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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) BERKALA FISIKA Media Statistika Jurnal Masyarakat Informatika MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Semantik Jurnal Ilmiah Kursor Jurnal Inovasi Teknologi Pendidikan 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 Jurnal Teknologi dan Sistem Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Matematika: MANTIK Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Sisfokom (Sistem Informasi dan Komputer) Journal of Applied Data Sciences Journal of Soft Computing Exploration Interdisciplinary Social Studies Journal of Fundamental Mathematics and Applications (JFMA) Buletin Abdi Masyarakat (BAM) Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Scientific Journal of Informatics

Bayu Surarso

Department Of Mathematics & Graduate School Of Information System

Author-ID : 2654028

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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PENERAPAN MODEL ADAPTIF DALAM RANCANG BANGUN SISTEM KUIS ONLINE Arief Hidayat; Bayu Surarso; Aris Sugiharto
Semantik Vol 1, No 1 (2011): Prosiding Semantik 2011
Publisher : Semantik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (437.809 KB)

Makalah ini membahas sebuah sistem kuis berbasis web dengan fitur adaptif yang ditambahkan. Sistem kuis adaptif ini menjadi lebih personalisasi karena model pertanyaan yang disajikan secara khusus dirancang bagi siswa sesuai dengan tingkat kemahiran mereka. Siswa akan lebih mengenal kekuatan dan kelemahan dalam proses belajar mereka karena mereka tidak akan menuju ke tingkat kesulitan yang lebihtinggi jika mereka tidak memenuhi nilai yang dipersyaratkan pada tingkat tertentu. Makalah ini fokus pada komponen utama fitur adaptif dan teknik untuk melaksanakan komponen adaptif tersebut. Sebuah studi perbandingan antara sistem adaptif saat ini dilakukan untuk mengidentifikasi komponen adaptif yangditerapkan dan teknik untuk menerapkan komponen adaptif. Hasil studi banding menjadi dasar untuk mengembangkan sistem kuis adaptif ini. Sistem kuis adaptif ini terdiri dari tiga komponen utama: student model, domain model dan adaptation model. Student model menggambarkan pengetahuan siswa, model domain merupakan domain mengajar atau representasi dari student model, sedangkan adaptation model terdiri dari satu sekumpulan aturan yang mendefinisikan aksi pengguna. Teknik stereotype dan overlaymodel diterapkan untuk student model, semantic network diterapkan pada domain model dan 'IF-THEN' rule diterapkan pada adaptation model. Sistem kuis adaptif ini menjadi sebuah sistem penilaian siswa berdasarkan kemampuan, pengetahuan dan preferensi dari masing-masing peserta didik.Kata kunci : Kuis online, adaptif, student model, domain model, adaptation model

Comparison Between Zero Point and Zero Suffix Methods in Fuzzy Transportation Problems Pukky Tetralian Ngastiti; Bayu Surarso; Sutimin Sutimin
Jurnal Matematika MANTIK Vol. 6 No. 1 (2020): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Transportation is discussing the problems of distribution items from a source to a destination with an aim to minimize transportation costs. The problem of fuzzy transport is the cost of transportation, supply, and demand with a quantity of fuzzy. The purpose of the research is a study of a comparison of theories from the zero-point method and the zero-suffix method in determining the optimal solution on cost transportation. Based on the result of the theoretical comparison, it can be concluded that the process of using the zero-suffix method is shorter in determining an optimal solution in 6 steps than that of a zero-point method in 11 steps. For achieving the optimal value shows that for zero-suffix the method of occurrence iteration in the sixth step, but for the zero-point method the iteration occurs in the ninth step. The results in the numerical comparison we conclude the distribution cost using two methods is the same, based on the demand and supply obtained 7 times iteration and 7 items allocation for zero point method, while 6 times iteration and 7 items allocation for zero suffix method.

The Implementations of K-medoids Clustering for Higher Education Accreditation by Evaluation of Davies Bouldin Index Clustering Ghufron Ghufron; Bayu Surarso; Rahmat Gernowo
Jurnal Ilmiah Kursor Vol 10 No 3 (2020)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i3.232

The need for data analysis in tertiary education every semester is needed, this is due to the increasingly large and uncontrolled data, on the other hand generally higher education does not yet have a data warehouse and big data analysis to maintain data quality at tertiary institutions is not easy, especially to estimate the results of university accreditation high, because the data continues to grow and is not controlled, the purpose of this study is to apply k-medoids clustering by applying the calculation of the weighting matrix of higher education accreditation with the data of the last 3 years namely length of study, average GPA, student and lecturer ratio and the number of lecturers according to the study program, so that it can predict accurate cluster results, the results of this study indicate that k-medoid clustering produces good cluster data results with an evaluation value of the Bouldin index davies cluster index of 0.407029478 and is said to be a good cluster result.

