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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Perfecting a Video Game with Game Metrics Journal of Enviromental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Habitat Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JAST : Jurnal Aplikasi Sains dan Teknologi
Arief Andy Soebroto
Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Other

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Sistem Pendukung Keputusan Seleksi Beasiswa Ppa Dan Bbm Menggunakan Metode Fuzzy Ahp Rekyan Regasari, Fauziah Mayasari Iskandar, Arief Andy Soebroto,
SMATIKA Vol 3, No 1 (2013)
Publisher : SMATIKA

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Abstract

Each institute of education like university offered scholarships for students who have a good achievement and lack of financial. To assured that Academic Achievement Scholarship (PPA) and StudentLearning Assistance (BBM) delivered to the right person, we need a comprehensive system to make decisions. The selection process of PPA and BBM scholarships is a problem which recently discussed by students because there  is  a  probability that  the  distribution is  not  well  targeted,  the  time  is  overdue,  and  the  amount  is inappropriate. We can use Fuzzy AHP method for this Decision Support System (DSS). AHP model can represent a  problem into a hierarchy with levels: objectives, criteria, and alternatives and the fuzzy logic is used to minimize uncertainty value in AHP with crisp value. The analysis of software requirement system consists of actor’s identification and requirement list.Implementation of web-based system use HTML and PHP programming language that integrated with MySQL databases. The testing used are validation (Black Box) testing and accuracy testing. Black Box testing result is 100% which indicates that the functionality of the system fulfill the system requirements list. Accuracy testing result is 80% for PPA and 33.33% for BBM which indicate the DSS is running well with Fuzzy AHP method.
Pengembangan Sistem Pakar Untuk Memprediksi Kelas Kemampuan Lahan Pertanian Issa Arwani, Sativandi Putra, Arief Andy Soebroto,
SMATIKA Vol 3, No 1 (2013)
Publisher : SMATIKA

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Abstract

Sistem Pakar Kelas Kemampuan Lahan Pertanian adalah perangkat lunak yang dapat digunakan untuk membantu dalam memprediksi delapan macam kelas kemampuan lahan pertanian melalui berbagai macam faktor  pembatas lahan  dan  kriteria  lahan  serta  memberikan keterangan tentang  perlunya  mengambil tindakan  atau   rekomendasi   lahan   yang   lebih   baik.   Sistem   pakar   dibangun berdasarkan   basis pengetahuan dan mesin inferensi.  Basis  pengetahuan direpresentasikan oleh  dua  elemen  dasar  yaitu  fakta  dan  aturan.  Basis pengetahuan menggunakan data hasil pertimbangan pakar.     Mesin inferensi pada sistem pakar yang dibuat  menggunakan    metode    penalaran  Forward    Chaining.    Perangkat    lunak    yang    dibuat dikembangkan  dengan bahasa  pemrograman  PHP berbasis  Framework  Codeigniter  dan  mengadopsi pola arsitektur Model-View- Controller.Sistem Pakar Kelas Kemampuan Lahan Pertanian dikembangkan dengan metode Component-Based Software Engineering. Fungsi-fungsi sistem ini diuji menggunakan white-box testing, black-box testing, dan pengujian akurasi. Prediksi kelas kemampuan lahan pertanian dibandingkan dengan prediksi kelas kemampuan   lahan   pertanian   oleh   seorang   pakar.   Hasil   perbandingan   ini merepresentasikan keakuratan prediksi sistem pakar. Keakuratan prediksi kelas kemampuan lahan pertanian mencapai 100%.
Akreditasi Program Studi Sarjana Menggunakan Metode Analytic Hierarchy Process (Ahp) Rekyan Regasari, Niken Hendrakusma Wardani, Arief Andy Soebroto,
SMATIKA Vol 3, No 1 (2013)
Publisher : SMATIKA

