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<![CDATA[Integrasi Variable-Centered Intelligent Rule System dengan Teori Dempster-Shafer pada Sistem Pakar Infeksi Saluran Pernafasan Akut ]]>
<![CDATA[Mola, Sebastianus Adi Santoso]]>;
<![CDATA[Rumlaklak, Nelci D.]]>;
<![CDATA[Prityaningsih, Ni Putu Dana]]>
<![CDATA[ JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 1 (2019): Volume 9 Nomor 1 Tahun 2019 ]]>
Publisher : <![CDATA[Universitas Diponegoro ]]>
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DOI: 10.21456/vol9iss1pp71-76
<![CDATA[Acute Respiratory Infection (ARI) is a disease caused by infections of the respiratory tract, larynx, pharynx, sinuses and nose. ARI often causes death because the sufferer who comes for treatment is underestimated is already suffering from severe ARI. In 2013 to 2015 ARI was one of the ten most common illnesses in the city of Kupang, where ARI ranked first, followed by other diseases of the upper respiratory tract and grastitis. This study produced an expert system to diagnose ARI using the Variable Centered-Rule System method which functions to facilitate knowledge development and Dempster-Shafer Theory which serves to overcome uncertainty by entering the density of each symptom of ARI in the system. The VCIRS method is a method of building knowledge and inference strategies on expert systems. This method is rigid in accommodating changes in inference strategies except for changes in knowledge structures. This study aims to make the VCIRS method dynamic in an inference process where the sequence of variables in inference is determined by the occurrence and density of the variable. System accuracy by using medical record data of 95% with the triggering sequence of symptoms becoming dynamic every time a consultation session occurs.]]>
<![CDATA[PENERAPAN METODE HEURISTIK (ALGORITMA IDA* DAN B&B) DALAM PEMECAHAN N-Queen Problem ]]>
<![CDATA[Novi Penna]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Meiton Boru]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 6 No 1 (2018): Maret 2018 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v6i1.353
<![CDATA[N-Queen problem is a problem which a N-Queen pawn in is place chess with n x n size. N-Queen pawn is a put in such away in chess board with under condition that the queen pawns do not attack each other. The attacking movement of N-Queen problem is similar to the way of the queen pawn attacking in chess. Commonly the queen pawn moves horizontally to left and right, forward and backward vertically and also diagonally, so there are no queen pawns in a line of horizontal, vertical and diagonal.Heuristical searching is one of the method which can be used to solve the game of N-Queen problem selectively, by giving solution of the shortest time channel efficiently in order to able the user to solve this game well, fast and relevantly. Some algorithms that use heuristic is Iterative Deepening algorithm A* (IDA*) and Branch and Bound (B&B) algorithm. The used heuristic function is by seeing the numbers of boxes which are empty and the number of queen which is not be put in board yet.The aim of making this final project to implement the solving of N-Queen problem using heuristic searching (B&B and IDA*). From this implementation could be seen that IDA* and B&B algorithm is able to give channel in solving N- Queen problem. After a repetition of test by using 19 sheet of data, it is shown the comparison of result between IDA* algorithm and B&B algorithm which IDA* algorithm result the shorter channel in solving N-Queen problem based on the node 61%, and time 41% which better than B&B algorithm.]]>
<![CDATA[PENERAPAN MODIFIED CERTAINTY FACTOR DALAM SISTEM PAKAR TES KEPRIBADIAN FLAG ]]>
<![CDATA[Romy O. D. Djami]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Tiwuk Widiastuti]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 6 No 1 (2018): Maret 2018 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v6i1.354
<![CDATA[Expert system is one of artificial intelligence engines that is using specific knowledge of an expert to solve a specific problem. In this study, the expert system is built to implement FLAG personality test using Modified Certainty Factor method in order to help counselee knowing his personality type and the careers suitable for him. Knowledge source for this system is obtained from the book Tes Bakat Anda (Test Your Own Aptitude) by Jim Barrett and Geoff Williams (2002) along with several consultations with Irianti Agustina, S.Pd., M.Pd. and Dra. Sri Rahayu Djami. This system is able to provide the output in the form of personality type of the counselee as well as career recommendations suitable for him. Based on study on 141 data of counselees, the results are: By using Modified Certainty Factor, this expert system has accuracy of 83.69%, and provides more certain output than the output provided by the conventional FLAG. Therefore, researcher recommends the using of Modified Certainty Factor method to improve any other personality test which still has not given certain output.]]>
