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INDONESIA
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Published by Universitas Gadjah Mada
ISSN : 19781520     EISSN : 24607258     DOI : https://doi.org/10.22146/ijccs
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can be built to industrial applications. The topics include but not limited to : fuzzy logic, neural network, genetic algorithm and evolutionary computation, hybrid systems, adaptation and learning systems, distributed intelligence systems, network systems, human interface, biologically inspired evolutionary system, artificial life and industrial applications. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 386 Documents
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Sistem Pendukung Keputusan Pengalokasian Spare Part Rita Wiryasaputra; Sri Hartati
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.2037

Abstract

AbstrakEra informasi yang semakin berkembang mempengaruhi lingkungan bisnis. Pengaruhnya dapat dilihat pada proses pengambilan keputusan. Proses pengambilan keputusan terhadap sejumlah alternatif dan sejumlah tujuan diselesaikan dengan sebuah sistem. Sistem  yang bermodelkan Multi Attribute Decision Making (MADM) dan Multi Objective Decision Making (MODM). Model MODM digunakan untuk menyelesaikan perancangan alternatif terbaik dan model MADM digunakan untuk menyelesaikan penyeleksian terhadap beberapa alternatif dalam jumlah yang terbatas. Salah satu pendekatan model MADM adalah TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Konsep utama TOPSIS adalah alternatif preferensi terbaik memiliki jarak terpendek dari solusi ideal positif dan memiliki jarak terjauh dari solusi ideal negatif. Hasil metode TOPSIS adalah perankingan terhadap sejumlah alternatif. Salah satu masukan dari metode TOPSIS adalah nilai pembobotan kriteria. Nilai pembobotan kriteria dapat diberikan secara langsung oleh pengambil keputusan atau dihitung melalui sebuah metode. Penelitian akan menghitung nilai pembobotan kriteria dengan metode Entropy. Tujuannya adalah untuk memberikan objektifitas pembobotan kriteria. Penelitian mengangkat kasus tentang pengalokasian spare part ke sejumlah store. Alternatif terbaik dengan sumber daya yang terbatas, beberapa tujuan yang saling bertentangan didekati dengan metode Goal programming. Pengambilan keputusan akan lebih terarah karena sistem menghasilkan perankingan store spare part, dan menampilkan  informasi alokasi spare part.  Kata kunci— Sistem Pendukung Keputusan, Entropy, TOPSIS, Goal Programming AbstractThe capabilities of computrized systems facilitate decision support in a number of ways, such as speed computations, increased productivity ,improved data management and others. Decisions are often made by individuals. There may be conflicting objectives even for a  decision maker. The conflicting objectives can be solved by goal programming. Research of spare part allocation focuses on an individual decision maker and presents the solving problem with Multiple Criteria Decision Making (MCDM). A lot of MCDM approaches have been developed and applied to diverse fields, like engineering, management, economic, etc. As one of the known classical MCDM approaches, TOPSIS method is known to be a common method to get the preliminary outcome.  The main concept of TOPSIS is the best alternative has the shortest distance from the positive ideal solution and has the longest distance from the negative ideal solution.  Before the stores are ranked with TOPIS method, the management assigned a weightage to each store using Entropy method.  Keywords— Decision Support Model, Entropy, TOPSIS, Goal Programming.
Pemodelan Sistem Interaksi Obat dengan Menggunakan Fuzzy Inference System dan Pareto Optimality Elena Yustina; Subanar Subanar
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.2038

Abstract

Drug interactions is the interaction occurs between drugs that consumption simultaneously. Drug interactions can produce a good effect on patients, but not rarely produce adverse effects. Patients with diabetes and hypertension expected to control blood pressure and blood glucose levels to remain in normal circumstances, it is necessary to consider the use of medications for both diseases in order to produce effective therapies.Pareto optimality is a popular concept in the determination optimal solution of multiobjective problems. In determining the optimal solution of multiobjective problem should pay attention for each objective function, frequently conflicting objective functions. The interaction of two drugs has two objective function that is maximizing the positive effects and minimize negative effects. So its use is necessary to find optimal solutions to achieve the expected therapeutic. This research using Fuzzy Inference Sistem (FIS) to determine the appropriate medication to keep blood pressure and blood glucose levels of patients with hypertension and diabetes under control in normal and Pareto optimality to determine drug optimal solution.Fuzzy Inference System generates output choice of drug classes based on fuzzy rules in accordance with the patient's disease condition. Pareto optimality produces a pair solution for diabetes and hypertension drug that satisfy thresholds the minimum effective level (Minimum Effective Concentration; MEC) and maximum toxic levels (Minimum Toxic Concentration; MTC) of each drug.
Simulasi Swarm Robot Dengan Pendekatan Rayap Pada Masalah Clustering Ketut Bayu Yogha Bintoro; Widodo Prijodiprodjo
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.2139

