Articles
<![CDATA[METODE BEDA HINGGA DAN TEOREMA NEWTON UNTUK MENENTUKAN JUMLAH DERET ]]>
<![CDATA[Mulyani, Tri]]>;
<![CDATA[Hasan, Moh.]]>;
<![CDATA[Slamin, Slamin]]>
<![CDATA[ Prosiding Seminar Matematika dan Pendidikan Matematik Vol 1 No 3 (2014): Prosiding Seminar Nasional Matematika 2014 ]]>
Publisher : <![CDATA[Prosiding Seminar Matematika dan Pendidikan Matematik ]]>
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<![CDATA[Permasalahan yang sering dihadapi untuk membuktikan kebenaran rumus suatu deret adalah jika yang disajikan rumus suatu deret yang bukan deret aritmatika dan bukan deret geometri. Salah satu pembuktian yang paling sering dipakai adalah pembuktian dengan induksi matematika. Penelitian ini dilakukan untuk menentukan rumus jumlah n suku pertama dari: (1) deret aritmatika, deret arirmatika bertingkat dengan landasan deret aritmatika; (2) deret geometri; (3) deret aritmatika bertingkat dengan landasan deret geometri; dan (4) deret yang bukan deret aritmatika dan bukan deret geometri yang diketahui rumus suku ke-nnya, dengan menggunakan metode beda hingga dan teorema Newton. Rumus jumlah n suku pertama yang diperoleh dari hasil penelitian kemudian dibuktikan kebenarannya dengan menggunakan induksi matematika.]]>
<![CDATA[Rancang Bangun Aplikasi Transaksi Elektronik Ritel Pupuk Dengan Metode Electronic Data Interchange (EDI) ]]>
<![CDATA[Adiwijaya, Nelly Oktavia]]>;
<![CDATA[M, Nurul Istiana]]>;
<![CDATA[., Slamin]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 4, No 1: Maret 2015 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v4n1.133.2015
<![CDATA[Fertilizer distribution from distributor to agents, are required to be responsive in addressing the demand for fertilizers. Distributors are also required to be able to manage inventory in the warehouse, to avoid overstocking of fertilizer. Design and implementation of  a fertilizer retail electronic commerce applications using electronic data interchange (EDI) method is applied in this study. The system is built to help distributors to control the existence of the stock of fertilizer so no excess stock. In addition, the use of EDI can provide information quickly (real-time) without having to go directly to the warehouse locations.Keywords : Application, Retail, Electronic data interchange (EDI) ]]>
<![CDATA[Bilangan Dominasi Jarak-2 Graf Jahangir Jn,m ]]>
<![CDATA[Yayuk Wahyuni]]>;
<![CDATA[M. Utomo]]>;
<![CDATA[Slamin Slamin]]>
<![CDATA[ Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Vol 1 No 1 (2017): Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai Islami ) ]]>
Publisher : <![CDATA[Mathematics Department ]]>
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<![CDATA[Dalam graf himpunan dinamakan himpunan dominasi jarak-2 (distance-2 dominating set) jika setiap titik anggota berada dalam jarak 2 dari paling sedikit satu titik dalam . Kardinalitas minimum diantara himpunan dominasi jarak-2 pada graf dinamakan bilangan dominasi jarak–2 dari , dinotasikan dengan . Penelitian ini bertujuan untuk menentukan bilangan dominasi jarak-2 dari graf Jahangir Jn,m, dengan menentukan suatu himpunan dominasi jarak-2 dan memperlihatkannya sebagai himpunan dominasi jarak-2 dengan kardinalitas minimum. Hasil penelitian ini menunjukkan bahwa untuk berlaku sedang untuk yang lain bilangan dominasi jarak-2 Jn,m dapat dikelompokkan nilainnya dalam tiga kelompok bergantung pada nilai , semuanya berlaku untuk .]]>
<![CDATA[On inclusive distance vertex irregular labelings ]]>
<![CDATA[Martin Baca]]>;
<![CDATA[Andrea Semanicova-Fenovcikova]]>;
<![CDATA[S. Slamin]]>;
<![CDATA[Kiki A. Sugeng]]>
<![CDATA[ Electronic Journal of Graph Theory and Applications (EJGTA) Vol 6, No 1 (2018): Electronic Journal of Graph Theory and Applications ]]>