<![CDATA[RANCANG BANGUN APLIKASI PREDIKSI CALON KREDITUR PADA BANK MUAMALAT KUPANG ]]>
<![CDATA[Abdul G Farid]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Dony M Sihotang]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 5 No 2 (2017): Oktober 2017 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v5i2.358
<![CDATA[The implementation of stored-transaction data can provide a lot of useful knowledge to createbusinesses intelligence in Muamalat Bank. But Muamalat Bank has not done it yet; so, it will be difficultto give credits to the creditors. This study aimed to create business intelligence in terms of prospectivecreditors prediction. It was expected that it could predict creditors in making payments using old existingcreditors forms data. The research applied the K-Nearest Neighbor algorithm (K-NN) where thisalgorithm looking for similarly between render candidates and old creditors as much as k values thatstill or have done their lends to Muamalat Bank Kupang. The result of this research shows that with KNNalgorithm, a creditor can be predict using data comparism. Highest accuracy can be reach when kvalue=5, with accuracy level up to 80%.]]>
<![CDATA[CASE BASED REASONING UNTUK MENDIAGNOSA PENYAKIT KEHAMILAN MENGGUNAKAN COSINE SIMILARITY ]]>
<![CDATA[Adelysa P Gitaswara]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Emerensiana S.Y Pandie]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 5 No 2 (2017): Oktober 2017 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v5i2.359
<![CDATA[The application of case-based reasoning in diagnosing pregnancy deseases is motivated by the lack of number of obstetricians. The use of CBR aims to solve new problems by adapting the solutions contained in the previous case, by calculating the level of similarity. Calculation of similarity value using cosine similarity method, with threshold equal to 100%. This system can diagnose 6 diseases, 28 existing symptoms. System outbreaks of illness experienced by patients based on symptoms induced by non-specialist medical personnel, as well as handling solutions accompanied by a presentation of similarities with previous cases to indicate the degree of truth of possible diagnosis. Based on the results of case testing, the results obtained: the system can retrieve the exact old case and have used the cosine similarity methodology correctly, shown with 100% accuracy results, and using 104 cases is optimal enough to diagnose 6 illnesses shown with average results Similarity to 20 cases is 90%.]]>
<![CDATA[PENERAPAN METODE FUZZY SERVICE QUALITY (SERVQUAL) UNTUK MENGANALISA KEPUASAN PELAYANAN PENDIDIKAN PADA JURUSAN ILMU KOMPUTER FAKULTAS SAINS DAN TEKNIK UNIVERSITAS NUSA CENDANA ]]>
<![CDATA[Roswita R Ligoresi]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Nelci D Rumlaklak]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 5 No 2 (2017): Oktober 2017 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v5i2.365
<![CDATA[In carrying the service of education, Departmen Of Computer Science Faculty Of Science And Technique University Of Nusa Cendana, trying to give the service that can be contented the students. So far the departmen doesn’t know how the assessment of students against the service given. The survey of students statisfaction can be a manner to deliver what they feel and what is the hope of students against the service of education. Fuzzy service quality (servqual) method can be used to analyze the statisfaction of service. The concept of fuzzy is used to help the respondent for giving value that more objective, while the servqual method define the statisfaction of service as how far the difference between the facts and the hope on the service that is received by respondent. This method have five dimention that are tangibles, reliability, responsiveness, assurance dan emphaty. The result of service statisfaction analysis in Computer Science Department using the fuzzy method in the academic year 2016/2017 the value is GAP -14.3197, that means the giving service is not statisfy. Based on the result of analysis gived repair recommendation of each dimention that is the value of GAP is smallest negative.]]>
<![CDATA[IMPLEMENTASI CASE BASE REASONING MENGGUNAKAN METODE COSINE SIMILARITY UNTUK MENDIAGNOSA PENYAKIT PADA SAPI ]]>
<![CDATA[Ssainah P Faransyah]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Yelly Y Nabuasa]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 6 No 2 (2018): Oktober 2018 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v6i2.515
