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Contractors face most of the construction risks among stakeholders, and insurance is a common method to mitigate these risks. However, not all risks are insurable. While prior studies have typically assessed risk insurability through a binary approach (insurable versus non-insurable) and lacked clear criteria, this study offers a novel perspective by evaluating the insurability of construction risks based on four criteria: ‘accidental events,’ ‘quantifiable,’ ‘numerous and homogenous,’ and ‘evaluable.’ This study develops a fuzzy-based model to assess the degree of the construction risk insurability, accounting for the uncertainty, imprecision, and vagueness inherent in evaluating insurability against a specific criterion and criteria combinations. The model is applied to assess the insurability of several construction risks, illustrating its practical application. This paper concludes by discussing the model’s limitations and suggesting directions for future research.

The representation of the fuzzy set membership curve consisting of trapezoidal, triangular, and linear shapes, has an important role in the fuzzy logic system. The selection of the curve's shapes determines the useable membership function and affects the fuzzy output value. Previous studies generally used curves that had been employed in predecessors or other studies that did not explain the reason for choosing a fuzzy member curve. This condition became problem because there was not a guide in selecting the appropriate membership function model for the parameters used in the fuzzy process so that most researchers only use membership functions that are commonly used in previous studies or in the same case as their research. The purpose of this study was to determine the effect of selecting trapezoidal and triangular curves on the performance of Tsukamoto's fuzzy logic for determining the rice-fields suitability status. The research methodology comprised 3 main stages. The first stage was data collecting, to collect soil pH values, soil moisture, and air temperature in rice fields. The second stage was the implementation of the Tsukamoto fuzzy. At this stage, two membership function curves were used. The third stage was a comparative analysis of Tsukamoto's fuzzy's output of trapezoidal and triangular curves. The results obtained indicate that there is no significant performance difference between the two different membership functions. The results of the research with the trapezoidal membership function have a better accuracy rate of 93% while the triangular membership function has an accuracy rate of 90%.

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Situbondo Regency is one of the regions designated as a pilot minapolitan area in Indonesia. This study aims to analyze the feasibility of developing a Minapolitan area in Situbondo Regency using a sustainable development perspective. The data processing method used in this research is the Mamdani fuzzy inference system. This study uses sustainable development dimensions to examine the feasibility of minapolitan area, including ecological, social, economic, and institutional aspects. Data processing aids using Matlab software. The results showed that the Minapolitan area in Situbondo Regency is feasible for a sustainable Minapolitan area. Situbondo Regency has an ecologically appropriate area and meets the requirements for developing fisheries and marine potential. The social environment in Situbondo Regency is also quite conducive to the development of the Minapolitan area, which can be seen from the community's active role in managing fishery resources. Community involvement in fisheries resource management is supported by fishermen and cultivation groups, including supporting institutions that can institutionally strengthen the presence of minapolitan in Situbondo Regency. The Minapolitan area's development is considered to provide economic benefits to both the communities around the area and the local government.

Copyright of Journal of Social & Technology / Jurnal Sosial dan Teknologi (SOSTECH) is the property of Green Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tujuan dari penelitian ini adalah untuk menentukan jumlah kepesertaan PBI pada BPJS Kesehatan Cabang Kota Pekanbaru. Dalam penelitian ini digunakan metode FIS Sugeno yang merupakan salah satu Fuzzy Inference System. Tahapan-tahapan yang dilakukan yaitu menentukan himpunan fuzzy, fungsi implikasi, dan defuzzyfikasi serta keakuratan peramalan. Hasil penelitian ini menunjukkan bahwa jumlah kepesertaan PBI dengan variable input BPBI dan Jamkesda dan PJKMU Askes menggunakan Metode FIS Sugeno memiliki nilai keakuratan yang mecapai 94,17%, hal ini berarti hasil peramalan yang dilakukan mendekati dengan jumlah kepesertaan sebenarnya

