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All Journal Jurnal Informatika Jurnal Teknik Industri JIK Jurnal Ilmu Komputer Jurnal Sistem Komputer Prosiding SNATIKA Vol 01 (2011) Proceeding of the Electrical Engineering Computer Science and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Health Notions
Saiful Bukhori
Universitas of Jember
Computer Science & IT Dentistry Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Nursing Public Health

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Penentuan Kesesuaian Lahan Pemukiman di Kabupaten Jember dengan menggunakan Metode AHP Retnani, Windi Eka Yulia; Bukhori, Saiful; Hastungkara, Duhita
Jurnal Sistem Komputer Vol 5, No 2 (2015)
Publisher : Jurnal Sistem Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jsk.v5i2.92

Abstract

Kebutuhan rumah tinggal merupakan kebutuhan primer bagi manusia. Meningkatnya jumlah penduduk pada tiap tahun mengakibatkan meningkatnya kebutuhan rumah tinggal. Peningkatan kebutuhan rumah tinggal tidak menutup kemungkinan berubahnya fungsi lahan-lahan pertanian, hutan, dan kawasan lainnya menjadi lahan permukiman baru. Permasalahan ini juga menjadi salah satu fokus pengambangan di Kabupaten Jember. Tidak semua lahan di Kabupaten Jember layak untuk menjadi lahan pemukiman. Pertimbangan penentuan kesesuaian lahan yang optimal untuk wilayah permukiman menggunakan berbagai parameter seperti kemiringan lereng, kerawanan bencana, tekstur tanah, kepekaan tanah terhadap erosi, aksesibilitas, curah hujan, serta penggunaan lahan. Penentuan kesesuaian lahan pada penelitian ini digunakan metode Analytical Hierarchy Process (AHP) untuk mendapatkan nilai bobot pada setiap parameter. Hasil dari penelitian ini membagi Kabupaten Jember menjadi 3 kawasan permukiman, yaitu kawasan permukiman sangat sesuai (S1) sebanyak 18,35%, kawasan permukiman sesuai sebanyak 65,3%, dan kawasan permukiman tidak sesuai (NS) adalah sebanyak 16,36%.
Parrondo’s Paradox Based Strategies in The Serious Game of RTGS Using Sandpile Model Bukhori, Saiful
Prosiding SNATIKA Vol 01 (2011) Vol 1
Publisher : Prosiding SNATIKA Vol 01 (2011)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research proposed parrondo’s paradox strategies in the serious game of Real Time Gross Settlement using sandpile model, which develop the existence of the parrondo paradox and applied in serious game of RTGS as switching in the settlement process. The settlement process, that our proposed at this paper, is managed by clearing house. The mechanism at clearing house is a transmitter client sends a message of transaction through transmitter bank, that having canal at clearing house, then continue to receiver client through receiver bank by using sandpile model. When settlement process done by one transmitter bank (Process A), the probability of increase Net Worth (NW) is p. When settlement process done by more than one transmitter bank (Process B), we have introduced the probabilities of a self-transition in each state, that is, if the capital is a multiple of three we have a probability r1 of remaining in the same state, whereas if the capital is not a multiple of three then the probability is r2. We will turn to the random alternation of process A and B with probability γ. This will be named as process AB. Examination result of process A change in net worth trend to decrease, process B trend to decrease and process AB that switches randomly between process A and process B trend to increase net worth. Simulation of parrondo’s paradox based strategies in the serious game RTGS using star logo by randomize process A and process B so distribution net worth lot  in the bank that has wealth in intermediate level, total money and total loan trend to rise, total saving loan trend to rise but total wallets trend to decrease.   Kata Kunci: Parrondo paradox, RTGS, sandpile model, net worth.
Duration of Gadget Usage Affects Eye Fatigue in Students Aged 16-18 Years Rahmat, Nafolion Nur; Munawir, Al; Bukhori, Saiful
Health Notions Vol 1 No 4 (2017): October-December 2017
Publisher : Humanistic Network for Science and Technology (Address: Cemara street 25, Ds/Kec Sukorejo, Ponorogo, East Java, Indonesia 63453)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.039 KB)

