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All Journal Seminar Nasional Informatika (SEMNASIF) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Informatics Management and Information Technology Journal of Social Responsibility Projects by Higher Education Forum KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Basic and Applied Science J-SAKTI (Jurnal Sains Komputer dan Informatika) JUSTIN (Jurnal Sistem dan Teknologi Informasi) BEES: Bulletin of Electrical and Electronics Engineering TECHSI - Jurnal Teknik Informatika

Sundari Retno Andani

STIKOM Tunas Bangsa, Pematangsiantar

Author-ID : 500939

Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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FUZZY MAMDANI DALAM MENENTUKAN TINGKAT KEBERHASILAN DOSEN MENGAJAR Sundari Retno Andani
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 4 (2013): Intelligent System dan Application
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Permasalahn yang timbul di dunia ini terkadang sering sekali memiliki jawaban yang tidak pasti, logika fuzzy merupakan salah satu metode untuk melakukan analisis system yang tidak pasti. Paper ini berisi tentang penggunaan metode logika fuzzy mamdani dalam menentujkan tingkat keberhasilan dosen mengajar pada AMIK Tunas Bangsa Pematangsiantar. Masalah yang diselesaikan adalah cara menentukan tingkat keberhasilan dosen mengajar jika hanya menggunakan dua variable input, yaitu dosen dan nilai. Langkah pertama penyelesaian masalah tingkat keberhasilan dosen mengajardengan menggunakan metode fuzzy mamdani yaitu menentukan variable input dan output yang merupakan himpunan tegas. Langkah kedua yaitu mengubah variable input menjadi himpunan fuzzy dengan proses fuzzifikasi, selanjutnya langkah ketiga adalah pengolahan datahimpunan fuzzy dengan metode maksimum. Dan langkah terakhir atau keempat adalah mengubah output menjadi himpunan tegas dengan proses defuzzifikasi dengan metode centroid, sehingga akan diperoleh hasil yang diinginkan pada variable output. Hasil dari perhitungan dengan menggunakan metode fuzzy mamdani dari tingkat keberhasilan dosen mengajar untuk nilai variable dosen 55 dan nilai variable nilai 65 adalah 80.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KEPALA BAGIAN DISTRIBUSI PADA PDAM TIRTAULI PEMATANGSIANTAR DENGAN MENGGUNAKAN METODE SAW Ahmad, Abdullah; Solikhun, Solikhun; Andani, Sundari Retno
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

The study, entitled "Supporting System for the Decision of the Head of Distribution Section at PDAM Tirtauli Pematangsiantar Using the SAW Method" aims to produce a Supportive System that is objective and systematic in determining the distribution heads who have the best qualifications. The research data is sourced from the relevant agencies in 2018. The data that is used as a reference for the requirements of the system requirements that are built is obtained from interviews with relevant agencies. From the interview, it was found that the problem of lack of objectivity and transparency of information in the process of determining the section head in any sector including the determination of the head of the distribution section is the absence of a standard or system used in determining the section head and only using manual selection method so that the determination of the section head is determined subjectively. In addition, the Candidates / alternatives recommended by PDAM Tirtauli themselves consist of 5 employees from a total employee population of 362 with the highest criteria and 5 criteria as the requirements for the assessment of the candidates for the head of the distribution department itself covering the criteria of responsibility (C1), achievement motivation (C2) , discipline (C3), communicative (C4), and working period (C5). This study uses the Simple Additive Weighting (SAW) method. With this system, agency leaders can produce a decision to choose the best distribution head more objectively.Keywords: Election of Distribution Section Head of PDAM Tirtauli Pematangsiantar, Decision Support System (SPK), Simple Additive Weighting (SAW)

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN OPERATOR SELULER MENGGUNAKAN METODE MULTI-OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS (MOORA) Nur, Khairun Nisa Arifin; Andani, Sundari Retno; Poningsih, Poningsih
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

