Previous researches outlined the advantages of the Analytical Hierarchy Process (AHP) and Analytic Network Process (ANP) methods in solving Multi-Attribute Decision Making (MADM) problems. The advancement of the above methods was continually developed as an effort to cover up various weaknesses. Mainly related to the consistency and linguistic variables in translating the expert opinions. Thus, it initialized the emergence of Fuzzy AHP (F-AHP) and Fuzzy ANP (F-ANP). Due to the restricted operation of these algorithms in smartphone selection, this research attempted to investigate the effectiveness of both methods in providing the analysis of criteria weight, the final recommendation weight, the product recommendation weight, and the execution time in DSS-SmartPhoneRec application development. A survey of one hundred respondents of University students identified the dominant criteria in selecting the smartphone, namely price, Random Access Memory (RAM), processor, internal memory, and camera. Hence, five alternative products were then chosen as the appropriate smartphones’ recommendations based on the respondent’s preferences. As an automatic tool, a DSS-SmartPhoneRec application was built to analyze and compare between F-AHP and F-ANP methods in resolving the smartphone selection cases. It revealed that the level of consistency of criteria weight, the final weight of recommendation, and the weight that the product-based F-ANP was 40% greater than F-AHP. In terms of execution time, F-AHP had a shorter time than F-ANP. Meanwhile, the comparison of products recommendation from DSS-SmartPhoneRec and a manual test showed that F-ANP was 16% more in line with the respondents’ predilection. In a nutshell, the DSS-SmartPhoneRec administered the devote smartphone recommendations based on the user’s expectation. The comparison analysis furnished a learning outcome for the users in determining the appropriate MADM method tailored to the type of cases.
Business technological advancement facilitates human activities through online shopping. The number of online shops in the marketplace offers many kinds of products with attractive marketing strategies thus the customers are confused with the product comprising. Therefore, this research tries to provide an optimal online shop recommendation as an alternative solution. The Decision Support System (DSS) approach on management model applied Multi-Objective Optimization on the Base of Ratio Analysis (MOORA) for the analytical calculation by considering several criteria, including price, rating, discount, a product sold, and response chat. It reveals the ranking of fifty on-line shops in the marketplace as the maximum alternatives' product recommendations. Thus, the customers will be smartly guided to choose the high-quality product at the greatness services of an online shop. The mechanism of DSS based on MOORA was applied through the construction of a prototype system, namely DSS-MyProduct. DSS-MyProduct suggests the buyers with optimal products and the greatest online shop choice for shopping. The application has been tested by using Blackbox and User Acceptance Test (UAT) testing which indicated that the application can perform the functions and operational procedures appropriately. 83.4% of users agreed that this DSS-MyProduct aids them in deciding on the optimal choice preferred in shopping. The comparison of user manual selection and system calculation shows a positive outcome on the accuracy of the system. Hence, this application can be used by the marketplace as a smart recommendation tool for product selection.
Penyakit merupakan suatu kondisi di mana pikiran dan tubuh mengalami semacam gangguan dan ke tidaknyamanan bagi yang mengalaminya. Semakin hari, jumlah pasien di Puskesmas Kuok semakin meningkat dengan beragam jenis penyakit yang berbeda-beda. Peningkatan jumlah pasien mengharuskan staff Puskesmas Kuok harus selalu memperbaharui data rekam medis pasien. Data rekam medis pasien ini berupa laporan yang berisikan jumlah pasien dan penyakit yang diderita. Berdasarkan data tersebut, pihak Puskesmas perlu untuk mengetahui informasi tentang penyakit yang paling rentan dan banyak diderita pasien. Penelitian ini bertujuan untuk mengelompokkan data penyakit pasien untuk mengetahui penyakit yang paling banyak diderita oleh pasien di Puskesmas Kuok Kabupaten Kampar. Pengelompokan data penyakit pasien dilakukan dengan tahapan Data Mining Clustering dan dilanjutkan dengan tahapan metode K-Medoids. Selanjutnya, di lakukan pengujian cluster menggunakan Silhouette Coefficient. Hasil penelitian ini menunjukkan bahwa pada cluster 1 penyakit yang paling banyak diderita oleh pasien adalah penyakit Diabetes Melitus tidak bergantung Insulin (tipe II) dengan total kasus sebanyak 435 kasus. Pada cluster 2, penyakit yang paling banyak diderita oleh pasien adalah penyakit Hipertensi Esensial (Primer) dengan total kasus sebanyak 2785 kasus. Untuk cluster ke 3, penyakit yang paling banyak diderita oleh pasien adalah penyakit Vulnus Laseratum, Punctum, dengan total kasus sebanyak 328 kasus. Dari hasil cluster yang diperoleh, maka didapatkan hasil pengujian Silhouette Coeficient sebesar 0,900033674.