Abstract

Gadget is one of the innovations generated by humans in order to simplify the work or for the benefit of everyday because with gadgets will easily get various kinds of information needed with a single press. Gadgets easily accessible by everyone one of them is a student or schoolchild so that it is possible for school children have complaints on the eyes if too concentrated on gadgets. Student should know Factors associated with vision complaints such as gender and length of use of gadgets in a day. The purpose of this study was to determine the effect of long use of gadgets against eye fatigue. This research is analytic observational with cross sectional method. The population in this study were all students in SMA Zainul Hasan Gengong Problinggo which used gadgets as many as 296 students. A large sample calculation using the formula Isaac and Michael, amount to 165 students. Sampling technique with simple random sampling and carried out in August 2017. To determine the effect of the long use of gadgets against eye fatigue is used chi-Square test. The results of this study as many as 58 respondents who long using gadgets and fatigue, 22 respondents used gadget for < 2 hours, 3 respondents used gadget 2-3 hours, 5 respondents used gadgets for >3-4 hours, 4 respondents used gadget for  > 4-6 hours, 23 respondents usedgadget for  >6-8 hours, and 1 respondents used gadget > 8 hours. then. Respondents who long used gadget and  did not experience some eye fatigue 107 respondents, 43 respondents used gadget for < 2 hours, 30 respondents used gadget 2-3 hours, 20 respondents used gadget for > 3-4 hours, 3 respondents used  gadget for > 4-6 hours, 9 respondents used gadget for >6-8 hours, and 2 respondents used gadget > 8 hours. Chi-Square result is taken data P value < 0,00 with  α significance 0,05 so it takes conlusion H1 received if P value <0,05 it means there is an effect of long time usage of gadget against eye fatigue in SMA 1 Zainul Hasan Genggong Probolinggo. Technological innovation is made in the purpose in order to simplify all human affairs hence from the human unknowingly also exposed negative impact of the use of gadgets one of them is eyestrain.
Pengembangan Graph Mining untuk Prediksi Jaringan Kerja Sistem Pembayaran dalam Real Time Gross Settlement Berbasis Clearing House Bukhori, Saiful; Hariadi, Mochamad; Purnama, I Ketut Eddy; Purnomo, Mauridhi Heri
Jurnal Teknik Industri Vol 12, No 1 (2010): JUNE 2010
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (175.978 KB) | DOI: 10.9744/jti.12.1.pp. 33-40

Abstract

This research develops the settlement mechanism in the Real Time Gross Settlement using so called clearing house through a serious game method. In this approach banks are represented as nodes that do the settlement process according to the simple rules. Moreover, the graph mining approach is used for predicting the activity networks on those banks. As the result, for constant nodes indicate that the more the activity networks among banks are available, the more the activity networks can be identified. Furthermore, the smaller the differences among the bank health’s level are, the greater the network activities can be identified. This behavior is a consequence of chosen fixed point assumption.
Sugar Production Forecasting System in PTPN XI Semboro Jember using Autoregressive Integrated Moving Average (ARIMA) Method Putra, Januar Adi; Bukhori, Saiful; Basbeth, Faishal
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1988

Abstract

There is a lot of entrepreneurial competition in the production of goods or services in the world, especially in Indonesia, especially the production of staple goods, namely sugar. The problem that is often faced at Sugar Factory PTPN XI Semboro Jember is the lack of management that is neatly organized and efficient, which makes this company less working optimally. Often there is a lack and excess of sugar production which makes the sugar does not have the maximum value, the sugar has been damaged, and sales at a reduced price because the sugar is not as efficient as the initial product. From these various problems, it can reduce profits from the company. From these problems it can be concluded that the company needs a system that can organize the management of the company, and is able to forecast production in the future. In this research will make a forecasting system using the method of Autoregressive Integrated Moving Average (ARIMA), where this method is divided into three methods, namely the Autoregressive (AR) method, the Moving Average (MA) method, and the Autoregressive Integrated Moving Average (ARIMA) method, which preceded by checking stationary data, and modeling the Autoregressive Integrated Moving Average (ARIMA) method. Forecasting is done using production data for the previous 12 years from the company. The system is made to facilitate management that is less organized and displays predictions for the next production period. The results of this forecasting system are to determine the amount of production each year needed in this company. From the results of the ARIMA method modeling, the right ARIMA method is obtained by the ARIMA / AR (1,0,0), ARIMA / MA (0,0,1), and ARIMA (1,0,1) methods. The test results found that the average value of Mean Absolute Percentage Error (MAPE) in the Autoregressive (AR) method was 17%, the Moving Average (MA) method was 19%, and the Autoregressive Integrated Moving Average (ARIMA) method was 15%.
PENGEMBANGAN SANDPILE MODEL UNTUK MEMPREDIKSI SISTEM YANG DALAM KONDISI CHAOTIC Bukhori, Saiful
Jurnal Informatika Vol 8, No 1 (2007): MAY 2007
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/informatika.8.1.pp. 63-67