Abstract

AbstrakPendekatan rayap yang merupakan salah satu metode dalam rumpun swarm intelligence yang dapat mengatasi masalah clustering, pada penelitian ini pendekatan rayap dilihat dari sudut pandang pemodelan berbasis agent dan diimplementasikan ke dalam swarm robot. Penelitian ini penting untuk mengembangkan model pendekatan rayap pada kasus – kasus nyata terutama pada masalah clustering, untuk mengimplemantasikan model yang diperoleh dari studi literatur maka dibuatkan simulasi untuk menggambarkan secara detail proses yang terjadi dalam menangani masalah clustering.Pendekatan IODA digunakan untuk memodelkan interaksi yang terjadi didalam simulasi, pendekatan ini di sesuaikan dengan perangkat pengembangan yang digunakan yaitu NETLOGO. Penggunaan IODA menjadi suatu kontribusi untuk mengembangkan metodologi ini, terutama pada NETLOGO disamping pengimplementasian komunikasi tidak langsung dan optimasi pencarian yang dapat membentuk clister lebih cepat dari penelitian sebelumnya. Kata kunci— Pendekatan rayap, simulasi, IODA, clustering, agent AbstractTermites approach is one of the method in swarm intelligent field which used to handle clustering problem. In this research, termites approach are in agent metodology point of view and implemented  to swarm robot. This research is important to developing termites model in some real cases especially in clustering problem, to implement this model gathered from literatur study, we used simulation to give detail model about clustering solving process.  IODA metodologi is used to modelling  the interaction in simulation, this approach is appropriate with NETLOGO as development tool. The involve of IODA has become one of the contribution to develop this in NETLOGO beside the implementation of indirect communication and searching optimization that can makes clustering process faster than the previous research. Keywords—Termites approach, Simulation, IODA, clustering, agent.
Sistem Pendukung Keputusan Model Fuzzy AHP Dalam Pemilihan Kualitas Perdagangan Batu Mulia Sri Wahyuni; Sri Hartati
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.2140

Abstract

AbstrakPemilihan kualitas batu mulia membutuhkan kemampuan khusus untuk memilih dan menilai kualitas batu mulia yang akan diperdagangkan. Keberagaman jenis batu mulia dan konsumen menjadi kendala tersendiri ketika pengetahuan dan kemampuan individu dalam menganalisis kualitas batu mulia sangatlah minim.Penelitian ini menggunakan metode kuantitatif dengan menggunakan model Fuzzy AHP. Pengumpulan data dilakukan dengan cara konsultasi dengan Direktur Kantor Pusat Promosi Batu Mulia Indonesia GEM-AFIA GROUP  di Bandung sehingga dihasilkan kriteria-kriteria terbaik dalam pemilihan kualitas perdagangan batu mulia. Kriteria-kriteria tersebut kemudian disusun berdasarkan literatur, observasi dan wawancara, selanjutnya diberi penilaian perbandingan berpasangan dengan AHP untuk mencari bobot informasional dan menggunakan TFN untuk mencari upper excepted value.Hasil yang didapat dengan menggunaan model Fuzzy AHP dalam pemilihan kualitas perdagangan batu mulia menunjukkan bahwa kriteria berat jenis, warna, kekerasan, pemotongan, dan kejernihan merupakan kriteria utama dalam pemilihan kualitas perdagangan batu mulia. Fuzzy AHP dalam penilaian tingkat kosistensi dilakukan pada level struktur hierarki dan mampu mengakomodir ketidak konsistenan dalam penilaian. Kata kunci—AHP (Analysis Hierarchy Process), Fuzzy AHP, TFN (Triangular Fuzzy Number), upper eecepted upper. AbstractThe selection process of Precious stone quality requires particular ability in selecting and assessing the quality of traded Precious stones . The diversity types of Precious stoneand consumers in choosing it become an obstacle since the limited knowledge and ability to analyze needs of individuals.This research applied quantitative method by employing Fuzzi AHP model. The data was collected by consulting the director of  Kantor Promosi Batu Mulia Indonesia GEMAFIA GROUP located in Bandung that gives some criteria in the selection of Precious stonetrade quality. Further, these criteria are formulated based on AHP pair comparison to find out the informational quality and upper expected values using TFT (triangular Fuzzy Number).The result that is based on Fuzzy AHP method show that density, color, hardness, cutting and clarity criteria are the criteria in selecting Precious stonetrade quality.  This method in the assessment of consistency level is done in the hierarchy structure level and is able to accommodate the assessment inconsistency. Keywords—AHP (Analysis Hierarchy Process), Fuzzy AHP, TFN (Triangular Fuzzy Number),  upper eecepted upper.
Sistem Pendukung Keputusan Seleksi Anggota Paduan Suara Dewasa Menggunakan Metode Fuzzy Mamdani Sherly Jayanti; Sri Hartati
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.2141