Publisher : <![CDATA[GTA Research Group, Univ. Newcastle, Indonesian Combinatorics Society and ITB ]]>
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DOI: 10.5614/ejgta.2018.6.1.5
<![CDATA[For a simple graph G, a vertex labeling f : V(G) → {1, 2, ..., k} is called a k-labeling. The weight of a vertex v, denoted by wtf(v) is the sum of all vertex labels of vertices in the closed neighborhood of the vertex v. A vertex k-labeling is defined to be an inclusive distance vertex irregular distance k-labeling of G if for every two different vertices u and v there is wtf(u) ≠ wtf(v). The minimum k for which the graph G has a vertex irregular distance k-labeling is called the inclusive distance vertex irregularity strength of G. In this paper we establish a lower bound of the inclusive distance vertex irregularity strength for any graph and determine the exact value of this parameter for several families of graphs.]]>
<![CDATA[Non-inclusive and inclusive distance irregularity strength for the join product of graphs ]]>
<![CDATA[Faisal Susanto]]>;
<![CDATA[Kristiana Wijaya]]>;
<![CDATA[I Wayan Sudarsana]]>;
<![CDATA[Slamin Slamin]]>
<![CDATA[ Electronic Journal of Graph Theory and Applications (EJGTA) Vol 10, No 1 (2022): Electronic Journal of Graph Theory and Applications ]]>
Publisher : <![CDATA[GTA Research Group, Univ. Newcastle, Indonesian Combinatorics Society and ITB ]]>
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DOI: 10.5614/ejgta.2022.10.1.1
<![CDATA[A function ϕ: V(G)→{1, 2, …, k} of a simple graph G is said to be a non-inclusive distance vertex irregular k-labeling of G if the sums of labels of vertices in the open neighborhood of every vertex are distinct and is said to be an inclusive distance vertex irregular k-labeling of G if the sums of labels of vertices in the closed neighborhood of each vertex are different. The minimum k for which G has a non-inclusive (resp. an inclusive) distance vertex irregular k-labeling is called a non-inclusive (resp. an inclusive) distance irregularity strength and is denoted by dis(G) (resp. by dis(G)). In this paper, the non-inclusive and inclusive distance irregularity strength for the join product graphs are investigated.]]>
<![CDATA[PEWARNAAN TITIK TOTAL ANTIAJAIB LOKAL PADA GRAF HASIL OPERASI KORONA DAN KAITANNYA DENGAN KETERAMPILAN BERPIKIR TINGKAT TINGGI ]]>
<![CDATA[Safira Izza Ghafrina]]>;
<![CDATA[Slamin Slamin]]>;
<![CDATA[Dafik Dafik]]>;
<![CDATA[Arif Fatahillah]]>;
<![CDATA[Antonius Cahya Prihandoko]]>
<![CDATA[ Saintifika Vol 20 No 2 (2018) ]]>
Publisher : <![CDATA[Jurusan Pendidikan MIPA FKIP Universitas Jember ]]>
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<![CDATA[Penelitian ini merupakan pengembangan dari paper berjudul “Local Antimagic Vertex Coloring of a Graph” oleh Arumugam et al. mengenai pewarnaan titik dengan pelabelan sisi pada graf khusus yang bertujuan untuk menentukan pewarnaan titik total antiajaib lokal pada graf hasil operasi korona. Penelitian juga akan menganalisis tentang keterkaitan antara pewarnaan titik total antiajaib lokal dengan pewarnaan titik antiajaib lokal pada graf hasil operasi korona ; Dan Menganalisis kaitan keterampilan berpikir tingkat tinggi dalam menentukan pewarnaan titik total antiajaib lokal pada graf hasil operasi korona yang diteliti menggunakan Taksonomi Bloom Revisi. Dalam penelitian ini digunakan instrumen validasi untuk mengetahui pencapaian tingkat keterampilan berpikir tinggi. Hasilnya, ditemukan teorema baru yang membuktikan bahwa bilangan kromatik antiajaib lokal oleh Arumugam lebih besar dibandingkan bilangan kromatik total antiajaib lokal . Dalam penelitian ini juga menghasilkan kaitan keterampilan berpikir tingkat tinggi dalam menentukan pewarnaan titik total antiajaib lokal pada graf hasil operasi korona yang diteliti.]]>
