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Implementasi Protokol Diffie-Hellman Dan Algoritma RC4 Untuk Keamanan Pesan SMS Decky Hendarsyah; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 1 (2011): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.1997

Abstract

Abstrack— SMS now becomes such a need for cellular phone users to communicate to other people. But the cellular phone users do not realize that the sent messages could be intercepted or changed by an unwanted party. Therefore it requires a security in sending an SMS message which is called cryptography. Given limited resources on cellular phone, then the implementation of symmetric cryptographic technique is suitable to meet the security needs of an SMS message. In symmetric cryptography, there is a symmetric key for encryption and decryption process. In order to secure exchange of symmetric keys in public channels is required of a protocol for key exchange.This research implements RC4 symmetric cryptography to encrypt and decrypt messages, while for key exchange is using Diffie-Hellman protocol. In this research, there are modifications to the Diffie-Hellman protocol that is the calculation of the public key and symmetric key to include cellular phone number as authentication. Whereas on a modified RC4 is the key where there is a combination with cellular phone number as authentication and key randomization, and then there are also modifications to the pseudorandom byte generator, encryption and decryption of the RC4 algorithm. The system is constructed using the Java programming language in the platform Micro Edition (J2ME) based MIDP 2.0 and CLDC 1.0.The research found that with the cellular phone number as authentication, key, encryption and decryption process automatically it is able to maintain confidentiality, data integrity, authentication and non-repudiation to the message. Keywords—  Diffie-Hellman, Key exchange, RC4, SMS Secure, Symmetric Cryptography.
Optimasi Cluster Pada Fuzzy C-Means Menggunakan Algoritma Genetika Untuk Menentukan Nilai Akhir Putri Elfa Mas`udia; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 6, No 1 (2012): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.2145

Abstract

AbstrakNilai akhir mahasiswa dapat ditentukan dengan berbagai cara, beberapa diantaranya menggunakan range nilai, standart deviasi, dll. Dalam penelitian ini akan ditawarkan sebuah metode baru untuk menentukan nilai akhir mahasiswa menggunakan clustering dalam hal ini adalah Fuzzy C-Means.Fuzzy C-Means digunakan untuk mengelompokkan sejumlah data dalam beberapa cluster. Tiap data memiliki derajat keanggotaan pada masing-masing cluster antara 0-1 yang diukur melalui fungsi objektif. Pada Fuzzy C-Means ini fungsi objektif diminimumkan menggunakan iterasi yang biasanya terjebak dalam optimum lokal. Algoritma genetika diharapkan dapat menangani masalah tersebut karena algoritma genetika berbasis evolusi yaitu dapat mencari individu terbaik melalui operasi genetika (seleksi, crossover, mutasi) dan dievaluasi berdasarkan nilai fitness. Penelitian ini bertujuan untuk mengoptimasi titik pusat cluster pada Fuzzy C-Means menggunakan algoritma genetika. Hasilnya, bahwa dengan menggunakan GFS didapatkan fungsi objektif yang lebih kecil daripada menggunakan FCM, walaupun membutuhkan waktu yang relative besar. Meskipun selisih antara FCM dan GFS tidak terlalu besar namun hal tersebut berpengaruh pada anggota cluster  Kata kunci— clustering, Fuzzy C-Means, algoritma genetika AbstractThe final grade of students could be determined in various ways, some of which use a range of values, deviation standard, etc. In this study will be offered a new method for determining final grades of students by using the clustering method. In this research the clustering method that will be used is the Fuzzy C-Means (FCM).Fuzzy C-Means is used to group a number of data in multiple clusters. Each data has a degree of membership (the range value of membership degree is 0-1). Membership degree is measured through the objective function. In Fuzzy C-Means,  objective function is minimized by using iteration and is usually trapped in a local optimum. Genetic algorithm is expected to handle these problems. The operation of genetic algorithm based on evolution that is able to find the best individuals through genetic operations (selection, crossover and mutation) and evaluated based on fitness values.This research aims to optimize the cluster center point of FCM by using genetic algorithms. The result of this research shows that by combining the Genetic Algorithm with FCM could obtained a smaller objective function than using FCM, although it takes longer in execution time. Although the difference of objective function that produced by FCM and FCM-Genetic Algorithm combination is not too big each other, but it takes effect on the cluster members. Keywords— clustering, fuzzy c-means, genetic algorithm
Artificial Intelligence on Computer Based Chess Game: An Implementation of Alpha-Beta-Cutoff Search Method Albert Dian Sano; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 1, No 2 (2007): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.2277