Abstract

AbstrakKebijaksanaan dalam mengambil sebuah keputusan pada permasalahan tertentu bukan lah hal yang mudah, karena perlu dilakukan pertimbangan yang diharapkan dapat membantu memberikan alasan keputusan tertentu harus diambil. Begitu juga penanganan masalah menentukan seseorang untuk menjadi anggota paduan suara dewasa pada Sanggar Bina Vokalia Menteng Palangka Raya.Seseorang yang akan bergabung pada sebuah tim paduan suara yang akan mengikuti kegiatan atau event tertentu, maka hal yang perlu diperlukan adalah seperti kualitas usia, pengalaman, kedisiplinan, intonasi, artikulasi dan wilayah nada dari seseorang tersebut. Sistem Pendukung Keputusan Seleksi Anggota Paduan Suara Kategori Dewasa  sangat tepat diterapkan untuk penanganan masalah  yang membutuhkan penyelesaian mandiri dari komputer untuk pemrosesan data peserta yang mengikuti seleksi dengan perhitungan efisien dan akurat. Dengan menggunakan penalaran Logika Fuzzy Mamdani dalam pemrosesan data input dan output, serta informasi pendukung berupa ranking sangat mendukung dalam pengambilan keputusan untuk menentukan seseorang untuk menjadi anggota paduan suara dewasa. Kata kunci— Sistem Pendukung Keputusan, Paduan Suara, Logika Fuzzy, Mamdani  AbstractWisdom in taking a decision on a particular issue is in fact not an easy thing, because consideration needs to be done that is expected to help justify a particular decision should be taken. So is handling the problem of determining a person to become a member of the adult choir at Sanggar Bina Vokalia Menteng Palangkaraya.Someone who will join in a choir team who will follow a particular activity or event, then it is necessary to like the quality of the age, experience, discipline, intonation, articulation and tone areas of a person is.Decision Support System Selection Category Adult Choir members are very appropriate to be applied to the handling problems that require independent completion of the computer for processing the data that follows the selection of participants with efficient and accurate calculations. By using Mamdani Fuzzy Logic reasoning in data processing input and output, and supporting information in the form of ranking is very supportive in the decision to determine a person to become a member of the adult choir. Keywords— Decision Support System, Chorus, Fuzzy's logic, Mamdani
Sistem Pendukung Keputusan Dalam Menentukan Supplier Jeruk Pontianak Berbasis Fuzzy-AHP Salahuddin Salahuddin; Sri Hartati
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.2142

