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All Journal BERKALA FISIKA Media Statistika Jurnal Masyarakat Informatika MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Semantik Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Register: Jurnal Ilmiah Teknologi Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics AKSIOMA Informatika Mulawarman Jurnal Matematika: MANTIK Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) Journal of Fundamental Mathematics and Applications (JFMA) Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Bayu Surarso
Department Of Mathematics & Graduate School Of Information System
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Physics Other

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Implementasi Metode AHP Dan Promethee Untuk Pemilihan Supplier Chamid, Ahmad Abdul; Surarso, Bayu; Farikhin, Farikhin
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 5, No 2 (2015): Volume 5 Nomor 2 Tahun 2015
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.087 KB) | DOI: 10.21456/vol5iss2pp128-136

Abstract

Selection of suppliers is one of the most important things to meet the needs of the company consistently and at an acceptable cost, decision support system used to select suppliers by identifying suppliers with the highest potential. The object of this study is the drug suppliers. In this study we use four criterias to select suppliers of drugs: drug completeness, price, time delivery, payment or loan term. AHP method is used to calculate the weight of each criterion based on the pharmacist assessment. The weight criterias of the AHP process result is used for the calculation of the alternatives rank. PROMETHEE method used to alternatives calculation analysis that produce alternatives rankings.
Sistem Pendukung Keputusan Evaluasi Pemilihan Pemenang Pengadaan Aset dengan Metode Simple Additive Weighting (SAW) Nugraha, Fajar; Surarso, Bayu; Noranita, Beta
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 2 (2012): Volume 2 Nomor 2 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (531.063 KB) | DOI: 10.21456/vol2iss2pp067-072

Abstract

Procurement of assets by auction requires a decision support in selecting the winning bidder so that decision makers can pick and choose the winner of the auction. This study aims to develop a Decision Support System (DSS), which serves as an aid in decision mak ing in the process  of  evaluating  the  winning  bidder  acquisitions.  In order to  achieve  the  purpose  of  SPK  well  then helped  by  using  one  of  the methods in decision-making that is the method of Simple Additive weighting method (SAW) to evaluate alternatives in the provision of asset  based  decision-making  criteria.  This  method  has  the  advantage  criteria  (benefits)  and  cost  criteria  (cost).  Criteria  advantage (benefit) is used when considering the aspects of decision making maximum profit. While the cost criteria (cost) is the inver se of the attributes of an advantage, in this draft decision will be looking  for a minimal fee. The results may support the decision on the selection of an alternative evaluation of acquisitions winners based on predetermined criteria.Keywords: Acquisitions; Decision support systems; Simple additive weighting
SISTEM PAKAR DIAGNOSA PENYAKIT TELINGA HIDUNG TENGGOROK (THT) DENGAN MENGGUNAKAN METODE INFERENSI BERBASIS SHORT MESSAGE SERVICE (SMS) Indriyawati, Henny; Sugiharto, Aris; Surarso, Bayu
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 3, No 1 (2013): Volume 3 Nomor 1 Tahun 2013
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (372.65 KB) | DOI: 10.21456/vol3iss1pp01-06

Abstract

Public understanding about otolaryng desease (THT) is still insufficient. Most of them medically untrained so that when they experienced thesymptoms of the disease, they might not be able to understand how to overcome the symptoms. It is regrettable when the symptoms could not be handled because of insufficient knowledge. This problem has encouraged the birth of expert system concept. The purpose of the use of the expert system is to help public solve their problems by using the knowledge possessed by the expert system without visiting the experts directly. By the exixtence of this expert system, public are able to detect the presence of the otolaryng disease based on their symptoms. The testing of the system show that the system is capable to diagnose otolaring disease by entering a list of symptoms through short message service. Then the application will process the input data bu using inferensi method and forward chaining reasoning techniques to produce usefull information for the public. The research is result the accuracy level around 87,5%. Keywords : Expert system; Forward chaining; SMS.
Sistem Aplikasi Penyelesaian Masalah Program Linier Standar Maksimal Berbasis Web dengan Keluaran Sesuai Produk Kemasan terkecil Sriwasito, Putut; Surarso, Bayu; Sarwoko, Eko Adi
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 1, No 2 (2011): Volume 1 Nomor 2 Tahun 2011
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (847.888 KB) | DOI: 10.21456/vol1iss2pp99-107