Abstract

Chaotic condition or dynamic system (in physics) is a condition that a system always grows. In a system that has chaotic condition, a method to predicti the future condition is needed. This method is important to support the decision for industry or organization.Chaotic condition also has happened in the industry or organizations that will launch a new product. Launching the new product not only influence this new product but also influence the product in the market. Sand pile model is an algorithm that designed wit illustration of sand pile in the real life. In this research a sand pile model for solved the chaotic condition is developed. The result of this research shows that sand pile model algorithm can be used to solve the chaotic condition with pay attention of add inside, rounds and surface parameters. Abstract in Bahasa Indonesia : Keadaan chaotic atau dalam ilmu fisika disebut sebagai dynamic system merupakan kondisi dimana sistem selalu berkembang. Pada sistem yang memiliki kondisi chaotic ini dibutuhkan metode yang cukup rumit untuk memprediksi kondisi yang akan datang, padahal prediksi merupakan kebutuhan yang sangat penting untuk menentukan suatu keputusan yang diambil suatu perusahaan atau organisasi yang berpengaruh pada kondisi yang direncanakan. Keadaan chaotic ini juga terjadi apabila suatu perusahaan atau organisasi akan meluncurkan produk baru atau fitur tambahan dari suatu produk yang sudah ada. Peluncuran suatu produk baru atau fitur tambahan dari produk yang sudah ada tidak hanya mempengaruhi produk yang akan diluncurkan, akan tetapi juga mempengaruhi produk yang sudah ada. Sandpile model merupakan algoritma yang dibuat dengan mengilustrasikan prinsip bagaimana perilaku sandpile pada real-life. Pada penelitian ini dikembangkan sandpile model untuk memecahkan keadaan chaotic pada saat perusahaan atau organisasi akan meluncurkan produk baru atau fitur tambahan dari suatu produk yang sudah ada. Dari hasil penelitian didapatkan bahwa algoritma sandpile model merupakan salah satu algoritma yang dapat digunakan untuk memprediksi sistem yang dalam kondisi chaotic dengan memperhatikan parameter add Inside, parameter rounds dan parameter Surface. Kata kunci: Sandpile model, parameter add inside, parameter rounds, parameter surface.
Pengembangan Ant Algorithm Dengan Hybridization Concept Untuk Clustering Data Bukhori, Saiful
JIK: Jurnal Ilmu Komputer Vol 4, No 1 (2006)
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/komp.v4i1.417

Abstract

Application of ant algorithm for the problem solving with artificial intelligence has grew at full speed. This problem was related to the behavior of ant that was aimed at strove for sustain the ant colony life. Base on the literature survey, the research that was apply the ant algorithm in data mining scope for clustering data has not done . In this research, researcher was design and analysis application of ant algorithm  for clustering data . The algorithm, that was used, was modification and improvement for the algorithm that has developed previously. Ant algorithm that was designed was not used four main parameters, ant desirability, ant frequency, heuristic information (a) and pheromone concentration (b), that used in the previous research[2]. The Software that was designed and implemented in operating system Windows has experimented with data from many sources. The result of the experiment was the true classification in 93,48% - 97,00% range, the false classification in 3,00% - 6,52% range and unclassified 0%. Keyword: data mining, clustering data, ant algorithm, hibridization concept
Sugar Production Forecasting System in PTPN XI Semboro Jember using Autoregressive Integrated Moving Average (ARIMA) Method Januar Adi Putra; Saiful Bukhori; Faishal Basbeth
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1988

Abstract

There is a lot of entrepreneurial competition in the production of goods or services in the world, especially in Indonesia, especially the production of staple goods, namely sugar. The problem that is often faced at Sugar Factory PTPN XI Semboro Jember is the lack of management that is neatly organized and efficient, which makes this company less working optimally. Often there is a lack and excess of sugar production which makes the sugar does not have the maximum value, the sugar has been damaged, and sales at a reduced price because the sugar is not as efficient as the initial product. From these various problems, it can reduce profits from the company. From these problems it can be concluded that the company needs a system that can organize the management of the company, and is able to forecast production in the future. In this research will make a forecasting system using the method of Autoregressive Integrated Moving Average (ARIMA), where this method is divided into three methods, namely the Autoregressive (AR) method, the Moving Average (MA) method, and the Autoregressive Integrated Moving Average (ARIMA) method, which preceded by checking stationary data, and modeling the Autoregressive Integrated Moving Average (ARIMA) method. Forecasting is done using production data for the previous 12 years from the company. The system is made to facilitate management that is less organized and displays predictions for the next production period. The results of this forecasting system are to determine the amount of production each year needed in this company. From the results of the ARIMA method modeling, the right ARIMA method is obtained by the ARIMA / AR (1,0,0), ARIMA / MA (0,0,1), and ARIMA (1,0,1) methods. The test results found that the average value of Mean Absolute Percentage Error (MAPE) in the Autoregressive (AR) method was 17%, the Moving Average (MA) method was 19%, and the Autoregressive Integrated Moving Average (ARIMA) method was 15%.
Co-Authors Al Munawir Basbeth, Faishal Faishal Basbeth Hastungkara, Duhita I Ketut Eddy Purnama Januar Adi Putra Mauridhi Heri Purnomo Mochamad Hariadi Nafolion Nur Rahmat, Nafolion Nur Putra, Januar Adi Retnani, Windi Eka Yulia