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Abstract

Setiap program studi sarjana dari perguruan tinggi negeri maupun swasta yang ada di Indonesia memerlukan penilaian akreditasi sebagai kendali mutu dan akuntabilitas publik institusi. Pencapaian predikat terakreditasi A  dari  Badan  Akreditasi  Nasional  Perguruan  Tinggi  (BAN-PT)  bukanlah  hal  yang  mudah dilakukan dalam waktu singkat. Keterbatasan sumber daya manusia, dana, waktu dan penilaian BAN-PT dijadikan sebagai pertimbangan ketua program studi (kaprodi) untuk perbaikan akreditasi. Sistem Pendukung Keputusan  (SPK)  dibuat  untuk  membantu  kaprodi  dalam  menyusun  prioritas  perbaikan  tujuh  standar akreditasi berdasarkan pertimbangan kondisi program studi. Metode Analytic Hierarchy Process (AHP) merupakan salah satu metode dalam Multiple Criteria Decision Making (MCDM) yang mampu menguraikan sebuah masalah ke bentuk hierarki dengan level: tujuan, kriteria, dan alternatif [1].Perangkat lunak yang dikembangkan menggunakan bahasa pemrograman PHP dan HTML. Hasil pengujian fungsionalitas terhadap 12 test case dengan metode black-box testing menunjukkan bahwa sistem ini100% valid untuk memenuhi daftar kebutuhan sistem. Pengujian proses perankingan dan User Acceptance Test (UAT) dilakukan terhadap 7 objek uji. Hasilnya menunjukkan bahwa sistem dapat diterima dan  bekerja dengan baik   untuk   menentukan   prioritas   perbaikan   standar   akreditasi   secara   ideal   (menggunakan perhitungan matematis metode AHP) berdasarkan bobot kriteria dan kondisi program studi.
Prediksi Tinggi Muka Air (TMA) Untuk Deteksi Dini Bencana Banjir Menggunakan SVR-TVIWPSO Soebroto, Arief Andy; Cholissodin, Imam; Wihandika, Randy Cahya; Frestantiya, Maria Tenika; Arief, Ziya El
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2, No 2 (2015)
Publisher : Fakultas Ilmu Komputer

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Abstract

Abstrak Banjir merupakan salah satu jenis bencana alam yang tidak dapat diprediksi kedatangannya, salah satu penyebabnya adalah adanya hujan yang terus – menerus(dari peristiwa alam). Faktor penyebab banjir dari segi meteorologi yaitu curah hujan yang tinggi dan air laut yang sedang pasang sehingga mengakibatkan tinggi permukaan air meningkat. Analisis terhadap data curah hujan serta tinggi permukaan air setiap periodenya dirasa masih belum dapat menyelesaikan permasalahan yang ada. Oleh karena itu, pada penelitian ini diusulkan teknik integrasi metode Time Variant Inertia Weight Particle Swarm Optimization(TVIWPSO) dan Support Vector Regression(SVR). Implementasi memadukan metode Regresi yaitu SVR untuk forecasting TMA, sedangkan TVIWPSO digunakan untuk mengoptimalisasi parameter – parameter yang digunakan di dalam SVR untuk memperoleh kinerja yang maksimal dan hasil yang akurat. Harapannya sistem ini akan dapat membantu mengatasi permasalahan untuk pendeteksian dini bencana banjir karena faktor cuaca yang tidak menentu. Hasil pengujian yang didapat dari 10 data bulanan yang berbeda menunjukkan bahwa didapatkan nilai error terkecil sebesar 0.00755 dengan menggunakan Mean Absolute Error untuk data Juni 2007 dengan menggunakan integrasi metode SVR-TVIWPSO. Kata Kunci : Support Vector Regression, Tinggi Muka Air, Time Variant Inertia Weight Particle Swarm Optimization. Abstract Flood is one type of natural disaster that can not be predicted its arrival, one reason is the rain that constantly occurs (from natural events). Factors that cause flooding in terms of meteorology are high rainfall and sea water was high, resulting in high water level increases. Analysis of rainfall data and water level in each period it is still not able to solve existing problems. Therefore, in this study the method proposed integration techniques Time Variant Inertia Weight Particle Swarm Optimization (TVIWPSO) and Support Vector Regression (SVR). Implementation combines regression method for forecasting TMA is SVR, while TVIWPSO used to optimize parameters that used in the SVR to obtain maximum performance and accurate results. Hope this system will be able to help solve the problems for the early detection of floods due to erratic weather. The result of forecasting experiment in water level forecasting from 10 monthly different data show that the smallest error rate is amount to 0.00755 using Mean Absolute Error for June 2007 with the integration method SVR-TVIWPSO. Keywords: Support Vector Regression, water level, Time Variant Inertia Weight Particle Swarm Optimization.
PEMODELAN SISTEM PENDUKUNG KEPUTUSAN PROMOSI JABATAN PADA PERUSAHAAN ASURANSI DENGAN MENGGUNAKANMETODE FUZZY MAMDANI soebroto, arief andy
MATICS Vol 6, No 2 (2014): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (451.604 KB) | DOI: 10.18860/mat.v6i2.2600