Kemajuan ilmiah yang konstan mengarah pada pertumbuhan teknologi yang luas. Sistem informasi hanyalah salah satu dari berbagai bentuk teknologi informasi. Suatu sistem informasi yang dikenal dengan sistem pakar (expert system) dapat dimanfaatkan untuk meningkatkan pelayanan medis, termasuk identifikasi penyakit secara dini dan pengobatan pasien yang lebih baik. Sistem pakar adalah program yang memasukkan pengetahuan manusia ke dalam komputer dengan tujuan menyelesaikan masalah yang biasanya ditangani oleh para pakar. Metode Depth First Search (DFS) merupakan metode tertentu dimana pencarian pada sebuah sumber dengan mengikuti satu cabang sebuah sumber hingga mendapatkan penyelesaian. Penelitian ini dimaksudkan untuk membantu mengungkapkan kesenjangan dalam penelitian yang telah dilakukan serta mendorong pertumbuhan konsep baru dan peningkatan kemampuan untuk memanfaatkan sumber daya penelitian yang sudah tersedia. Metode pengumpulan data yang diterapkan pada penelitian ini diantaranya yaitu, dengan cara mengidentifikasi, mengevaluasi, interpretasi dan mencari literatur dari berbagai sumber yang terpercaya seperti melakukan review jurnal terkait metode yang digunakan baik jurnal lokal, nasional maupun internasional yang terakreditasi. Artikel yang dirujuk dalam penelitian ini berjumlah 20 artikel yang diterbitkan dari tahun 2019-2023. Peneliti mengumpulkan 20 artikel tersebut dari beberapa website pencarian jurnal seperti; google scholar, Crossef,dan IEEE (Institute of Electrical and Electronics Engineers) dengan kata kunci Depth First Search (DFS), Expert System, dan Artificial Intelligence. Hasil penelitian ini menunjukkan bahwa metode Depth First Search (DFS) banyak digunakan para peneliti sebelumnya dalam menyelesaikan berbagai bentuk persoalan yang berhubungan dengan sistem pakar, seperti dalam mendignosa penyakit, dalam peningkatan pemanfaatan jaringan, menentukan rute evakuasi, strategi diagnosis dengan lebih baik, menunjukkan efektifitas metode dan peningkatan citra secara digital.
The usability and usefulness of smartphones have been found to lack optimality. Moreover, the action of the customer appears to behave as a consumptive user instead of buying following the basic needs. In selecting the right smartphone, this study provides an alternative option for buyers. The Fuzzy Analytical Hierarchy Process (F-AHP) approach is applied by distinguishing between two distinct decision-making namely, Profile User as a user recommendation-based, and Smartphone-based selection. The suggested requirements are hobbies, areas of jobs, and the use of social network applications in determining the user profile. The weights of the criteria and alternatives for profile users are acquired through the dissemination of questionnaires to 117 respondents. In the meantime, parameters such as Random-Access Memory (RAM), Read-Only Memory (ROM), camera, processor, screen, and battery are added to the smartphone list of criteria upon on the interviews of 15 experts and practices in smartphone and Information Technology (IT). F-AHP rates each of the Smartphone and User Profiles as a first-round output. A rule-based expert system is employed to intertwine Smartphone and User Profiles decision-making viewpoints. The relationship between the Smartphone and the User Profile is therefore circumscribed as the final decision to applaud the acceptable Smartphone for those users of the profile. A prototype of the MatchSmartPhone application has been developed to computerize the F-AHP calculation. This application can be used to assist users according to the user's profile in delivering the best Smartphone device recommendations. Users would be wiser and smarter when shopping in advance.
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