Wireless Sensor System for Prediction of Carbon Monoxide Concentration using Fuzzy Time Series Suryono Suryono; Ragil Saputra; Bayu Surarso; Ali Bardadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Carbon monoxide (CO) concentration produced from incomplete material burning affects both work health and safety. A smart system capable of early detection of carbon monoxide (CO) concentration is therefore required. This research develops a carbon monoxide sensor detection capability using a wireless sensor system that transmits data to the web server via internet connection. A semiconductor CO sensor is installed in a remote terminal unit. A computer application is developed for data acquisition and sending via online and in real time to a web server using an internet modem. For a web-based prediction of CO concentration, a Fuzzy Time Series algorithm induced by Pritpal Sing matrix is used. This research uses CO concentration data for two months. The resulting carbon monoxide concentration prediction is displayed in real time on a dashboard. This prediction is for the next day’s forecast. Results show that the Fuzzy Time Series that is induced by Pritpal Sing matrix has an average error of 2.67 %, calculated with its average forecasting error rate (AFER). This error value varies, depending on the number of data and data characteristics.

JEMBATAN PADA GRAF FUZZY INTUITIONISTIC Siti Alfiatur Rohmaniah; Bayu Surarso; Bambang Irawanto
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 1 No 01 (2015): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

An intuitionistic fuzzy graph consist of a couples of node sets V and set of edges E which the sum of degree membership and degree non membership each of nodes and each of edges in closed interval [0,1], the degree membership each of edges is less than or equal with the minimum of degree membership each of related nodes, and degree non membership each of edges is less than or equal with the maximum degree non membership each of related nodes. An intuitionistic fuzzy graph H can be said as intuitionistic fuzzy subgraph from intuitionistic fuzzy graph G if node set V of H is subset of node set V of G and edge set E of H is subset of edge set E of G. If there is an intuitionistic fuzzy graph G with nodes set of V and if each of edge has degree membership and non membership unconstantly, then G has at least one bridge. The theorem is proven to hold if the intuitionistic fuzzy graph has cycle.

Triangular Fuzzy Time Series for Two Factors High-order based on Interval Variations A. Nafis Haikal; Etna Vianita; Muhammad Sam'an; Bayu Surarso; Susilo Hariyanto
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8627

Fuzzy time series (FTS) firstly introduced by Song and Chissom has been developed to forecast such as enrollment data, stock index, air pollution, etc. In forecasting FTS data several authors define universe of discourse using coefficient values with any integer or real number as a substitute. This study focuses on interval variation in order to get better evaluation. Coefficient values analyzed and compared in unequal partition intervals and equal partition intervals with base and triangular fuzzy membership functions applied in two factors high-order. The study implemented in the Shen-hu stock index data. The models evaluated by average forecasting error rate (AFER) and compared with existing methods. AFER value 0.28% for Shen-hu stock index daily data. Based on the result, this research can be used as a reference to determine the better interval and degree membership value in the fuzzy time series.

HASIL PERBANDINGAN METODE IMPROVED NEWTON-RAPHSON BERBASIS DEKOMPOSISI ADOMIAN DAN BEBERAPA METODE KLASIK PADA MASALAH PERSAMAAN NON-LINIER Indah Jumawanti; Sutrisno Sutrisno; Bayu Surarso
Journal of Fundamental Mathematics and Applications (JFMA) Vol 1, No 1 (2018)
Publisher : Diponegoro University

In this paper, we work with ten nonlinear equations to compare a new method in nonlinear equation solving, Improved Newton-Raphson based on Adomian Decomposition method (INR-ADM) that consisting of two types called INR-ADM 1 and INR-ADM 2. The difference between INR-ADM 1 and INR-ADM 2 is on the iteration formula form. From our results, it was showed that INR-ADM 1 and INR-ADM 2 are not always better than classic Newton-Raphson method in term of the iteration number. However, if INR-ADM 1 and INR-ADM 2 are compared to Regula False method and Secant method, they are always better i.e. they had fewer number of iteration. The INR-ADM 1 and INR-ADM 2 had shorter computational time than Regula False method. Furthermore, the computational time of INR-ADM 1 and INR-ADM 2 cannot be claimed that they had shorter or longer if they are compared to Newton-Raphson method and Secant method.