Abstract

AbstractA chess program usually consists of three main parts, that is, a move generator to generate all legal moves, an evaluation function to evaluate each move, and a search function to select the best move. The search function is the core of thinking process. The goal of this research is to implement the alpha beta cutoff as a search method. This method is derived from minimax search method and is more optimal than the minimax search method.In minimax, all nodes is searched and compared one by one to get the best value. On the other hand, the alpha beta cut of methd only searches nodes which make contribution to the previous value and cuts off nodes which are not useful. It means that the alpha beta method will not search and compare all nodes. The new node will be better than the previous one and replace the old value with the new one. This will make the alpha beta method requires smaller search time.The proposed method is tested by doing a series of matches between humans and a computer. The results show that the computer has ability to think well and performs a good artcial intelligence though it is very open to be modified and more optimized.Keywords: move generator function, evaluation function, search function, minimax, alpha beta cutoff
An Implementation of Audio Security Using DES Algorithm Abdul Wahid; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 1, No 2 (2007): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.2280

Abstract

AbstractData security is an important problem in computer technology. This paper discusses security system for audio data. This technology is crucial because the multimedia technology has been improved very fast. One of the common audio format forms is wave audio format. The wave format is an uncompressed file format which is for RIFF specification owned by Microsoft. It is used for saving multimedia file. By using DES algorithm, the wave data could be encrypted for hiding information contained in the data. DES algorithm is chosen in this research because DES algorithm is one of the best symmetrical cryptography algorithms and it has been used world wide. This research is expected to give contribution to the audio security concept, especially for audio data security using wave file format.Keywords : audio security, DES algorithm, wave Omar
Purwarupa Sistem Pakar dengan Mamdani Product untuk Menentukan Menu Harian Penderita DM Nur Hasanah; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 7, No 1 (2013): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.3051

Abstract

AbstrakPada 2025 diperkirakan 12,4 juta orang yang mengidap Diabetes Melitus (DM) di Indonesia. Perencanaan makan merupakan salah satu pilar dalam pengelolaan DM. Sistem pakar dapat berfungsi sebagai konsultan yang memberi saran kepada pengguna sekaligus sebagai asisten bagi pakar. Logika fuzzy fleksibel, memiliki kemampuan dalam proses penalaran secara bahasa dan memodelkan fungsi-fungsi matematika yang kompleks. Penelitian ini bertujuan menerapkan metode ketidakpastian logika fuzzy pada purwarupa sistem pakar untuk menentukan menu harian. Manfaat penelitian ini adalah untuk mengetahui keakuratan mesin inferensi Mamdani Product.            Pendekatan basis pengetahuan yang digunakan pada sistem pakar ini adalah dengan Rule-Based Reasoning. Proses inferensi pada sistem pakar menggunakan logika fuzzy dengan mesin inferensi Mamdani Product. Fuzzifier yang digunakan adalah Singleton sedangkan defuzzifier yang digunakan adalah Rata-Rata Terpusat. Penggunaan kombinasi Singleton fuzzifier, mesin inferensi Product dan defuzzifier Rata-Rata Terpusat yang digunakan pada sistem pakar dapat diterapkan untuk domain permasalahan yang dibahas. Meskipun demikian, terdapat kemungkinan Singleton fuzzifier tidak dapat memicu beberapa atau semua aturan. Jika semua aturan tidak dapat dipicu maka tidak dapat disimpulkan kebutuhan kalori hariannya. Kata kunci— sistem pakar, logika fuzzy, mamdani product, diabetes, menu  AbstractIt is predicted that 12.4 million people will suffer from Diabetes Mellitus (DM) in Indonesia in 2025. Menu planning is one of the important aspects in DM management. Expert system can be used as a consultant that gives suggestion to users as well as an assistant for experts. Fuzzy logic is flexible, has the ability in linguistic reasoning and can model complex mathemathical functions. This research aims to implement fuzzy logic uncertainty method into expert sistem prototype to determine diabetic daily menu. The advantage is to find out the accuracy of Mamdani Product inference engine. The knowledge-based approach in this expert system uses Rule-Based Reasoning. The inference process employs fuzzy logic making use of Mamdani Product inference engine. The fuzzifier used is Singleton while defuzzifier is Center Average.            The combination of Singleton fuzzifier, Mamdani Product inference engine and Center Average defuzzifier that is used can be applied in the domain of the problem under discussion. In spite of the case, there is possibility that Singleton fuzzifier can’t trigger some or all of the rules. If all of the rules can’t be triggered then the diabetic daily menu can’t be concluded. Keyword— expert system, fuzzy logic, mamdani product, diabetes, menu
Aplikasi Metode Fuzzy Multi-Attribute Decision Making Berbasis Web dalam Pemilihan Calon Kepala Daerah di Indonesia Muhamad Munawar Yusro; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 7, No 1 (2013): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.3056