PematangsiantarÂ is a developing city in North Sumatra, so it is not surprising that there are a lot of freight forwarding partners that offer goods delivery services to peoples such as POS Indonesia, JNE, JET Express, J & T Express and SiCepat Express. Many factors that influence people, especially online shop users on the selection of freight forwarding companies, such as the length of delivery, price, type of fleet, range, to company experience. Then it is necessary to build a system that helps the community in taking a decision. The model used to build this Decision Support System uses the Multi-Objective Optimization On The Base Of Ratio Analysis Method which is expected to provide convenience for people in the selection of cellular operators that they will use.Keywords: Decision Support System, MOORA, Online Shop, delivery services

PENENTUAN PENERIMA KIP DENGAN MENGGUNAKAN METODE MOORA PADA SD NEGERI 124395 PEMATANG SIANTAR Sinaga, Rahmadani Fitri; Andani, Sundari Retno; Suhada, Suhada
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

The Smart Indonesia Card (KIP) is an educational cash assistance until graduating from high school with the age of 6-21 years of school age coming from poor families (underprivileged) or who are registered as participants in the Family Hope Program (PKH) or Family Welfare Card (KKS ) The Indonesia Smart Card (KIP) is a refinement part of the Poor Student Assistance Program (BSM) since the end of 2014. The author took a case study on 124395 Public Elementary School. 124395 Public Elementary School is one of the Public Elementary Schools in Pematangsiantar which received the Smart Indonesia Program for students / i poor and have difficult economic constraints. This research is in the background of the problem of KIP provision where the process of delivering assistance sometimes does not meet the target or target. Invalid data causes errors in the distribution of KIP that should be given to recipients who are entitled to receive it. To overcome these problems, a Decision Support System (SPK) is needed which is expected to solve problems in the provision of KIP with the Moora method. The Moora method is a multicriteria decision making method based on each appropriate criterion. The criteria used are: Fathers Work, Mothers Work, Fathers Income, Mothers Income, Amount of Dependent, Amount of Dependents Still in School, Rapot Value, KKS Holder, Residence, Type of House. SPK KIP is a recommendation to the school, for the next process to be returned to the school.Keywords: Decision Support System, Moora, Indonesia Smart Card (KIP)

PEMANFAATAN ALGORITMA CLUSHTERING DALAM MENGELOMPOKKAN JUMLAH DESA/KELURAHAN YANG MEMILIKI SARANA KESEHATAN MENURUT PROVINSI DENGAN K-MEANS Sadewo, Mhd Gading; Windarto, Agus Perdana; Andani, Sundari Retno; Handrizal, Handrizal
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 1, No 1 (2017): Intelligence of Cognitive Think and Ability in Virtual Reality
Publisher : STMIK Budi Darma

Kesehatan merupakan hal yang sangat penting bagi semua manusia karena tanpa kesehatan yang baik, maka setiap manusia akan sulit dalam melaksanakan aktivitasnya sehari-hari. Kesehatan adalah keadaan sehat, baik secara fisik, mental, spritual maupun sosial yang memungkinkan setiap orang untuk hidup produktif secara sosial dan ekonomis. Penelitian ini membahas tentang Pemanfaatan Algoritma Clushtering Dalam Mengelompokkan Jumlah Desa/Kelurahan Yang Memiliki Sarana Kesehatan Menurut Provinsi Dengan K-Means. Sumber data penelitian ini dikumpulkan berdasarkan dokumen-dokumen keterangan Jumlah Desa/Kelurahan Yang Memiliki Sarana Kesehatan yang dihasilkan oleh Badan Pusat Statistik Nasional. Data yang digunakan dalam penelitian ini adalah data dari tahun 2008-2014 yang terdiri dari 34 provinsi. Variable yang digunakan (6) jumlah populasi dari tahun 2008-2014. Data akan diolah dengan melakukan clushtering dalam 3 clushter yaitu clusther tingkat sarana kesehatanÂ tinggi, clusther tingkat sarana kesehatanÂ sedang dan rendah. Centroid data untuk cluster tingkat populasi tinggi 245, 624, 1434, 1038, 2264, 1223, Centroid data untuk cluster tingkat populasisedang 53, 89, 203, 271, 691, 212, dan Centroid data untuk cluster tingkat populasi rendah 7, 1, 9, 50, 0, 23. Sehingga diperolehÂ penilaian berdasarkan indeks Desa/Kelurahan Yang Memiliki Sarana Kesehatan dengan 4 provinsi tingkat sarana kesehatan tinggi yaitu Sumatera Utara, Jawa Barat, Jawa Tengah, Jawa Timur, 14 provinsi tingkat sarana kesehatan sedang, dan 16 provinsi lainnya termasuk tingkat sarana kesehatan rendah. Hal ini dapat menjadi masukan kepada pemerintah, provinsi yang menjadi perhatian lebih pada Desa/Kelurahan Yang Memiliki Sarana Kesehatan berdasarkan cluster yang telah dilakukan.