Abstract

Individual or cooperation  as the producer who produces more than one product always has a problem to determine the amount of each product, as well as the smallest packaging used to generate the maximum revenue but still meet the inventory of existing facilities. If the inventory of facilities and functions form a linear function of income then the problem is called the program a maximu m linear case, where all supplies are  limited means of the standard linear program is called maximal. Although the system has available a linear program to solve the problem,  the system is only owned by a limited circle, this system also   does not provide the smallest packaging option.  In general linear programming problem is solved by the simplex method with any number of real output in decimal or fractional format  mix.  Settlement  is  not  operational  because  the  manufacturers  do  not  always  able  to  make  the  smallest  product  packaging   in accordance with the unit on completion, to become operational, the results of this settlement may be rounded according to the smallest package selected. The problem of limited manufactures which have a system of linear program application can be overcome by providing a system similar to a web-based applications. This study compiled a web-based application system to solve a standard linear program that generates the maximum revenue that maximum use PHP software, data entered through the form and then taken by the POST method, then set up a matrix, carried out by iterating between the rows in the matrix operations that met the criteria optimal. By ch oosing the smallest packaging  which is used  0.25 units or 0.50  units, the system  check the number of products that  have  the smallest rounding according to the package selected, then the system prepare and present the inventory and revenue report.Keywords: Simplex metho; The smallest packaging; Web-based
Metode Jaringan Syaraf Tiruan Untuk Prediksi Performa Mahasiswa Pada Pembelajaran Berbasis Problem Based Learning (PBL) Badieah, Badieah; Gernowo, Rachmat; Surarso, Bayu
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 6, No 1 (2016): Volume 6 Nomor 1 Tahun 2016
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (837.567 KB) | DOI: 10.21456/vol6iss1pp46-58

Abstract

In order to improve academic quality in higher education, students’ performance evaluation is becoming important. To prevent increasing failure rate in the course, we need a system that is capable of predicting student’s performance in the end of the course. The research used several factors that are considered to affect students' performance on Problem Based Learning (PBL), such as students’ demography, students’ prior knowledge and group heterogeneity.  The method used in the study was Artificial Neural Network (ANN) with backpropagation training algorithm. Total 8 neurons were used as inputs for ANN which were obtained from gender variable (2 neurons), age variable (1 neuron), students’ average knowledge variable (1 neuron), students’ average skill variable (1 neuron) and group heterogeneity variable (3 neurons). Several different ANN architecture were tested in the study using 2, 7 and 12 hidden neurons respectively. Each architecture was trained using various different training parameters in order to find the best ANN architecture. Dataset used  in the research were obtained from Academic Information System in Faculty of Dentistry Unissula which contained Adult and Elderly Diseases Course’s participants from year 2009 to 2013. The ANN output were numeric values which represented students’ performance in Adult and Elderly Diseases Course. The output of this study is a system that is able to predict the student performance in block course. The result shows that using 7 hidden neurons in the network combining with 0.5 ,0.1 and  9000 for learning rate, momentum and epoch respectively, were the best ANN architechture and parameters in the study. The MSE obtained from validation test was 0,011926 with correlation coefficient (R) 0,796879. The prediction system are expected to help faculty and academic evaluation team to conduct actions to improve student’s academic performance and prevent them from failure in the course. 
Patient Queue Systems in Hospital Using Patient Treatment Time Prediction Algorithm Handayani, Dwi Putri; Mustafid, Mustafid; Surarso, Bayu
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 1, February 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.237 KB) | DOI: 10.22219/kinetik.v5i1.1001

Abstract

Patient Treatment Time Prediction Algorithm was very important to build an outpatient queue system at the hospital. This study aims to build a system of outpatient queues to predict the waiting time of outpatients in the eye clinic at one of Cirebon hospitals. Patient Treatment Time Prediction algorithm was calculated based on historical data or medical records of patients in the hospital with 120 patient data. The Patient Treatment Time Prediction algorithm was trained by improved Random Forest algorithm for each service and a waiting time for each service. Prediction of waiting time for each patient service was obtained by calculating the consumption of patient care time based on patient characteristics. The waiting time for each service predicted by the trained Patient Treatment Time Prediction algorithm is the total waiting time of patients in the queue for each service. This research resulted in a system that can show the time taken by patients in every service available in the eye clinic. Patient time consumption in each service produced varies according to the patient's condition, in this case based on the patient's gender and age. This research provides benefits in terms of improving performance in each department involved, optimizing human resources, and increasing patient satisfaction. This research can be developed for each department in the hospital.
PENDEKATAN VALUE BILANGAN TRAPEZOIDAL FUZZY DALAM METODE MAGNITUDE Aulia, Lathifatul; Irawanto, Bambang; Surarso, Bayu
MATEMATIKA Vol 20, No 2 (2017): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1054.25 KB)

