, abdominal pain, diarrhea, muscle pain, and serious complications if not treated promptly. A common challenge faced by society is limited access to medical professionals, especially in remote areas, and delays in recognizing symptoms. To address this problem, this study designs and implements a web-based expert system using the Certainty Factor (CF) method, which helps diagnose typhoid fever quickly and accurately. The Certainty Factor method is used to calculate the certainty level of the symptoms experienced by the patient, providing a diagnosis result in the form of early-stage typhoid, mild typhoid, or severe typhoid. The system was developed using PHP programming language and MySQL database, and tested at RSUD Djoelham Binjai City. The research data was obtained from patients at RSUD Djoelham Binjai with a case study on patient number 22. The processing of symptoms through Certainty Factor calculation showed that the patient is most likely to have severe typhoid with a certainty value of 0.9443 or 94.43%. This result proves that the Certainty Factor method can be used to assist in providing an accurate early diagnosis of typhoid fever with a high degree of accuracy.

Pemerintah daerah memiliki kewenangan pengelolaan Anggaran Pendapatan dan Belanja Daerah (APBD) untuk menyediakan dan melakukan pemeliharaan infrastruktur fisik yang digunakan oleh Masyarakat, sehingga diperlukan perencanaan yang komprehensif untuk Pembangunan dan pemeliharaan infrastruktur fisik agar tepat sasaran dan memiliki kemaslahatan bagi Masyarakat. Pembangunan infrastruktur yang berhasil akan berdampak pada masyarakat untuk memiliki akses dalam melaksanakan berbagai kegiatan yang berhubungan dengan peningkatan taraf hidup. Penelitian ini bertujuan untuk mengevaluasi biaya pemeliharaan infrastruktur jalan di Kota bogor berbasis faktor yang dianggap signifikan mempengaruhi sekaligus memberikan rekomendasi biaya pemeliharaan yang optimal untuk jalan raya di Kota Bogor, Jawa Barat. Penelitian ini dilakukan melalui metode kuantitatif dan kualitatif (mix method), metode kuantitatif dilakukan dengan menganalisa 30 ruas jalan yang telah dilaksanakan untuk menentukan faktor yang dianggap mempengaruhi dan dominan dalam pemeliharaan jalan. Penelitian kualitatif akan dilakukan melalui interview mendalam (in-depth interview) kepada pakar untuk memvalidasi hasil penelitian kuantitatif yang dihasilkan sehingga dapat menjadi rekomendasi pemeliharaan jalan raya di Kota Bogor, Jawa Barat. Hasil dari penelitian ini adalah hasil evaluasi pemeliharaan jalan beserta faktor yang dianggap mempengaruhi dalam pemeliharaan jalan.  Penelitian ini akan memberikan manfaat  baru dalam mengembangkan knowledge bidang pemeliharaan infrastruktur jalan raya bagi pemerintah daerah, akademisi, kontraktor dan Masyarakat dalam pemeliharaan infrastruktur jalan raya di Kota Bogor, Jawa Barat dan daerah lain untuk dievaluasi dan dikembangkan faktornya agar pekerjaan pemeliharaan jalan di daerah menjadi optimal di masa yang akan datang.

Persaingan yang semakin kompetitif dalam industri wedang uwuh di Imogiri mendorong UMKM Taruna Agro Nusantara untuk berinovasi melalui produk wedang uwuh siap saji dalam kemasan paper cup yang diharapkan dapat meningkatkan daya saing. Penelitian ini bertujuan untuk mengetahui preferensi konsumen terhadap atribut kemasan wedang uwuh. Metode penelitian yang digunakan adalah mixed method. Pendekatan kualitatif dilakukan melalui diskusi dengan pemilik UMKM dan pakar desain untuk merumuskan atribut kemasan. Selanjutnya, pendekatan kuantitatif dilakukan melalui analisis konjoin untuk mengetahui kombinasi atribut yang paling disukai konsumen. Atribut kemasan yang dipilih yaitu slogan, warna, informasi produk, dan ukuran kemasan yang kemudian ditentukan level atributnya. Dari 9 level atribut menghasilkan 54 stimuli yang kemudian direduksi menjadi 9 stimuli menggunakan  orthogonal array. Data yang diperoleh menunjukkan bahwa Persentase tingkat penerimaan responden terhadap stimuli tertinggi yaitu pada stimuli 4 sebesar 78%  kategori tinggi dengan kombinasi slogan “manfaat terasa, tradisi terjaga”, berwarna merah, menggunakan Bahasa Indonesia dan Bahasa Inggris, serta berukuran 240 ml. Nilai kepentingan tertinggi terdapat pada atribut ukuran dengan nilai 47,147. Nilai kegunaan tertinggi untuk atribut slogan adalah “kehangatan dalam tiap genggaman”, atribut warna terdapat pada warna merah, atribut informasi terdapat pada informasi yang menggunakan bahasa Indonesia dan Inggris, sedangkan nilai kegunaan tertinggi dalam atribut ukuran yaitu pada ukuran 240 ml. Penelitian ini diharapkan dapat menjadi dasar pengembangan produk wedang uwuh siap saji yang lebih inovatif dan sesuai dengan selera pasar.