Abstract

AbstrakSejak tahun 2005 di Indonesia sudah dilaksanakan pemilihan kepala daerah (pilkada) secara langsung mulai dari pemilihan kepala desa, bupati, walikota sampai dengan gubernur. Majalah SwaSembada menyebutkan ada pemilihan langsung untuk 500 anggota DPR; 33 gubernur, serta sekitar 460 pemilihan untuk jabatan bupati dan wali kota. Dalam penelitian ini dibuat sebuah aplikasi yang mampu mensimulasikan suatu bentuk aplikasi pengambilan keputusan kasus Penentuan Pilihan Calon Kepala Daerah di Indonesia menggunakan metode Fuzzy MADM yang dikembangkan oleh Moon Hyun Joo dan Chang Sun Kang. Sistem ini mempunyai kemampuan menampung input kriteria yang diinginkan dari pengguna, alternatif pasangan calon, dan pada akhirnya mampu memberikan tampilan visual berupa himpunan solusi terbaik dari beberapa alternatif yang diberikan menggunakan metode perangkingan Nilai Total integral. Dari dua kasus pemilihan bupati yang diujikan ternyata hasil perangkingan tidak selalu sama tergantung dari tingkat keoptimisan (a) yang dipakai. Kata kunci— fuzzy, fmadm, pemilihan kepala daerah AbstractSince 2005, in Indonesia the election of regional leader (pilkada) has been held directly start from election of countryside head, regent, mayor up to governor. SwaSembada Magazine mentioned that there are direct elections to elect 500 members of DPR; 33 governors, and also about 460 elections for the occupation of lord mayor and regent. The aim of this research is to create an application which is capable to simulate a Decision Making System in the case of Determination the Choice in the Election of Regional Leader in Indonesia using the Fuzzy MADM method developed by Moon Hyun Joo and Chang Sun Kang. This system is able to accomodate the criterion input as the consumer want, alternative of candidate couple, and finally can give the visual appearance in the form of best solution gathering from some given alternatives using the Nilai Total integral sort method. This system has been implemented in two elections of Regional Leader, and from the test can be concluded that the result of the sort is not always the same. It depends on the optimism storey level (a) that used in the system. Keywords— fuzzy, fmadm, election of regional leader
Perbandingan Algoritma Nearest Neighbour, C4.5 dan LVQ untuk Klasifikasi Kemampuan Mahasiswa Muhammad Fakhrurrifqi; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 7, No 2 (2013): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.3353