<![CDATA[PEWARNAAN SISI r-DINAMIS PADA GRAF HASIL OPERASI AMALGAMASI TITIK KELUARGA GRAF POHON DAN KAITANNYA DENGAN KETERAMPILAN BERPIKIR TINGKAT TINGGI ]]>
<![CDATA[Lusia Dewi Minarti]]>;
<![CDATA[Dafik Dafik]]>;
<![CDATA[Susi Setiawani]]>;
<![CDATA[Slamin Slamin]]>;
<![CDATA[Arif Fatahillah]]>
<![CDATA[ Saintifika Vol 21 No 2 (2019) ]]>
Publisher : <![CDATA[Jurusan Pendidikan MIPA FKIP Universitas Jember ]]>
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<![CDATA[Abstract. Pewarnaan sisi dinamis suatu graf didefinisikan sebagai pemetaan dari ke himpunan warna sedemikian hingga memenuhi kondisi dan dimana adalah himpunan sisi yang bertetangga dengan dan adalah derajat titik . Nilai yang minimal sehingga graf memenuhi pewarnaan warna sisi dinamis disebut bilangan kromatik sisi dinamis, yang dinotasikan dengan Penelitian ini, peneliti menentukan bilangan kromatik pada graf hasil operasi amalgamasi titik dari keluarga graf pohon yaitu graf bintang dan graf sapu menggunakan metode deduktif aksiomatik. Hasil dari penelitian ini adalah teorema yang menyatakan bilangan kromatik pewarnaan sisi dinamis. Terdapat tiga teorema yang dihasilkan dari graf yang diteliti serta setiap tahap dalam penelitian ini dikaitkan dengan keterampilan berpikir tingkat tinggi. Keywords: Pewarnaan sisi dinamis, operasi amalgamasi titik, keterampilan berpikir tingkat tinggi.]]>
<![CDATA[Sistem Pendukung Keputusan Seleksi Beasiswa Situbondo Unggul Menggunakan Metode Simple Additive Weighting dan Profile Matching ]]>
<![CDATA[Moh Febri Nurul Qorik]]>;
<![CDATA[Slamin Slamin]]>;
<![CDATA[Priza Pandunata]]>
<![CDATA[ INFORMAL: Informatics Journal Vol 3 No 1 (2018): INFORMAL - Informatics Journal ]]>
Publisher : <![CDATA[Faculty of Computer Science, University of Jember ]]>
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DOI: 10.19184/isj.v3i1.9853
<![CDATA[This study is about the use of simple additive weighting (SAW) and profile matching methods for the construction of information systems supporting the decision selection of scholarships. The case study of this research is the selection of superior situbondo scholarships in the Education Office of Situbondo Regency. The purpose of this study was to apply the profile matching method and SAW in resolving the problem of selecting the Situbondo Superior Scholarship recipients who had 2 aspects of assessment, namely aspects of poverty and academics which made it difficult to select scholarships, this difficulty is caused by the value of the aspect of poverty must be the smaller the difference in the value of students with the value of the scholarship it will be better while the academic value must go far beyond the minimum value, the better. The profile matching method is used to calculate the value of the aspect of poverty and SAW is used to calculate the value of the academic aspects. To determine the final results of this study using the criteria for decision-making scale determined by the District Education Office of Situbondo, one of the final methods of the method is less than 30 worth not funded, one of the final method values less than 60 is considered to be funded. The development of information systems supporting superior decision making for the Situbondo scholarship using the profile matching and simple additive weighting methods using a website-based system with system design using the SDLC waterfall model, implementation of the system using the laravel framework and program code using the hypertext pre-processor programming language (PHP ), while for managing the database using MySQL DBMS and system testing using black box and white box ( testing unit). The results of this research method of profile matching and simple additive weighting can be applied properly in a superior situbondo scholarship decision support system.]]>