Hypertension is a common disease in society and can lead to serious complications if not properly managed. This study aims to design a web-based expert system to assist in diagnosing hypertension using the Certainty Factor and Dempster Shafer methods. The Certainty Factor method is used to measure the confidence level of reported symptoms, while the Dempster Shafer method combines information from various sources to generate more accurate decisions. The system is designed with a user-friendly interface to facilitate access for medical personnel and patients. The research results show that the Certainty Factor method achieved an accuracy 97,9%, while the Dempster Shafer method reache 96,4%. The accuracy difference of 1,4% indicates that the Certainty Factor method is more effective in handling the uncertainty of hypertension symptoms than the Dempster Shafer method.

An expert system is a computer program designed to imitate the decision-making ability of an expert in a particular field, combining knowledge and rules obtained from experts to diagnose problems, provide advice, or make complex decisions, especially in dental diseases, so this requires the design of an expert system application for website-based dental disease diagnosis with a UML model for users who support the diagnostic process using the certainty factor method, in terms of the explanation of the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated with the formula in CF, the final result is the creation of a website-based dental disease diagnosis expert system.

An expert system is a computer program designed to imitate the decision-making ability of an expert in a particular field, especially in printer damage, so this requires an expert system application to diagnose printer damage to users who support it by obtaining diagnostic results using the certainty factor method, in terms of the explanation of the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated using the formula on the certainty factor, the final result is the creation of an expert system for diagnosing printer damage using the website-based certainty factor method.

Handling natural disaster victims requires a fast, precise, and fair aid distribution process. In this context, expert systems can be utilized as a decision-making tool in determining the type and amount of aid that should be given to victims. This article develops a desktop-based expert system using the Java programming language, which is able to calculate the type of aid based on the condition of the victim, the level of damage, and the number of affected family members. The method used is a rule-based expert system with if-then logic. The results show that this system can assist field officers in accelerating the calculation and distribution of aid.

Indonesian people mostly tend to ignore health, especially dengue fever because the symptoms that arise are similar to common fever, this causes people with common fever symptoms to be reluctant to see a doctor. This study aims to help the public recognize the symptoms of dengue fever early by using the implementation of the fuzzy method in the dengue fever disease diagnosis system that uses specific datasets as a reference. Mamdani's fuzzy method, which is based on linguistic frameworks and fuzzy concepts, allows for the management of knowledge from experts for intuitive decision-making. The test results using the Confusion Matrix, the system showed an accuracy of 92.8%, an average precision of 90.6%, a recall of 95.8%, and an F1-Score of 92.6%, with an effectiveness value of 100%. This study proves that the system is able to provide information about dengue fever, diagnose based on symptoms, and offer solutions for its treatment.

An expert system for diagnosing diseases in tilapia is one solution to help fish farmers detect and treat diseases that attack tilapia. In this study, an expert system was developed using the VCIRS (Voting Classifier for Integrated Rule Set) method to diagnose tilapia diseases based on the symptoms shown. The VCIRS method was chosen because of its ability to combine several classifiers to improve diagnostic accuracy. This system allows users, especially fish farmers, to enter symptoms observed in tilapia and obtain a diagnosis of possible diseases and appropriate treatment recommendations. The evaluation results showed that this system has a good level of accuracy in diagnosing tilapia diseases, by providing fast and accurate results, and making it easier for fish farmers to make decisions related to fish health. This expert system is expected to increase the productivity of tilapia cultivation by reducing the mortality rate of fish due to diseases that are not detected quickly.  