Abstract

Defuzzification is the process to transform fuzzy numbers into real numbers (crisp). There are some defuzzification methods which can be used to confirm the fuzzy numbers. However, different defuzzification methods produce different real numbers (crisp) too. In this paper, we discuss about Magnitude method, that is an approachment method which can be used in the defuzzification of trapezoidal fuzzy numbers. The defuzzification method  in the calculation considers average between the value of trapezoidal fuzzy numbers and the middle point of two defuzzifier trapezoidal fuzzy numbers
Implementasi Metode ANP-PROMETHEE Untuk Pemilihan Supplier (Studi Kasus PT. Lamongan Marine Industry) Wicaksono, Mahad; Surarso, Bayu; Farikhin, Farikhin
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 10, No 1 (2020): Volume 10 Nomor 1 Tahun 2020
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.641 KB) | DOI: 10.21456/vol10iss1pp36-45

Abstract

The selection of suppliers is essential to minimize the cost of procuring raw materials for production. This research is important to do in order to increase company profits and ensure the smooth production process. This study aims to select suppliers of shipbuilding raw materials of PT. LMI based on the best ranking order using the ANP-PROMETHEE method implemented in a decision support system. The variables used are 16 sub criteria and 6 alternatives. The ANP-PROMETHEE method is used because of its advantages in handling multi-criteria assessment based on subjective assumptions from decision makers. Stages of the study began with the ANP method to get the importance of weight then proceed to the calculation with the PROMETHEE method to get an alternative ranking. The results of this study is an application as a Decision Support System (DSS) that can help make supplier selection based on predetermined criteria. From the results of the study it was concluded that the ANP-PROMETHEE method can be implemented and is the right solution for supplier selection, ANP handles the problem of multiple objective decision making so that objectivity is maintained, while PROMETHEE handles the multi attribute decision making problem. Other conclusions are obtained that the PROMETHEE calculation has a more significant influence in determining the final outcome of an alternative ranking than the ANP. An input of ANP value is needed with a long number interval so that the results of the calculation of the Consistency Ratio (CR) approach the CR threshold (0.1) so that the ANP has a significant influence in determining the final outcome of an alternative ranking. The CR number that was tested was 0.0629 and proved unable to change the alternative ranking final results, when the CR number that was tested was 0.0993, it was proven to be able to change the alternative ranking final results.
Fuzzy-AHP MOORA approach for vendor selection applications Al Khoiry, I’tishom; Gernowo, Rahmat; Surarso, Bayu
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8, No 1 (2022): In progress (January)
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2356

Abstract

Vendor selection is a critical activity in order to support the achievement of company success and competitiveness. Significantly, the company has some specific standards in the selection. Therefore, an evaluation is needed to see which vendors match the company's criteria. The purpose of this study is to evaluate and select the proposed vendor in a web-based decision support system (DSS) by using the fuzzy-AHP MOORA approach. The fuzzy-AHP method is used to determine the importance level of the criteria, while the MOORA method is used for alternative ranking. The results showed that vendor 4 has the highest score than other alternatives with a value of 0.2536. Sensitivity analysis showed that the proposed DSS fuzzy-AHP MOORA concept was already solid and suitable for this problem, with a low rate of change.
Kombinasi Synthetic Minority Oversampling Technique (SMOTE) dan Neural Network Backpropagation untuk menangani data tidak seimbang pada prediksi pemakaian alat kontrasepsi implan Mustaqim, Mustaqim; Warsito, Budi; Surarso, Bayu
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 5, No 2 (2019): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v5i2.1705