[RETRACTED] COMBINATION OF SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE (SMOTE) AND BACKPROPAGATION NEURAL NETWORK TO CONTRACEPTIVE IUD PREDICTION Mustaqim Mustaqim; Budi Warsito; Bayu Surarso
MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

[RETRACTED] Data imbalance occurs when the amount of data in a class is more than other data. The majority class is more data, while the minority class is fewer. Imbalance class will decrease the performance of the classification algorithm. Data on IUD contraceptive use is imbalanced data. National IUD failure in 2018 was 959 or 3.5% from 27.400 users. Synthetic minority oversampling technique (SMOTE) is used to balance data on IUD failure. Balanced data is then predicted with neural networks. The system is for predicting someone when using IUD whether they have a pregnancy or not. This study uses 250 data with 235 major data (not pregnant) and 15 minor data (pregnant). From 250 data divided into two parts, 225 training and 25 testing data. Minority class on training data will be duplicated to 1524%, so that the amount of minority data become balanced with the majority data. The results of predictive with an accuracy rate of 99.9% at 1000 epoch.

Modifikasi Metode Fuzzy C-Means untuk Klasifikasi Citra Daun Padi Fra Siskus Dian Arianto; Adi Wibowo; Bayu Surarso
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 17, No 1 (2022): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jim.v17i1.6068

Metode Fuzzy C-means merupakan algoritma pembelajaran tidak terawasi yang menggunakan derajat keanggotaan untuk menentukan cluster tiap-tiap titik data. Proses pembelajaran yang tidak terawasi menjadi keunggulan untuk dapat diterapkan pada gambar yang terdapat noise. Dilakukan modifikasi terhadap metode Fuzzy C-means yaitu dengan melakukan penentuan dan perubahan matriks partisi menggunakan fungsi keanggotaan fuzzy untuk mendapatkan proses pembelajaran dan akurasi cluster. Penelitian ini bertujuan untuk mendapatkan model terbaik klasifikasi warna daun padi (Oryza Sativa) berdasarkan citra digital dengan menggunakan modifikasi metode fuzzy c-means yang diterapkan untuk klasifikasi. Data citra daun padi yang digunakan sebanyak citra dengan ukuran dimana data dibagi menjadi data latih citra untuk mendapatkan model dan 160 citra digunakan untuk pengujian model klasifikasi. Data citra diubah menjadi matriks Red, Green, Blue (RGB) yang kemudian ditransformasi menjadi matriks fuzzy. Penetapan nilai elemen-elemen matriks partisi dilakukan dengan membangkitkan bilangan random berdistribusi Uniform yang kemudian diubah menjadi matriks fuzzy. Model fuzzy c-means terbaik untuk klasifikasi diperoleh dengan menggunakan pusat cluster dari proses pembelajaran pada 9 percobaan terhadap parameter pangkat (). Diperoleh model terbaik modifikasi metode fuzzy c-means untuk klasifikasi pada percobaan parameter pangkat () sama dengan 2 dengan accuracy (ACC) 71%, specificity (SPC) 76%, sensitivity (TPR) 54%, positive predictive value (PPV) 51%, dan negative predictive value (NPV) 85%.

Sistem Penilaian Jawaban Singkat Otomatis pada Ujian Online Berbasis Komputer Menggunakan Algoritma Cosine Similarity Dedy Kurniadi; Rahmat Gernowo; Bayu Surarso; Adi Wibowo; Budi Warsito
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.66934