Chilli farming is an important sector in Ende District, but plant disease problems are often an obstacle that hampers productivity. Farmers often have difficulty recognizing the symptoms of disease in chili plants and determining appropriate treatment steps. To overcome this problem, this research aims to design and build a web-based expert system that can help diagnose chili plant diseases using the Forward Chaining method. This expert system was developed by collecting knowledge from agricultural experts and literature related to chili plant diseases, as well as applying the Forward Chaining method for the reasoning process. Users, especially farmers, can enter the symptoms experienced by chili plants into the system, then the system will produce a disease diagnosis and appropriate treatment recommendations based on these symptoms. This research uses a case study at Maju Tani Agriculture in Ende District to ensure that the expert system developed is relevant to local conditions. This system is implemented in the form of a web-based application so that it can be accessed easily by farmers using devices connected to the internet. The test results show that this expert system can provide accurate and efficient diagnoses, as well as assist farmers in making decisions to overcome chili plant disease problems. It is hoped that this system can increase agricultural productivity and reduce the risk of losses due to plant diseases.

This research aims to develop an expert system that can diagnose diseases related to brain tumors using the Case Based Reasoning (CBR) method. The CBR method works by comparing new cases with previous cases that have been stored in the database to provide appropriate diagnoses and treatment recommendations. This system is designed to assist medical personnel in analyzing patient symptoms, thus speeding up the process of identifying the type of brain tumor. In addition, the system is also equipped with a knowledge base obtained from real cases that have been validated by medical experts. Test results show that the diagnostic accuracy of this system reaches a fairly high level, especially in detecting frequently encountered types of brain tumors. Thus, this system has the potential to be an effective tool in the medical diagnosis process, especially in patients who show symptoms of brain tumors.

Autoimmune diseases, which are disorders where the immune system attacks the body’s own tissues, can affect anyone, including children and adults. These diseases often lead to serious tissue damage and physiological disturbances. Al Fuadi Binjai General Hospital, the primary healthcare facility in Binjai City, faces challenges in diagnosing autoimmune diseases in a timely manner due to limitations in time, cost, and distance. Delays in treatment can exacerbate patient conditions and slow recovery processes. The objective of this study is to develop a system that processes symptom and autoimmune disease data using the Dempster-Shafer method, which allows for uncertainty assessment in decision-making. Patient symptom data collected and analyzed using this method aims to determine the likelihood of autoimmune diseases. The developed system demonstrated high diagnostic accuracy, with the most accurate results for lupus with a confidence level of 94.40%. This result indicates that the Dempster-Shafer method can be an effective tool in accelerating the diagnostic process and improving the accuracy of autoimmune disease management at Al Fuadi Binjai General Hospital    

Nasal hypertrophy is a swelling that occurs in the nasal concha. This condition is caused because the inferior concha has a larger anatomical size when compared to the other concha structures. The process of diagnosing nasal hypertrophy often requires high clinical skills and experience. RSU Putri Bidadari is one of the hospitals that treats Nasal Hypertrophy disease in patients. Nose hypertrophy disease has several symptoms that are felt which are usually caused by several factors such as exposure to certain allergens, chronic sinus infections, or a family history of similar nasal problems, so several diagnostic tests are needed that can confirm the diagnosis, such as nasal endoscopy to see directly the condition inside the nose, medical imaging such as CT scan or MRI to evaluate the structure of the nose in more detail, or allergy tests to identify the causative allergen. From the above problems, patients really need a system that becomes a recommendation in helping provide information about nasal hypertrophy disease that can diagnose early and take further action to prevent nasal hypertrophy disease. By using the certainty factor method, information from the steps above can be systematically analyzed to determine the level of confidence in the diagnosis of nasal hypertrophy. These factors can be assessed based on severity, presence of typical symptoms, correlation with risk factors, and results of physical examination and diagnostic tests. Based on the results of the CF calculation, the highest value is in the type of nasal hypertrophy disease with the type of Septal Deviation disease having a value of 1 or 100%, in the type of Rhinitis disease having a value of 94.24% and in the type of sinusitis disease having a value of 85.60%. From the results obtained, the system identifies that the patient has nasal hypertrophy with Septal Deviation type by 100%.  