Bahan bakar merupakan salah satu kebutuhan yang saat ini tidak bisa dilepaskan dari masyarakat. Bahan bakar cair terutama bensin atau premium, pertalite, pertamax, dan solar merupakan bahan bakar yang digunakan pada alat transportasi. Semakin banyak alat transportasi yang dimiliki masyarakat dapat memungkinkan tidak tersedianya stok bahan bakar di salah satu SPBU (Stasiun Pengisian Bahan Bakar Umum) tertentu. Dengan tidak tersedianya stok persediaan bahan bakar di SPBU, hal ini dapat menimbulkan beberapa masalah, seperti antrian yang panjang pada salah satu SPBU, serta kurangnya kebutuhan bahan bakar pada masyarakat. Salah satu metode untuk memecahkan masalah tersebut adalah menggunakan metode Fuzzy Tsukamoto. Fuzzy Tsukamoto merupakan salah satu metode yang termasuk ke dalam sistem inferensi fuzzy. Metode ini dapat menentukan jumlah produksi, sehingga jumlah produksi sebuah barang dapat diprediksi. Hasil penelitian menunjukkan bahwa metode Tsukamoto mampu memprediksi jumlah penerimaan stok bahan bakar yang seharusnya diterima oleh SPBU pada periode berikutnya. Dimana, hasil pengujian ketepatan prediksi diukur dengan menggunakan metode MAPE (Mean Absolute Percentage Error) dengan nilai persentase error yang didapatkan adalah sebesar 16 %, sehingga kinerja sistem dalam memprediksi stok bahan bakar dapat dikatakan bagus.

Sikka District is an area with a dry tropical climate. Most of the plants especially food crops in Sikka District depend on rainfall. The lack of rain coupled with the weather anomalies occurring in Sikka District make Sikka District categorised in the area threatened by food insecurity. Food crop cultivation often experiences obstacles, one of which is in determining the suitability of agricultural land for the advancement of certain food crops because the productivity of food crops depends on the quality of the area used. Therefore, this study aimed to develop a smart decision support system to determine land suitability with food crops. This study used a fuzzy analytic hierarchy process to determine the value of alternatives based on parameters that affect the relevance of the land with the type of food crop. The results showed that corn food crops were the best alternative crop with a value of 0.339 of the three alternative food crops studied and then use the method fuzzy inference system to calculate the amount of land suitability. Kopong Village and Geliting Village were the best villages with land suitability values 81.

Penelitian ini dilakukan pada Sekolah Menengah Pertama (SMP) Mazroatul Ulum di Tangerang. Sekolah ini berusaha untuk meningkatkan mutu dan daya saing dari siswa-siswi agar dapat bersaing dengan sekolah lainnya. Salah satu cara yang diambil adalah dengan menerapkan pemilihan murid teladan berdasarkan penilaian yang diperoleh. Proses untuk menentukan predikat siswa teladan di SMP Mazro’atul Ulum saat ini dengan mempertimbangkan 4 kriteria yaitu data rata-rata rapor, total absensi berdasarkan alpha, nilai kepribadian, dan nilai ekstrakurikuler. Sebelumnya, sekolah ini belum memiliki aturan yang valid mengenai kriteria terhadap pemilihan siswa teladan. Untuk mengatasi masalah tersebut, dikembangkan Sistem Pendukung Keputusan (SPK) dengan metode Fuzzy Tsukamoto. Metode tersebut merupakan pilihan yang tepat dalam menangani masalah pengambilan sebuah keputusan yang menggunakan beberapa kriteria hingga menghasilkan dua keputusan yaitu teladan dan tidak teladan. Jika nilai probabilitas siswa lebih besar sama dengan 70 maka masuk ke rekomendasi teladan dan jika di bawah 70 maka tidak teladan. Dalam pengujian yang dilakukan pada data siswa kelas 7, 8, dan 9 pada tahun ajaran 2018/2019, bahwa sistem ini dapat menentukan siswa yang berhak mendapatkan predikat teladan dan memberikan penilaian dari hasil keputusan dengan tepat dan efisien.

The development of community farming center (SPR) of cattle beef to consolidate the potential of people's cattle beef to be managed optimally to increase the production and welfare of farmers in realizing national beef self-sufficiency. Jember Regency as one of the centers of cattle beef in East Java Province has a policy to develop SPR in a number of sub-districts but still faces a number of problems that is determining which district will be chosen as SPR location. This research aims to design the model of determining SPR cattle beef location using fuzzy inference system technique. A number of key criteria in location determination are explored then designed into decision support models using the Matlab fuzzy tool box. The results showed that there are three key criteria for determining the location of SPR development of cattle beef, namely 1) potential Feed from plants; 2) population of cattle beef; and the availability of facilities and infrastructure. Decision support model is built with fuzzy inference system technique using Triangular Fuzzy Number (TFN) representation model and MAMDANI inference method. The number of rules built as many as seven rules with the operator or and and and. Model simulation results show that the locations that are categorized as Very Suitable for SPR development of cattle beef are Silo, Sumberjambe, and Ledokombo Subdistricts, While sub District Gumukmas, Sumberbaru, Puger, Wuluhan, Kencong, Bangsalsari, Mumbulsari, and Jenggawah, fall into the Suitable category.