Penggunaan teknologi di bidang pendidikan sekarang ini sedang trending ke arah penilaian secara otomatis, namun penilaian secara otomatis ini memiliki permasalahan yaitu belum bisa mengkoreksi jawaban teks singkat secara otomatis, selain itu pada saat ini juga belum tersedia platform yang bisa mengkoreksi jawaban singkat secara otomatis, penilaian jawaban teks singkat ini membutuhkan waktu koreksi yang lama dan hasil penilaian yang tidak konsisten jika koreksi dilakukan oleh manusia, pada penelitian ini diusulkan sistem yang mampu mengkoreksi ujian peserta didik pada bagian jawaban singkat secara otomatis atau disebut dengan Automated Short Answer Grading (ASAG) dengan menggunakan metode cosine similarity, tahapan yang dilakukan adalah melakukan ekstraksi pada dua variabel inputan yaitu teks pada jawaban peserta didik dan teks pada kunci jawaban yang dilakukan dengan ekstraksi teks casefolding, tokenizing, stopword removal, setelah tahapan tersebut dilakukan kemudian dihitung nilai similarity antara kunci jawaban ujian dengan jawaban peserta didik apakah jawaban peserta didik sama dengan kunci jawaban atau tidak, dengan menggunakan skor yang dinilai otomatis menggunakan sistem, dihasilkan similarity antara jawaban peserta didik dengan kunci jawaban rata-rata sebesar 85,4%, untuk menguji korelasi koreksi jawaban peserta didik dengan sistem dan koreksi yang dilakukan oleh manusia maka dilakukan uji korelasi antara hasil penilian yang dilakukan oleh sistem dengan hasil penilaian yang dilakukan oleh manusia (instruktur) dengan menggunakan kendall’s w value menghasilkan nilai w antara instruktur 1 dengan sistem sebesar 0,885 dan instruktur 2 dengan sistem sebesar 0,883 dengan nilai chi square sebesar 135,4 dan 133,8 dengan p sebesar 0,0001, hasil tersebut menunjukkan ASAG memiliki korelasi yang tinggi dan sistem ASAG ini bisa melakukan penilaian secara otomatis.

Co-Authors A. Nafis Haikal Adi Wibowo Adi Wibowo Agus Subagio Ahmad Abdul Chamid Ahmad Aviv Mahmudi Aldi Setiawan, Aldi Alfajri, Willy Bima Ali Bardadi Anak Agung Gede Sugianthara Andi Setiabudi, Nur Antariksa, Muhammad Deagama Surya Arief Hidayat Aris Puji Widodo Aris Sugiharto Aslam Fatkhudin Aulia, Lathifatul Badieah Assegaf Bambang Irawanto Beta Noranita Budi Warsito Budi Warsito Budi Warsito Che Pee, Ahmad Naim Dedy Kurniadi Dinar Mutiara Kusumo Nugraheni Dwi Putri Handayani Dwiyanasari, Desty Edwin Setiawan Eko Adi Sarwoko Eko Sediyono Etna Vianita Fajar Nugraha Fra Siskus Dian Arianto Ghufron Ghufron Harjito - Henny Indriyawati Imam Tahyudin Indah Jumawanti Irfan Santiko I’tishom Al Khoiry Jatmiko Endro Suseno Jumawanti, Indah Jumawanti, Indah Juwanda, Farikhin Khoerunnisa, Selvi Fitria Khusnah, Miftakhul Laily Rahmania, Laily Lili Rusdiana, Lili LM Fajar Israwan, LM Fajar Lucia Ratnasari Masruroh, Fitriana Maunah, Uun Migunani Migunani Muhammad Haris Qamaruzzaman Muhammad Nasrullah Muhammad Sam'an Mustafid Mustafid Mustaqim Mustaqim Mustaqim Mustaqim, Mustaqim Nugraheni, Dinar Oky Dwi Nurhayati Pukky Tetralian Bantining Ngastiti Puspita, Yuanita Candra Putri, Aina Latifa Riyana Putri, Nitami Lestari Putut Sriwasito Rachmat Gernowo Ragil Saputra Ragil Saputra Rahmat Gernowo Rahmawati, Nurhita Ratri Wulandari Rezki Kurniati, Rezki Robertus Heri Sulistyo Utomo Saputra, Ragil Satriani, Rineka Brylian Akbar Siti Alfiatur Rohmaniah St. Budi Waluya Sugiyamto Sugiyamto, Sugiyamto Sulastri Daruni Sulistiyo, Budi Suryono Suryono Suryono Suryono Suryono, Suryono Susi Hendartie Susilo Hariyanto sutimin sutimin Sutrisno, Sutrisno Sutrisno, Sutrisno Syibli, Mohammad T Indriastuti . Titi Udjiani SRRM Tri Retnaningsih Soeprobowati Uswatun Khasanah Vianita, Etna Wahyul Amien Syafei Wicaksono, Mahad Zainal Arifin Hasibuan

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