<![CDATA[Rancang Bangun Aplikasi Customer Relationship Management (CRM) Untuk Identifikasi Tingkat Kepuasan Pelanggan Pada Perusahaan PT. TIKI Jalur Nugraha Ekakurir (JNE) Agen Mastrip Jember Menggunakan Metode K-Means Clustering ]]>
<![CDATA[Moch Bustommy Maulana]]>;
<![CDATA[Slamin Slamin]]>;
<![CDATA[Oktalia Juwita]]>
<![CDATA[ INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal ]]>
Publisher : <![CDATA[Faculty of Computer Science, University of Jember ]]>
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<![CDATA[The level of customer satisfaction is a benchmark to get a better benefit. One of the strategies that relates to creation of customer satisfaction is customer relationship management (CRM). Tiki Jalur Nugraha Ekakurir (JNE) Ltd. in Mastrip Jember agency is a company that experienced consumers degression after the emergence of competitors that offered better services. Because of that it is necessary to evaluate the service quality, facilities, and rates compatibility that can affect customer satisfaction. Therefore, CRM method is needed to know the level of customer satisfaction. Questionnaire is used as the method to collect the customers’ responses as the data. After that, the data which is the questionnaires that contain the customer’s responses is processed using K-Means clustering method as the grouping algorithm of respondents. K-means is algorithm clustering by grouping the data which has similar criteria by determining the center point of the cluster (centroid). There are 4 Clusters, the first cluster has a role as a very dissatisfied customer, the second cluster is not satisfied customer, the third cluster is satisfied customer and the fourth cluster has a role as a very satisfied customer. The application examination used 100 respondents with 80 respondents are training set and 20 respondents are test set. The result showed the cluster which has the most members is cluster 3, it means that there are so many customers satisfied with the services. The results of the training test set 100% accurate with the test set. Thus, the appropriate centroid coordinate is the one from the cluster in the last training set iteration.]]>
<![CDATA[Sistem Prediksi Jumlah Permintaan Produk Darah Menggunakan Metode Least Square Regression Line (Studi Kasus : Utd Pmi Kabupaten Jombang) ]]>
<![CDATA[Dzurrotun Nasyika]]>;
<![CDATA[Slamin Slamin]]>;
<![CDATA[Priza Pandunata]]>
<![CDATA[ INFORMAL: Informatics Journal Vol 3 No 2 (2018): INFORMAL - Informatics Journal ]]>
Publisher : <![CDATA[Faculty of Computer Science, University of Jember ]]>
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DOI: 10.19184/isj.v3i2.9989
<![CDATA[Blood Transfusion Unit (UTD) as the provider of blood supply is required to fulfill blood demand. However in reality, the blood stock does not always meet the demand for blood. The amount of blood group stock in UTD depends on blood donors who voluntarily donate blood. Red blood cells only have a life span of 35 days since they were donated, if they have passed that time the blood cannot be used for transfusion. Based on these problems, the authors applied the Lesat Square Regression Line method to predict the number of requests for blood products in the coming month. The calculation results obtained prediction of demand with the smallest MAPE value that is blood product of PRC blood type A with a value of 14.40%. The biggest MAPE value obtained is 180.66% for WB blood type AB. Factors or parameters that affect the amount of blood product demand, that is the environment, disease outbreaks and differences in body resistance of each blood group. In addition, the types of blood products also have a number of different requests depending on the level of blood needs for health.]]>