Abstract

Combination of Synthetic Minority Oversampling Technique (SMOTE) and Backpropagation Neural Network to handle imbalanced class in predicting the use of contraceptive implants  Kegagalan akibat pemakaian alat kontrasepsi implan merupakan terjadinya kehamilan pada wanita saat menggunakan alat kontrasepsi secara benar. Kegagalan pemakaian kontrasepsi implan tahun 2018 secara nasional sejumlah 1.852 pengguna atau 4% dari 41.947 pengguna. Rasio angka kegagalan dan keberhasilan pemakaian kontrasepsi implan yang cenderung tidak seimbang (imbalance class) membuatnya sulit diprediksi. Ketidakseimbangan data terjadi jika jumlah data suatu kelas lebih banyak dari data lain. Kelas mayor merupakan jumlah data yang lebih banyak, sedangkan kelas minor jumlahnya lebih sedikit. Algoritma klasifikasi akan mengalami penurunan performa jika menghadapi kelas yang tidak seimbang. Synthetic Minority Oversampling Technique (SMOTE) digunakan untuk menyeimbangkan data kegagalan pemakaian kontrasepsi implan. SMOTE menghasilkan akurasi yang baik dan efektif daripada metode oversampling lainnya dalam menangani imbalance class karena mengurangi overfitting. Data yang sudah seimbang kemudian diprediksi dengan Neural Network Backpropagation. Sistem prediksi ini digunakan untuk mendeteksi apakah seorang wanita mengalami kehamilan atau tidak jika menggunakan kontrasepsi implan. Penelitian ini menggunakan 300 data, terdiri dari 285 data mayor (tidak hamil) dan 15 data minor (hamil). Dari 300 data dibagi menjadi dua bagian, 270 data latih dan 30 data uji. Dari 270 data latih, terdapat 13 data latih minor dan 257 data latih mayor. Data latih minor pada data latih diduplikasi sebanyak data pada kelas mayor sehingga jumlah data latih menjadi 514, terdiri dari 257 data mayor, 13 data minor asli, dan 244 data minor buatan. Sistem prediksi menghasilkan nilai akurasi sebesar 96,1% pada epoch ke-500 dan 1.000. Implementasi kombinasi SMOTE dan Neural Network Backpropagation terbukti mampu memprediksi pada imbalance class dengan hasil prediksi yang baik.  The failed contraceptive implant is one of the sources of unintended pregnancy in women. The number of users experiencing contraceptive-implant failure in 2018 was 1,852 nationally or 4% out of 41,947 users. The ratio between failure and success rates of contraceptive implant, which tended to be unbalanced (imbalance class), made it difficult to predict. Imbalance class will occur if the amount of data in one class is bigger than that in other classes. Major classes represent a bigger amount of data, while minor classes are smaller ones. The imbalance class will decrease the performance of the classification algorithm. The Synthetic Minority Oversampling Technique (SMOTE) was used to balance the data of the contraceptive implant failures. SMOTE resulted in better and more effective accuracy than other oversampling methods in handling the imbalance class because it reduced overfitting. The balanced data were then predicted using backpropagation neural networks. The prediction system was used to detect if a woman using a contraceptive implant was pregnant or not. This study used 300 data, consisting of 285 major data (not pregnant) and 15 minor data (pregnant). Of 300 data, two groups of data were formed: 270 training data and 30 testing data. Of 270 training data, 13 were minor training data and 257 were major training data. The minor training data in the training data were duplicated as much as the number of data in major classes so that the total training data became 514, consisting of 257 major data, 13 original minor data, and 244 artificial minor data. The prediction system resulted in an accuracy of 96.1% on the 500th and 1,000th epochs. The combination of SMOTE and Backpropagation Neural Network was proven to be able to make a good prediction result in imbalance class.
Co-Authors A. Nafis Haikal Adi Wibowo Agus Subagio Ahmad Abdul Chamid Ahmad Aviv Mahmudi Al Khoiry, I’tishom Ali Bardadi Anak Agung Gede Sugianthara Arief Hidayat Aris Sugiharto Aslam Fatkhudin Aulia, Lathifatul Badieah Assegaf Bambang Irawanto Beta Noranita Budi Warsito Budi Warsito Budi Warsito Dedy Kurniadi Dwi Putri Handayani Eko Adi Sarwoko Eko Sediyono Etna Vianita Fajar Nugraha Farikhin Farikhin Farikhin Frikhin, Farikhin Fra Siskus Dian Arianto Ghufron Ghufron Harjito - Henny Indriyawati Indah Jumawanti I’tishom Al Khoiry Jumawanti, Indah Jumawanti, Indah Laily Rahmania, Laily Lili Rusdiana, Lili LM Fajar Israwan, LM Fajar Lucia Ratnasari M. Haris Qamaruzzaman Maunah, Uun Muhammad Sam'an Mustafid Mustafid Mustaqim Mustaqim Mustaqim Mustaqim, Mustaqim Nitami Lestari Putri Pukky Tetralian Bantining Ngastiti Putut Sriwasito Rachmat Gernowo Ragil Saputra Ragil Saputra Rahmat Gernowo Rezki Kurniati, Rezki Robertus Heri Sulistyo Utomo Saputra, Ragil Siti Alfiatur Rohmaniah St. Budi Waluya Sugiyamto Sugiyamto, Sugiyamto Sulastri Daruni Suryono Suryono Suryono Suryono Suryono, Suryono Susi Hendartie Susilo Hariyanto sutimin sutimin Sutrisno, Sutrisno Sutrisno, Sutrisno T Indriastuti . Wicaksono, Mahad