Abstract

Promotion of professionalism is the recognition given to employees on company performance. Promotion can increase employee job satisfaction and effectiveness. Promotion opportunities can make employees feel valued, cared for, needed and recognized his ability by the company. One of the positive impact of the promotion is to produce a high loyalty to the company. However, in deciding the promotion of optimum accuracy is needed in the selection of employees eligible to get it. Factors that influence the decision of the promotion criteria should be considered as working time, discipline, teamwork, performance and appearance. The proposed research model is a decision support system in the promotion of insurance companies using fuzzy method mamdani. The method used for calculating the value of each criterion in determining preferences. The results of these calculations a reference manager in determining which employees are given proper promotion. Keywords : Decision support systems, Promotion of professionalism, Mamdani Fuzzy.
SISTEM PAKAR TES KEPRIBADIAN PAPI KOSTICK UNTUK SELEKSI DAN PENEMPATAN TENAGA KERJA Cemani, Dwi Puri; Soebroto, Arief Andy; Wicaksono, Satrio Agung
MATICS MATICS (Vol 5, No 3
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (620.628 KB) | DOI: 10.18860/mat.v0i0.2428

Abstract

Company commonly in doing the  selection or the placement of the employees by using curriculum vitae (CV) or application form to see the applicant’s ability. The weakness, although the CV writer who is capable who is able until the level of  interview is not a guarantee that he is the right person who is needed by the company. The company can see the adjustment between the aplicant with the working through personality test. Kostick PAPI method is implemented in the expert system to evaluate behavioral and individuals working way in the relation to the working situation. The expert system is implemented in a web-based. The testing used are validation testing (Black Box testing) and accuracy testing the of expert systems. The result of Black Box testing   is 100% showing of  functionality system works well as requirements list. The result of accuracy testing is 96,49% showing of an expert system functions well as Kostick PAPI method.  
SISTEM RESERVASI TIKET BUS DI TERMINAL ARJOSARI MALANG Wirawan, Surya; Soebroto, Arief Andy; Aknuranda, Ismiarta
MATICS MATICS (Vol 5, No 3
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (610.552 KB) | DOI: 10.18860/mat.v0i0.2429

Abstract

Bus Ticket Reservation System is an application that can be used to help booking bus tickets and the buyer will get a report via SMS Gateway. The reservation system is made by conducting field studies in Arjosari Bus Station Malang. This system uses SMS Gateway to send the report to the buyer after booking bus tickets online. SMS Gateway on this application serves as a liaison which delays sms between External Short Message entitiy (ESME) and Short Message Service Center (SMSC) and so does in reserve.The reservation system made is developed with the PHP programming language and has a prototype system pattern. System functions were tested using the validation testing, performance testing, and usability testing. The results percentage of responses usability testing is 67.7%. This shows that Ticket Reservation System at Arjosari Bus Station can be used well enough.  
Integration Method of Local-global SVR and Parallel Time Variant PSO in Water Level Forecasting for Flood Early Warning System Arief Andy Soebroto; Imam Cholissodin; Maria Tenika Frestantiya; Ziya El Arief
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.6772