Abstract

Orange fruit siam Pontianak or usually called Pontianak ,it is very popular to the people and the fruit itself is very favorite of many people in Indonesia because of its taste which is so sweet and a little sour and refresing. The competition of orange in industries is becoming more intense. The high preference to this orange makes it a demand in most markets  to the food industries, farmacy industry and local(traditional) medicine has point out that supplier of this orange is meeting importan factor that quarantee direct to the company. The collection of data in this survey and the sample of orange from every area is capable of producing orange Pontianak in the province of West Kalimantan. In this research will analyst the area supplier in producing standardize orange founded on the quality and the appropriate criteria based on the SNI. The method that is used is Fuzzy-AHP with weighting non-additive.The result that is used Fuzzy AHP non-additive in stating supplier of the orange pontianak in showing, attractive criteria, hygienic,sizes, marketing, , rotting is the first criteria which is undetake for giving the supplier quality orange. In examining the level of consistency using the method Fuzzy AHP non-additive is made in every structural level, hierarchal system is capable of handling the non consistency in the end testing, then will obtained the best supplier with important criteria for the company.
Reduksi Parameter Quality-Of-Service Menggunakan Rough-Set-Theory Dalam Simulasi Routing Algoritma Dijkstra Gede Saindra Santyadi; Reza Pulungan
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.2143

Abstract

AbstrakProses pemilihan jalur/rute terbaik dalam proses routing melibatkan bobot-bobot yang terbentuk dalam topologi jaringan. Terdapat banyak parameter yang menunjang munculnya bobot tersebut. Kesalahan dalam pemilihan parameter dapat mengganggu proses kumunikasi data yang terlihat pada communication-overhead (CO) yang muncul dalam jaringan. Proses reduksi parameter dalam teori Rough Set dapat memilih parameter mana yang dianggap penting sesuai dengan nilai quality of service. Sehingga dari sekian banyak parameter, akan terpilih parameter yang akan dijadikan bobot dalam topologi. Hal ini akan mengurangi beban CO yang akan mengoptimalkan proses routing dalam jaringan.  Kata kunci—Quality of Service, reduksi parameter, teori rough set, routing, algoritma Dijkstra AbstractPath selection process/best route in the routing process involves weights that are formed in the network topology. There are many parameters that support the emergence of these weights. Errors in the selection process parameters can interfere with communication data seen in communication-overhead (CO) which appears in the network. Reduction process on Rough Set theory can select the parameters which are considered important parameters in accordance with the quality of service (QoS). So of the many parameters, will be selected parameters to be used as weights in the topology. This will reduce the burden of CO that will optimize the process of routing in the network. Keywords—Quality of Service, parameter’s reduction, rough set theory, routing, Dijkstra algorithm
Klasifikasi Posting Twitter Kemacetan Lalu Lintas Kota Bandung Menggunakan Naive Bayesian Classification Sandi Fajar Rodiyansyah; Edi Winarko
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.2144

Abstract

AbstrakSetiap hari server Twitter menerima data tweet dengan jumlah yang sangat besar, dengan demikian, kita dapat melakukan data mining yang digunakan untuk tujuan tertentu. Salah satunya adalah untuk visualisasi kemacetan lalu lintas di sebuah kota.Naive bayes classifier adalah pendekatan yang mengacu pada teorema Bayes, dengan mengkombinasikan pengetahuan sebelumnya dengan pengetahuan baru. Sehingga merupakan salah satu algoritma klasifikasi yang sederhana namun memiliki akurasi tinggi. Untuk itu, dalam penelitian ini akan membuktikan kemampuan naive bayes classifier untuk mengklasifikasikan tweet yang berisi informasi dari kemacetan lalu lintas di Bandung.Dari hasil uji coba, aplikasi menunjukan bahwa nilai akurasi terkecil 78% dihasilkan pada pengujian dengan sampel sebanyak 100 dan menghasilkan nilai akurasi tinggi 91,60% pada pengujian dengan sampel sebanyak 13106. Hasil pengujian dengan perangkat lunak Rapid Miner 5.1 diperoleh nilai akurasi terkecil 72% dengan sampel sebanyak 100 dan nilai akurasi tertinggi 93,58% dengan sampel 13106 untuk metode naive bayesian classification. Sedangkan untuk metode support vector machine diperoleh nilai akurasi terkecil 92%  dengan sampel sebanyak 100 dan nilai akurasi tertinggi 99,11% dengan sampel sebanyak 13106. Kata kunci— Twitter, tweet, klasifikasi, naive bayesian classification, support vector machine AbstractEvery day the Twitter server receives data tweet with a very large number, thus, we can perform data mining to be used for specific purpose. One of which is for the visualization of traffic jam in a city.Naive bayes classifier is an approach that refers to the bayes theorem, is a combination of prior knowledge with new knowledge. So that is one of the classification algorithm is simple but has a high accuracy. With this, in this research will prove the ability naive bayes classifier to classify the tweet that contains information of traffic jam in Bandung.The testing result, the program shows that the smallest value of the accuracy is 78% on testing by using a sample 100 record and generate high accuracy is 91,60% on the testing by using a sample 13106 record. The testing results with Rapid Miner 5.1 software obtained the smallest value of the accuracy is 72% by using a sample 100 records and the high accuracy is 93.58%  by using a sample 13.106 records for naive bayesian classification. And for the method of support vector machine obtained the smallest value is 92% accuracy by using a sample 100 records and the high accuracy of 99.11% by using a sample 13.106 records. Keywords—Twitter, tweet, classification, naive bayesian classification, support vector machine
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
Penerapan FCM dan TSK Untuk Penentuan Cluster Rawan Pangan di Kabupaten Cirebon Harliana Harliana; Azhari SN
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 6, No 2 (2012): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.2147

