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All Journal Jurnal Mantik Penusa MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Komputasi dan Teknologi Informasi JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) ComTech: Computer, Mathematics and Engineering Applications Jurnal Mantik TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) INFOKUM Journal of Innovation Information Technology and Application (JINITA) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing International Journal of Basic and Applied Science Jurnal Mandiri IT Jurnal Nasional Teknologi Komputer LEBAH Journal of Computer Science and Research International Journal of Enterprise Modelling Indonesian Journal of Education And Computer Science
Fristi Riandari
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Journal : journal of intelligent decision support system idss

 1 
Expert System Diagnosing Diabetes Using the Web-Based Dempster Shafer Method Siti Ilya Suwella; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v4i4.31

Abstract

Diabetes is a very dangerous disease because diabetes can attack other organs of the body so that it can cause death. This is due to the lack of technology-based information that can help determine the symptoms of diabetes. With the limited number of diabetes experts, an expert system is needed to diagnose diabetes. The method applied to the system is the Dempster Shafer method, by determining 17 symptoms and 3 types of disease, as well as compiling a rule base in determining the relationship of each symptom so that the results in the calculation achieve 100% accurate results. This method has 5 steps in its completion. The results showed that the Dempster Shafer method could be used to diagnose the symptoms of diabetes. So that the existence of this system can help the wider community in finding information about the symptoms of diabetes.
Expert System Diagnosing Anxiety Disorder Using Based Naïve Bayes Method Danvy Nadhira; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v4i4.34

Abstract

Psychological problems such as Anxiety Disorder have become a common problem in the world. Most sufferers of this disease are under 45 years old on average and usually this disorder often attacks the mentality of women. However, this disease is often considered trivial and not many sufferers realize it. Not to mention the handling of course requires quite a lot of money. Another thing is the lack of information about this disease, which causes the risk of sufferers of Anxiety Disorder to increase every year. To solve existing problems, it can be solved by using computer technology in the health sector that can diagnose a disease like an expert, namely an expert system application disease symptoms. The purpose of this study is as a first step to treat this disorder as quickly as possible. The application of the Naïve Bayes method plays a role in being able to provide diagnostic results because the Naïve Bayes method is considered capable of providing the largest clarification of the value of v based on the selected symptoms.
Application Of Dempster Shafer Method To Diagnose Disease In Sugarcane Plant Dewi Novika Simanjuntak; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v4i4.36

Abstract

Sugarcane is a very important and agrarian plantation product in Indonesia, because sugar cane is a producer of sugar. However, in its cultivation, several problems often occur, such as diseases in sugarcane plants where when sugarcane plants are attacked by disease and are not handled, farmers will experience crop failure. Based on this, a tool is needed in the form of an expert system to diagnose diseases in sugarcane plants. The method used in this study is the Dempster Shafer method which processes data by providing evidence based on the belief funcation and plausible value of each symptom. This study treats 4 types of disease with 13 symptoms. The results showed that the dempster shafer method can be used as a tool in diagnosing sugarcane plant diseases so that it is expected to help farmers in handling diseases that attack sugarcane plants quickly and precisely and can increase profits from sugarcane harvests for farmers.
Implementation Of Data Mining With C4.5 Algorithm For Determining The Home Industry Product Marketing Strategy Teresia Herniamwati Zebua; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v4i4.37

Abstract

me Industry is one of the SMEs that produce home-made products, such as pastries. Not all of these products are sold by consumers. This study uses a web-based C4.5 algorithm to determine marketing strategies for Home Industry products that are not selling well by classifying the indicators that most influence consumers in buying Home Industry products so that they can provide information about marketing strategies that will be carried out. Based on the results of the study, the highest gain value was the packaging attribute with a value of 1.86, so that the packaging attribute was used as the root in the formation of a decision tree. Then the second highest gain is the price attribute with a value of 1.26, and the third highest gain is the taste attribute with a value of 1.03, then the fourth highest gain is the service attribute with a value of 0.89.
Decision Support System in Determining the Location of Village Health Services (Puskesmas) in Pagar Merbau District Using the Profile Matching Method Wan Wimar Yahya; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v4i4.38