Abstract

AbstrakPada pelaksanaan acara perkuliahan atau saat proses balajar mengajar, dosen sering terkendala dengan kemampuan mahasiswa pada suatu matakuliah di satu kelas yang tidak merata. Oleh karena itu dosen terlebih dulu mengetahui kemampuan setiap mahasiswanya dengan salah satu caranya adalah dengan melihat karakteristik setiap mahasiswa dan kemudian dibandingkan dengan mahasiswa-mahasiswa sebelumnya dalam menyelesaian suatu mata kuliah.Pada penelitian ini, akan dilakukan perbandingan tingkat akurasi antara tiga algoritma, yaitu : Nearest Neighbour, C45 dan LVQ, pada kasus klasifikasi kemampuan mahasiswa untuk keperluan penentuan pembagian kelas mahasiswa baru. Selain itu, juga akan diperbandingkan tingkat kecepatan setiap algoritma dalam mendapatkan kelas kasus lama yang paling mirip dengan kasus baru yang dimasukkan.Kesimpulan yang didapatkan setelah sistem dibangun dan kemudian membandingkan ketiga algoritma tersebut adalah algoritma nearest neighbour dapat menghasilkan akurasi tertinggi. Kata kunci— nearest neighbour, c45, jaringan syaraf tiruan, lvq, mahasiswa AbstractDuring the lecture or in teaching-learning process, a lecturer sometimes finds that heterogeneous classroom as the obstacles due to the differences in students’ performances.  Thus, the lecturer should be aware of this phenomenon and one way to overcome this is to find out the characteristics of each student in order to compare them with the previous students while completing their study. In this research, the three algorithms are compared, they are namely; Nearest Neighbor, C45, and LVQ, this is done to classify the students’ ability and to decide the class for the new students. In addition, the speed level of each algorithm is compared by means of getting the nearest previous case study to the new class.    Finally, the ideas coming up as the conclusion for this research is that after the system is developed and those three algorithms are being compared, the result shows that there is nearest neighbour algorithm can produce the highest accuracy. Keywords—nearest neighbour, c45, artificial neural network, LVQ, students’ performances.
Sistem Pendukung Keputusan Penentuan Pemenang Tender Pekerjaan Konstruksi dengan Metode Fuzzy AHP Peggi Sri Astuti; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 8, No 1 (2014): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.3490

Abstract

AbstrakPengambilan keputusan dalam penentuan pemenang tender pekerjaan konstruksi (tidak kompleks) pada pembangunan gedung kuliah Fakultas Ekonomi Univesitas Udayana (UNUD) oleh panitia tender di Bagian Perlengkapan Rektorat UNUD masih dilakukan secara manual (dengan software Microsoft Excel dan Word), sehingga untuk membantu dan mempercepat pengambilan keputusan tersebut (dalam situasi beberapa/banyak peserta tender memenuhi semua evaluasi kriteria dan memiliki harga penawaran terkoreksi terendah yang sama di bawah HPS) maka penelitian ini bertujuan untuk membangun SPK (Sistem Pendukung Keputusan) dengan metode Fuzzy AHP. Versi Fuzzy AHP yang dipakai adalah model Chang (1992) karena memiliki langkah-langkah sederhana dan mudah diaplikasikan pada penelitian ini. Hasil penelitian menunjukkan bahwa SPK yang dibangun menghasilkan perangkingan peserta 1, 2, dan 3 yang sama dengan sistem manual yang ada di Bagian Perlengkapan Rektorat UNUD, meskipun perangkingan 4, 5, 6 yang juga dihasilkan SPK ini tidak ada di sistem manual karena perangkingan 4, 5, 6 tidak memenuhi evaluasi kriteria kualifikasi (syarat untuk lulus tender adalah memenuhi semua evaluasi kriteria). Maka disimpulkan bahwa SPK yang dibangun menghasillkan informasi yang valid.  Kata kunci— sistem pendukung keputusan, fuzzy AHP, tender, pekerjaan konstruksi  AbstractDecision-making to determine the winner of project tender (not complex one) on the construction of college buildings for Economics Faculty of Udayana University by tender committee at the Rectorate Equipment Section of Udayana University, still is carried out manually (applying Microsoft Excel and Word), so to assist and accelerate the decision (in this situation a few/many bidders met all evaluation criteria and have the same lowest bidding price corrected under HPS), this study aims to build a DSS (Decision Supporting System) with Fuzzy AHP method. The applied Fuzzy AHP version is Chang model (1992) because it has simple steps and easy to apply in this study. The results showed that SPK produced ranking method of 1, 2, and 3 that are similar to the existing manual system in Equipment Section of the Rectorate, though the ranking method of 4, 5, 6, which also produced by SPK, is not contained in the manual system because ranking method of 4, 5, 6 did not meet the qualifying criteria evaluation (a requirement for graduation is to fulfill all tender evaluation criteria). It, therefore, comes to conclude that the DSS produce valid information. Keywords— decision supporting system, fuzzy AHP, tender, construction project
Modifikasi Algoritma Genetika untuk Penyelesaian Permasalahan Penjadwalan Pelajaran Sekolah Rahman Erama; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 8, No 2 (2014): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.6539