Copyright of Techno.com is the property of Universitas Dian Nuswantoro, Fakultas Ilmu Komputer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The human stress level is rather intangible, and therefore cannot be directly measured. However, this stress can be correlated to external and/or internal factors, which are rather tangible things, such as heart rate, Systolic-Diastolic Blood Pressure, salivary α-amylase, and skin temperature. These factors measurements are provided in wide ranges and vary individually lends itself naturally to fuzzy sets and fuzzy logic. This research is aimed at assessing respondents stress level through the changes of physiological factors above over time. The subjects of this study are 10 healthy adults, aged between 23-35 years old. The measurement time divided into four periods, namely pre-stressor, stressor-I, stressor-II and post stressor period. Pauli-test and mental arithmetic test was used as stressors. Obtained data were analyzed using Fuzzy Inference System (FIS) toolbox in MATLAB. By using fuzzy inference system model, the system succeeds to predict subject stress value/index based on subject physiological value. The result showed that the changes in human factors affects human stress value/index, although the subjects stated that their stress level on the same level their physiological factors were changed during measurement, and the models showed the changes of subject stress value during different period of measurement time. Keywords:

Trans Sarbagita is a public transportation services people at Denpasar, Badung, Gianyar and Tabanan. Trans Sarbagita is aimed to resolve a problems caused by accretion volume of vehicles in Bali. This study conducted to forecast the number of Trans Sarbagita passengers in 2013 using ANFIS. The ANFIS system composed by five layers where each layers has a different function and its divide in two phases, i.e. forward and backward phases. The ANFIS uses a hybrid learning algorithm which is a combination of Least Squares Estimator (LSE) on forwards phases and Error Backpropagation (EBP) on the backward phases. The results show, ANFIS with six inputs with M.F of Pi produces smallest error, compared to seven and eight input and M.F gauss and generalizedbell. Forecast of Trans Sarbagita passenger numbers in 2013 have to fluctuated every day and the average of passenger’s Trans Sarbagita for a day is 1627 passengers with MSE equal to 10210 and MAPE is 4.01%.

Demam berdarah Dengue (DBD) merupakan penyakit yang ditularkan ke manusia melalui gigitan nyamuk Aedes yang terinfeksi virus Dengue. Penyakit ini sudah menyebar luar ke seluruh Indonesia termasuk Kabupaten Malang. Pemerintah dan Dinas Kesehatan di Kabupaten Malang sudah melakukan berbagai upaya seperti pencegahan dan sosialisasi, namun masih terjadi kasus pasien yang meninggal akibat penyakit berbahaya ini.Peramalan jumlah kasus Demam Berdarah sangat penting dilakukan bagi pihak dinas kesehatan agar bisa membuat perencanaan untuk pencegahan dan pelayanan yang lebih matang dalam penanganan pasien di masa mendatang. Pada penelitian ini, digunakan metode Fuzzy Inference System untuk meramalkan jumlah kasus Demam Berdarah di kabupaten Malang. Peramalan dilakukan dengan memproses data jumlah kasus Demam Berdarah pada tiga kelompok kecamatan berdasarkan letak geografisnya tiap bulan dari beberapa tahun sebelumnya dengan melibatkan kepadatan penduduk. Data tersebut juga akan dibagi menjadi data training dan data testing dengan perbandingan 70:30.Tugas akhir ini menghasilkan model peramalan jumlah kasus Demam Berdarah yang memiliki nilai MAPE pada tiap kelompok kecamatan di Dataran Rendah, Dataran Sedang, dan Dataran Tinggi adalah : 6% , 12%, dan 14% sehingga hasil peramalan ini dapat dikategorikan baik.

Bed active carbon is one of the most important materials that had great impact in determining level of impurities in production of CO2 gas. In this particular factory case, there is unavailability of standard duration time of heating and cooling and steam flow rate for the re-generation process of bed active carbon. The paper discusses the fuzzy inference system for modeling of re-generation process of bed active carbon to find the optimum setting parameter. The fuzzy inference system was build using real historical daily processing data. After validation process, surface plot analysis was performed to find the optimum setting. The result of re-generation parameter setting is 9-10 hours of heating process, 4.66-5.32 hours of cooling process, and 1500-2500 kg/hr of steam flow rate.