Abstract

Community health center (puskesmas), is a health service facility that organizes public health efforts and first-level individual health efforts, and prioritizes promotive and preventive efforts. In accordance with geographical conditions, area size, transportation facilities, and population density in the working area of the puskesmas so that the puskesmas services are accessible to the population, to assist the smooth process of services that will make it easier for the community. Therefore, to assist in determining an ideal puskesmas development location, a Decision Support System (DSS) is used, the process of calculating the results of determining the location of the puskesmas construction using the Profile Matching method. As for the alternatives of this study, 6 villages were taken, namely Tanjung Mulia, Sumberejo, Sidodadi, Pagar Merbau II, Sidoarjo Satu Pasar Miring, and Bandar Dolok. And from the results of calculations using the Profile Matching method, it displays the ranking of the results of determining the location, where the highest value is in Tanjung Mulia village with a value of 3.69 so that it can be used as a solution or consideration in determining the location of the puskesmas to be built.
Robust mathematical model for supply chain optimization: A comprehensive study Lise Pujiastuti; Mochamad Wahyudi; Barreto Jose da Conceição; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 2 (2023): June : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i2.137

Abstract

This research provides a comprehensive review of existing literature and research on supply chain optimization, aiming to capture the advances made in the field and identify emerging perspectives. Supply chain optimization plays a vital role in improving operational efficiency, reducing costs, and enhancing customer satisfaction. By analyzing a wide range of studies, this review examines various approaches, models, and techniques used in supply chain optimization, including mathematical programming, stochastic programming, simulation, and metaheuristic algorithms. The review also encompasses key aspects such as demand forecasting, inventory management, production planning, transportation, and distribution network design. Furthermore, the study investigates recent trends, such as incorporating sustainability considerations, addressing uncertainties and risks, and utilizing real-time data and decision support systems. By identifying the gaps and limitations in the existing research, this review sets the stage for future investigations and provides valuable insights for researchers and practitioners seeking to advance supply chain optimization efforts. The findings of this review contribute to enhancing the understanding of supply chain optimization and provide a roadmap for future research directions in this dynamic and critical field
Co-Authors Adjie Bintang Pamungkas Afifa, Rizky Maulidya Afrisawat, Afrisawat Afrisawati afrisawati, Afrisawati Agustina Simangunsong Aisyah Alesha Arjon Samuel Sitio Baik Sepwanri Sinaga Barreto Jose da Conceição Benny Ginting Bosker Sinaga Chandra, Suherman Christina Simanjuntak Cristy, Niolinda Dalimunthe, Yulia Agustina Danvy Nadhira Dedi Setiawan Halawa Demita Sihotang Dewi Novika Simanjuntak Dimas Ribowo Esera Gulo Ginting, Ramadhanu Hamed Huckle Schubert Hasugian , Paska Marto Hasugian, Penda Sudarto Hengki Tamando Sihotang Husain Husain Ibnu Rizky John Foster Marpaung Judijanto, Loso Lamhot Situmorang Lise Pujiastuti Marsoit, Patrisia Teresa Mochamad Wahyudi Muhammad Rafli Muhammad Syaif Nasib Ratna Sari Purba Nellysa Putri Denila Nasution Novita Ria Lase Nurul Hayani Petti Indrayati Sijabat Pilisman Buulolo R. Mahdalena Simanjorang Ramayuni Marpaung Rehentiara Siringoringo Rian Syahputra Rita Zahara Tarigan Ritha Zahara Tarigan Ritonga, Rama Prameswara Rohit Gautama Roimasro Sibagariang Safitri, Habibi Ramdani Sari Murni Sarjon Defit Sethu Ramen Sihotang , Jonhariono Sim, Lee Choi Simangunsong, Agustina Sinaga, Baik Sepwanri Siringoringo, Rimmar Siti Ilya Suwella Situmorang, Lamhot Song , Jiang Lou Subowo Subowo Subowo Subowo Sulistianingsih, Indri Susandri, Susandri Tarisa Tarigan Tasril, Virdyra Temasokhi Ndruru Teresia Herniamwati Zebua Vina Winda Sari Vinsensia, Desi Wan Wimar Yahya Weno Syechu Yuda Perwira Yunus Simare-mare