Abstract

AbstrakKetahanan pangan merupakan salah satu prasyarat dasar yang harus dimiliki dalam rangka mewujudkan kesejahteraan masyarakat. Namun, pada kenyataannya meskipun kabupaten Cirebon termasuk salah satu pensuplai beras wilayah Jawa Barat masih ada beberapa desa yang justru mengalami rawan pangan. Minimnya indikator yang digunakan oleh BKP5K Kabupaten Cirebon dalam menentukan status rawan pangan dan tahan pangan masih menjadi kendala dalam penganalisaan penyebab rawan pangan. Penelitian ini mencoba mengembangkan sebuah sistem yang dapat membantu BKP5K Kabupaten Cirebon untuk penentuan cluster rawan pangan dan tahan pangan serta macam rekomendasi bantuannya melalui parameter indikator ketahanan dan kerawanan pangan yang telah ditentukan. Sistem ini dibangun dengan menggunakan metode Fuzzy C-Means untuk mengelompokkan daerah rawan pangan dan tahan pangan serta metode Takagi Sugeno Kang sebagai rulebase dalam pemberian rekomendasi bantuannya. Setelah melakukan pengujian pada 6 kasus uji, aspek yang paling berpengaruh pada penentuan desa rawan pangan yaitu aspek ketersediaan pangan, aspek akses pangan dan penghidupan, serta aspek kesehatan dan gizi. Sedangkan jumlah penduduk dibawah garis kemiskinan, desa yang tidak memiliki akses penghubung yang memadai, jumlah RT tanpa akses listrik, jumlah areal tanam yang terkena puso, serta jumlah buruh baik buruh tani dan swasta merupakan 5 indikator yang memiliki pengaruh penting dalam penentuan daerah rawan pangan. Kata kunci— Fuzzy C-Means, Fuzzy Takagi Sugeno Kang, rawan pangan, cluster  AbstractFood security is one of the basic prerequisites that must be reserved in order to realize the welfare of society. Although the district Cirebon is one supplier of rice areas of West Java, there are still some villages experiencing food insecurity. The lack of indicators used by BKP5K Cirebon in determining the food insecurity is still a constraint in analyzing the causes of food insecurity. This study seeks to develop a system that can help BKP5K Cirebon to determine cluster food insecurity and advice assistance through a variety of parameters have been determined.The system is built using the Fuzzy C-Means method to classify the food insecurity and food stand andalso Takagi Sugeno Kang method asrulebase in the provision of assistance and advice. After testing 6thtest cases, the most influential aspectare: aspect food availability,aspect accessfood and livelihood, and also aspects of health and nutrition. While the number of people below the poverty line, the village with no access to adequate, the number of RT without access to electricity, the number of areas puso, and the number of workers are5thindicators that have an important influence in the determination of food-insecure areas. Keywords— Fuzzy C-Means, Fuzzy Takagi Sugeno Kang, Food insecurity, Cluster

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