<![CDATA[Case Based Reasoning (CBR) is a case-breaking technique based on experience in cases that have previously occurred with the highest similarity value. In this study, the authors apply CBR to diagnose cow disease. Sources of system knowledge are obtained by collecting cases from medical records on 2014, 2016, and 2017. The system uses the Rough Set method for indexing and the calculation of similarity values using the Cosine Similarity method with threshold 70%. This system is able to diagnose 15 diseases based on 29 existing symptoms. The output of the system in the form of the illness experienced, the solution and the presentation of similarities with the previous case to show the truth level of possible diagnose. Based on the test of 30 cases on casebase obtained system accuracy at second part is 27% and at third part the system gets the best result using 3 fold by 33,33%. The system produces low accuracy due to the small number of cases and the scattered data in the case.]]>
<![CDATA[IMPLEMENTASI PENETAPAN PAJAK KENDARAAN BERMOTOR UBAH BENTUK PADA SAMSAT KABUPATEN TIMOR TENGAH SELATAN ]]>
<![CDATA[Emerensye Sofia Yublina Pandie]]>;
<![CDATA[Febryan Cornelis Lomi]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>
<![CDATA[ J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v7i1.886
<![CDATA[The problem in doing the majoring in SAMSAT of sub-province of Timor Tengah Selatan can be solved by using information system. In a month SAMSAT of sub-province of Timor Tengah have served 3.131 taxpayer, that means for a day SAMSAT of sub-province of Timor Tengah served approximately reach 150 taxpayer and total vehicles in registration is 39.492 vehicles. The system that is developed to maintain vehicles data, types of vehicle data, vehicles brands data, dumps data, vehicles price data, registration data, and to count vehicles tax determining rightly dan quickly and can gain the report of all registration data, specific report of the vehicles, specific report of vehicles tax determining and receipt tax payments of vehicles transform. This system capable to answered the hypothesis H0 about contentment of service with satisfaction level more than 70% viz 78%.]]>
<![CDATA[Case Based Reasoning untuk Mendiagnosa Jenis Gangguan Jiwa Menggunakan Metode Dempster Shafer ]]>
<![CDATA[Viani Anika Afeanpah]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Adriana Fanggidae]]>
<![CDATA[ J-ICON : Jurnal Komputer dan Informatika Vol 10 No 1 (2022): Maret 2022 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v10i1.6326
<![CDATA[Mental disorders are disorders of behavior, moods and thoughts that can change a person's behavior differently than usual. Cases of mental disorders obtained from medical record data at the Naimata Mental Hospital (RSJ) in 2019 were 6,157 patients with 2 mental specialists. The lack of a number of mental specialists has caused some mental health programs not to run properly, resulting in a longer recovery rate for mental disorders. In this study, a case-based reasoning system was created to overcome the problem of the lack of mental health workers at Naimata Hospital. The system uses the dempster shafer method for the indexing process and cosine similarity to calculate the similarity value. This system diagnoses 9 types of mental disorders based on 125 symptoms. The output of the system is a diagnosis of the type of mental disorder suffered by the patient. Based on the test results on 90 data on a case basis by dividing the data into 10 folds, the system accuracy for similarity is 49.83% and indexing is 81.01%. The test was carried out another way, by dividing the data randomly into 3 groups, namely 9:1, 8:2 and 7:3 20 times. The first group got an average indexing of 85.21% and similarity 49.22%, the second group got an average indexing of 82.01% and similarity 48.84%, the third group got an average indexing of 78.82% and similarity 48.09%. The average accuracy is low due to the unbalanced case data for each type of disturbance.]]>
<![CDATA[Implementasi Hamilton Anxiety Rating Scale untuk Mendiagnosis Tingkat Kecemasan pada Mmahasiswa Dalam Penyusunan Skripsi ]]>
<![CDATA[Elfrida Veranda Beka Dede]]>;
<![CDATA[Sebastianus Adi Santoso Mola]]>;
<![CDATA[Yelly Yosiana Nabuasa]]>
<![CDATA[ J-ICON : Jurnal Komputer dan Informatika Vol 10 No 1 (2022): Maret 2022 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v10i1.6353
<![CDATA[Students who do thesis generally feel anxious. Lack of motivation and creativity, and there are still many students who find it difficult to write scientific papers are the main causes of anxiety. This anxiety needs to be addressed immediately so as not to have an impact on the writing time of the thesis which will be longer. Students can consult with a psychiatrist or psychologist to deal with anxiety. However, the inefficient consulting service becomes a problem due to the unbalanced comparison between the population in East Nusa Tenggara and clinical psychologists. Therefore, we need a system that has the experience and knowledge of an expert to determine the level of anxiety of students who are writing a thesis using the Hamilton Anxiety Rating Scale (HARS) and forward chaining inference. From the results of the research conducted, it is known that forward chaining inference is proven to be able to be applied and accurate in diagnosing anxiety levels in students who are writing thesis with 100% accuracy.]]>