Respiratory tract disease is a common condition that can affect anyone regardless of age. Starting from relatively mild symptoms to alarming symptoms. Although some respiratory diseases are not life-threatening, they should not be taken lightly as they can cause serious complications. What often happens is that it is difficult for a patient to see a specialist doctor because of the limited number of respiratory specialists who cannot fully serve patients, so people often have difficulty if they want to consult directly. This triggers the habit of the community to treat complaints on their own with simple drugs bought freely at drugstores or pharmacies without knowing for sure the disease they suffer, as well as the length of waiting for queues, consultation fees that are quite expensive and not everyone has a short distance to the hospital prefer not to go to a specialist. Like other organs of the human body, breathing is also prone to various diseases. Respiratory organs will be disrupted and can even cause death. By using the Naïve Bayes method above, it is known that the diagnosis of respiratory disease is that the young female patient is diagnosed with a type of respiratory disease called Farangitis (P05) with a percentage of 47.44%.

An expert system is a device designed with the thought processes of one or more experts in specific or complex fields of knowledge. This system is built on instructional elements that identify and analyze data to address unstructured problems or conduct mathematical analyses of particular issues. With the advancement of web-based information technology, computer damage detection becomes easier for users. Therefore, a web-based expert system application using the certainty factor method is needed to detect computer damage. The certainty factor method works based on symptoms and diagnoses weighted by experts and user input. These weights are then calculated using the certainty factor formula to produce a confidence level in the given diagnosis. The end result is the creation of an expert system application capable of detecting computer damage for users using the web-based certainty factor method. This application not only enhances efficiency in detecting damage but also facilitates maintenance processes by providing a history of damage detection, thereby reducing the time required for repairs. Thus, this application offers an effective and efficient solution for computer damage detection. Additionally, this application can be continually developed and adapted to user needs, making it a highly useful tool in computer maintenance across various environments.

Kucing adalah hewan peliharaan populer yang sering kali rentan terhadap berbagai penyakit. Ketidakmampuan pemilik untuk mendiagnosa penyakit kucing secara tepat waktu sering kali mengharuskan konsultasi dengan dokter hewan yang sebagian besar hanya tersedia di perkotaan. Penelitian ini bertujuan mengembangkan sistem pakar berbasis web menggunakan metode Forward Chaining dan Certainty Factor untuk membantu mendiagnosa penyakit pada kucing. Metodologi pengembangan sistem ini mencakup tahap persiapan, prototyping, dan penyelesaian. Pada tahap persiapan, masalah dirumuskan dan wawancara dengan dokter hewan dilakukan untuk membangun knowledge base. Tahap prototyping melibatkan pembuatan mesin inferensi dan knowledge base, sementara tahap penyelesaian meliputi implementasi sistem ke dalam antarmuka pengguna berbasis web menggunakan PHP dan framework Laravel. Hasil uji sistem menunjukkan konsistensi tinggi dengan hasil diagnosa manual menggunakan Excel. Sebagai contoh, diagnosa penyakit Virus Panleukopenia memiliki nilai certainty factor sebesar 94,62% pada aplikasi, sementara perhitungan manual menunjukkan 95,21%, dengan perbedaan hanya 0,41%. Hal ini menunjukkan bahwa sistem pakar yang dikembangkan mampu memberikan diagnosa yang cepat dan akurat. Kesimpulannya, sistem pakar berbasis web ini dapat diandalkan untuk mendiagnosa penyakit kucing dan membantu dokter hewan serta pemilik kucing melakukan diagnosa awal dengan lebih efisien.

Abstract -  Corn plants are one of the plants that are easy to grow and relatively fast to get results but also a plant that is vulnerable to pests and diseases. The symptoms that arise require an expert or agricultural expert to be able to diagnose. Limited time and expert labor is one of the causes of delayed diagnosis, causing a decrease in farmers' yields. This is the basis for making this expert system by adopting knowledge from agricultural experts about the symptoms of corn disease using the Forward Chaining method. To support the research conducted, researchers used the Research and Development (R&D) research method and the design used the Object Oriented Programming (OOP) method using the Unified Modeling Language (UML). Software is built using the PHP programming language, MySQL as a database, and Bootstrap as an interface design with a web-based system.