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AbstrakModifikasi Algoritma Genetika pada penelitian ini dilakukan berdasarkan temuan-temuan para peneliti sebelumnya tentang kelemahan Algoritma Genetika. Temuan-temuan yang dimakasud terkait proses crossover sebagai salah satu tahapan terpenting dalam Algoritma Genetika dinilai tidak menjamin solusi yang lebih baik oleh beberapa peneliti. Berdasarkan temuan-temuan oleh beberapa peneliti sebelumnya, maka penelitian ini akan mencoba memodifikasi Algoritma Genetika dengan mengeliminasi proses crossover yang menjadi inti permasalahan dari beberapa peneliti tersebut. Eliminasi proses crossover ini diharapkan melahirkan algoritma yang lebih efektif sebagai alternative untuk penyelesaian permasalahan khususnya penjadwalan pelajaran sekolah.Tujuan dari penelitian ini adalah Memodifikasi Algoritma Genetika menjadi algoritma alternatif untuk menyelesaikan permasalahan penjadwalan sekolah, sehingga diharapkan terciptanya algoritma alternatif ini bisa menjadi tambahan referensi bagi para peneliti untuk menyelesaikan permasalahan penjadwalan lainnya.Algoritma hasil modifikasi yang mengeliminasi tahapan crossover pada algoritma genetika ini mampu memberikan performa 3,06% lebih baik dibandingkan algoritma genetika sederhana dalam menyelesaikan permasalahan penjadwalan sekolah. Kata kunci—algoritma genetika, penjadwalan sekolah, eliminasi crossover  AbstractModified Genetic Algorithm in this study was based on the findings of previous researchers about the weakness of Genetic Algorithms. crossover as one of the most important stages in the Genetic Algorithms considered not guarantee a better solution by several researchers. Based on the findings by previous researchers, this research will try to modify the genetic algorithm by eliminating crossover2 which is the core problem of several researchers. Elimination crossover is expected to create a more effective algorithm as an alternative to the settlement issue in particular scheduling school.This study is intended to modify the genetic algorithm into an algorithm that is more effective as an alternative to solve the problems of school scheduling. So expect the creation of this alternative algorithm could be an additional resource for researchers to solve other scheduling problems.Modified algorithm that eliminates the crossover phase of the genetic algorithm is able to provide 2,30% better performance than standard genetic algorithm in solving scheduling problems school. Keywords—Genetic Algorithm, timetabling school, eliminate crossover
Penentuan Arsitektur Jaringan Syaraf Tiruan Backpropagation (Bobot Awal dan Bias Awal) Menggunakan Algoritma Genetika Christian Dwi Suhendra; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 9, No 1 (2015): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.6642