Abstract

Flood is one type of natural disaster that can’t be predicted, one of the main causes of flooding is the continuous rain (natural events). In terms of meteorology, the cause of flood is come from high rainfall and the high tide of the sea, resulting in increased the water level. Rainfall and water level analysis in each period, still not able to solve the existing problems. Therefore in this study, the proposed integration method of Parallel Time Variant PSO (PTVPSO) and Local-Global Support Vector Regression (SVR) is used to forecast water level. Implementation in this study combine SVR as regression method for forecast the water level, Local-Global concept take the role for the minimization for the computing time, while PTVPSO used in the SVR to obtain maximum performance and higher accurate result by optimize the parameters of SVR. Hopefully this system will be able to solve the existing problems for flood early warning system due to erratic weather.
Audit System Development for Government Institution Documents Using Stream Deep Learning to Support Smart Governance Imam Cholissodin; Arief Andy Soebroto; Sutrisno Sutrisno
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1246.411 KB) | DOI: 10.25126/jitecs.20194173

Abstract

Document audit system is a means of evaluating documents on the results of delivering information, administrative documentary evidence in the form of texts or others. Currently, these activities become easier with the presence of computer technology, smartphones, and the internet. One of the examples is the documents created by various government institutions whether local, city and central government. The instance is online-published documents that are shaded by certain government institutions. Before the documents are published or used as an archive or authentic evidence for reporting or auditing activities, the documents must go through the editing stage to correct if there are errors and deficiencies such as spelling errors or incomplete information. In the editing process, however, a person may not be able to escape from making mistakes that result in the existence of writing errors after the editing process before the submission. Word spelling mistakes can change the meaning of the conveyed knowledge and cause misunderstanding of information to the readers, especially for assessors or the audit team. Based on the problem, the researcher intends to assist the work of the audit preparation team in document analysis by proposing a system capable of detecting word spelling errors using the Dictionary Lookup method from Information Retrieval (IR) and Natural Language Processing (NLP) science combined with Stream Deep Learning algorithms. Dictionary Lookup method is considered effective in determining the spelling of words that are true or false based on Lexical Resource. In addition, String Matching method that has been developed can correct word-writing errors correctly and quickly.Keywords: spelling mistake detection, dictionary lookup, audit of government institution documents, stream deep learning
Comparison of Regression, Support Vector Regression (SVR), and SVR-Particle Swarm Optimization (PSO) for Rainfall Forecasting Fendy Yulianto; Wayan Firdaus Mahmudy; Arief Andy Soebroto
Journal of Information Technology and Computer Science Vol. 5 No. 3: Desember 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1148.218 KB) | DOI: 10.25126/jitecs.20205374