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AbstrakKelemahan dari jaringan syaraf tiruan backpropagation adalah sangat lama untuk konvergen dan permasalahan lokal mininum yang membuat jaringan syaraf tiruan (JST) sering terjebak pada lokal minimum. Kombinasi parameter arsiktektur, bobot awal dan bias awal yang baik sangat menentukan kemampuan belajar dari JST untuk mengatasi kelemahan dari JST backpropagation.            Pada penelitian Ini dikembangkan sebuah metode untuk menentukan kombinasi parameter arsitektur, bobot awal dan bias awal. Selama ini kombinasi ini dilakukan dengan mencoba kemungkinan satu per satu, baik kombinasi hidden layer pada architecture maupun bobot awal, dan bias awal. Bobot awal dan bias awal digunakan sebagai parameter dalam perhitungan nilai fitness. Ukuran setiap individu terbaik dilihat dari besarnya jumlah kuadrat galat (sum of squared error = SSE) masing – masing individu, individu dengan SSE terkecil merupakan individu terbaik. Kombinasi parameter arsiktektur, bobot awal dan bias awal yang terbaik akan digunakan sebagai parameter dalam pelatihan JST backpropagation.Hasil dari penelitian ini adalah sebuah solusi alternatif untuk menyelesaikan permasalahan pada pembelajaran backpropagation yang sering mengalami masalah dalam penentuan parameter pembelajaran. Hasil penelitian ini menunjukan bahwa metode algoritma genetika dapat memberikan solusi bagi pembelajaran backpropagation dan memberikan tingkat akurasi yang lebih baik, serta menurunkan lama pembelajaran jika dibandingkan dengan penentuan parameter yang dilakukan secara manual. Kata kunci  Jaringan syaraf tiruan, algoritma genetika, backpropagation, SSE, lokal minimum AbstractThe weakness of back propagation neural network is very slow to converge and local minima issues that makes artificial neural networks (ANN) are often being trapped in a local minima. A good combination between architecture, intial weight and bias are so important to overcome the weakness of backpropagation neural network.This study developed a method to determine the combination parameter of architectur, initial weight and bias. So far, trial and error is commonly used to select the combination of hidden layer, intial weight and bias. Initial weight and bias is used as a parameter in order to evaluate fitness value. Sum of squared error(SSE) is used to determine best individual. individual with the smallest SSE is the best individual. Best combination parameter of architecture, initial weight and bias will be used as a paramater in the backpropagation neural network learning.            The results of this study is an alternative solution to solve the problems on the backpropagation learning that often have problems in determining the parameters of the learning. The result shows genetic algorithm method can provide a solution for backpropagation learning and can improve the accuracy, also reduce long learning when it compared with the parameters were determined manually. Keywords: Artificial neural network, genetic algorithm, backpropagation, SSE, local minima.
Co-Authors Abdul Wahid Adiananda Adiananda Agus Harjoko Ahmad Ashari Ahmad Asharit Aina Musdholifah Aina Musdholifah Albert Dian Sano Anastasya Latubessy Andeka Rocky Tanaamah Andika Kurnia Adi Pradana Andriyani, Widyastuti Anny Kartika Sari Arief Kelik Nugroho, Arief Kelik Azhari Azhari Azhari Azhari Azhari Subanar Bambang Sugiantoro Bambang Sugiantoro Bangun Wijayanto Bernard Renaldy Suteja Budiarsa, Rahmat Christian Dwi Suhendra Clara Hetty Primasari Danang Lelono Decky Hendarsyah Desyandri Desyandri Djemari Mardapi Doni Setyawan E. Elsa Herdiana Murhandarwati Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Edi Winarko Edi Winarko Enny Itje Sela Gede Angga Pradipta, Gede Angga Hananto, Andhika Rafi Hardyanto Soebono Herri Setiawan Herri Setiawan I Made Agus Wirawan I Made Agus Wirawan Ida Ayu Putu Sri Widnyani Istiyanto, Jazi Eko Jazi Eko Istiyanto Jazi Eko Istiyanto Jazi Eko Istiyanto Joan Angelina Widians, Joan Angelina Khabib Mustofa Khairunnisa Khairunnisa Kusrini Kusrini Lausu, Suwandi Lilik Sumaryanti M Mustakim M.Cs S.Kom I Made Agus Wirawan . Moh Edi Wibowo Muhamad Munawar Yusro Muhammad Fakhrurrifqi Muhammad Mukharir Munakhir Mudjosemedi Mustakim, M Nola Ritha NUR HASANAH Peggi Sri Astuti Pratama, Kharis Suryandaru Purba, Susi Eva Maria Purwo Santoso Putri Elfa Mas`udia Rahman Erama Rahmat Budiarsa Ramos Somya Rika Rosnelly Rosa Delima Rosihan Rosihan, Rosihan Santoso, Purwo Silmina, Esi Putri Sri Andayani Sri Hartati Sri Hartati Sri Hartati Sri Hartati Sri Kusrohmaniah, Sri Sri Kusumadewi Sri Mulyana Subahar, Subahar Subanar . Suryo Guritno Suryo Guritno Suryo Guritno Tempola, Firman Tenia Wahyuningrum Wenty Dwi Yuniarti, Wenty Dwi Wibowo, Moh Edi Winarko, Edi Wiwiet Herulambang Yayi Suryo Prabandari