Abstract

Rainfall is one of the factors that influence climate change in an area and is very difficult to predict, while rainfall information is very important for the community. Forecasting can be done using existing historical data with the help of mathematical computing in modeling. The Support Vector Regression (SVR) method is one method that can be used to predict non-linear rainfall data using a regression function. In calculations using the regression function, choosing the right SVR parameters is needed to produce forecasting with high accuracy. Particle Swarm Optimization (PSO) method is one method that can be used to optimize the parameters of the existing SVR method, so that it will produce SVR parameter values with high accuracy. Forecasting with rainfall data in Poncokusumo region using SVR-PSO has a performance evaluation value that refers to the value of Root Mean Square Error (RMSE). There are several Kernels that will be used in predicting rainfall using Regression, SVR, and SVR-PSO with Linear Kernels, Gaussian RBF Kernels, ANOVA RBF Kernels. The results of the performance evaluation values obtained by referring to the RMSE value for Regression is 56,098, SVR is 88,426, SVR-PSO method with Linear Kernel is 7.998, SVR-PSO method with Gaussian RBF Kernel is 27.172, and SVR-PSO method with ANOVA RBF Kernel is 2.193. Based on research that has been done, ANOVA RBF Kernel is a good Kernel on the SVR-PSO method for use in rainfall forecasting, because it has the best forecasting accuracy with the smallest RMSE value.
Co-Authors Achmad Arwan Achmad Ridok Adam Hendra Brata Ade Wija Nugraha Adi Setyo Nugroho Admaja Dwi Herlambang Agi Putra Kharisma Ahmad Afif Supianto Ahmad Mustafirudin Ahmad Shofi Nurur Rizal Aizul Faiz Iswafaza Alysha Ghea Arliana Amira Ibtisama Ana Kusuma Ardani Andreas Tommy Christiawan Andri Wijaya Kusuma Asrul Syawal Austenita Pasca Aisyah Bambang Gunadi Candra Dewi Candra Dewi Canny Amerilyse Caesar Catur Ari Setianto Dama Yuliana Deby Putri Indraswari Denny Sagita Rusdianto Destyana Ellingga Pratiwi Dhea Azahria Mawarni Dian Eka Ratnawati Djoko Pramono Dwi Cindy Herta Turnip Dwi Puri Cemani Edy Santoso Eka Miyahil Uyun Eko Ari Setijono Marhendraputro Eko Arisetijono Elza Fadli Hadimulyo Enggar Septrinas Enggarsita Auliasin Eugenius Yosep Korsan N Evi Irhamillah Azza Faisal Roufa Rohman Faizatul Amalia Fajar Pradana Fauziah Mayasari Iskandar Febrianita Indah Perwitasari Fendy Yulianto Ferdy Wahyurianto Fildzah Amalia Galuh Mazenda Guruh Prayogi Willis Putra Habib Yafi Ardi Hastian Bayu Herman Syantoso Himawan Sutanto I Gede Adi Brahman Nugraha I Putu Bagus Arya Pradnyana Ibrahim Kusuma Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indra Ekaristio P Indriana Candra Dewi Indriati Indriati Ishak Panangian Sinaga Ismiarta Aknuranda Issa Arwani Issa Arwani Karmia Larissa Br Pandia Khoifah Inda Maula Khrisna Widhi Dewanto Krisna Wahyu Aji Kusuma Lailatul Rizqi Ramadhani Lailil Muflikhah Laode Muhamad Fauzan Latifah Hanum Mahdi Fiqia Hafis Maria Tenika Frestantiya Maria Tenika Frestantiya Maria Tenika Frestantiya, Maria Tenika Maya Febrianita Mohammad Imron Maulana Muh Arif Rahman Muhammad Iqbal Kurniawan Muhammad Rois Al Haqq Muhammad Rouzikin Annur Muhammad Tanzil Furqon Muhammad Tanzil Furqon Muhammad Tanzil Furqon Muhammad Taruna Praja Utama Mutia Ayu Sabrina Nadya Rahmasari Nadya Sylviani Niftah Fatiha Armin Niken Hendrakusma Wardani Nizar Rahman Kusworo Nuriya Fadilah Nurudin Santoso Nurudin Santoso Nurul Faizah Nurul Faridah Nurul Hidayat NURUL HIDAYAT Nurul Hidayat Nurul Hidayat Odhia Yustika Putri Priyambadha, Bayu Randy Cahya Wihandika Raymond Gunito Farandy Junior Rekyan Regasari Restia Dwi Oktavianing Tyas Reynald Daffa Pahlevi Ridwan Fajar Widodo Rio Andika Dwiki Adhi Putra Rio Arifando Risda Nur Ainum Riski Ida Agustiyan Risqi Nur Ifansyah Rivaldy Raihan Syams Rizal Setya Perdana Sativandi Putra Satrio Agung Wicaksono Stefan Levianto Surya Wirawan Sutrisno Sutrisno Sutrisno Sutrisno Sutrisno Sutrisno Teddy Syach Pratama Thareq Ibrahim Tiara Rossa Diassananda Tryse Rezza Biantong Vicky Virdus Vivien Fathuroya Wayan Firdaus Mahmudy Welly Purnomo Wildan Ziaulhaq Wildan Ziaulhaq Wildansyah Maulana Rahmat Yearra Taufan Ardy Rinaldy Yusril Iszha Eginata Zaien Bin Umar Alaydrus Ziya El Arief Ziya El Arief Ziya El Arief, Ziya El