Model Jaringan Syaraf Tiruan Dalam Memprediksi Produksi Susu Segar Di Indonesia Berdasarkan Propinsi Rika Asma Dewi; Rusmansyah Rusmansyah; Syahrul Ramadan; Sundari Retno Andani; Solikhun Solikhun
Jurnal Teknovasi : Jurnal Teknik dan Inovasi Vol 6, No 1 (2019): Teknovasi April 2019
Publisher : LPPM Politeknik LP3I Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55445/teknovasi.v6i1.281

The problem of drinking fresh milk in Indonesia looks minimal and rarely from children to adults who drink fresh milk, both milk and milk in canned milk. In an effort to realize the provisions as stipulated in the Minister of Health Regulation No. 75 of 2013 informing one's nutritional needs based on age and sex, the Indonesian Government has increased nutritional needs in Indonesia. This research contributes to the government to be able to predict the Production of Fresh Milk in Indonesia by Province. The data used is data from the National Statistics Agency through the website www.bps.go.id. The data is predictive data of fresh milk from 2010 to 2017. The algorithm used in this study is Artificial Neural Networks with the Backpropogation method. The input variables used were data for 2010 (X1), data for 2011 (X2), data for 2012 (X3), data for 2013 (X4), data for 2014 (X5), data for 2015 (X6) and 2016 data (X7) with 4 training and testing architectural models, namely 7-2-1, 7-4-1, 7-16-1 and 7-32-1. Target data is taken from 2017 data. The resulting output is the best pattern of Artificial Neural Network architecture. The best architectural model is 7-4-1 with EPOCH 1042, MSE 0.0095979 and 100% accuracy rate. From this model, the prediction of Fresh Milk Production is based on provinces in Indonesia.

Application of Data Mining in Determining Social Assistance Recipients With C4.5 Algorithm in Maligas Mountain District Rika Nur Adiha; Sundari Retno Andani; Widodo Saputra
International Journal of Basic and Applied Science Vol. 10 No. 3 (2021): December: Basic and Applied Science
Publisher : Institute of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v10i3.59

The Gunung Maligas District Office is a government agency tasked with running a government program, namely the Social Assistance Receipt program, to run the social assistance program, many residents complain that they do not receive assistance, while some residents who are considered capable actually get assistance, where each aid program is have different criteria in determining the recipient. Due to the large number of existing aid programs with different criteria in determining the acceptance of the aid program, of course, local government staff will have difficulty in conducting the selection process. So we need a system that is able to help local government staff to more easily determine the recipients of the social assistance. Based on the historical data of beneficiaries, recommendations for the classification of beneficiaries can be made that will assist government staff. Classification can be done using the C4.5 algorithm. In this study, it has parameters, namely, occupation, income, housing conditions and number of dependents. By applying the C4.5 data mining algorithm, it is hoped that it will make it easier and faster for government staff to determine the recipients of social assistance at the Gunung Maligas District Office.

Rancang Bangun Robot Pemotong Rumput Berbasis Arduino Menggunakan Smartphone Android Bellarmino Wira Permana; Sundari Retno Andani; Ika Purnama Sari; Dedy Hartama; Jalaluddin Jalaluddin
BEES: Bulletin of Electrical and Electronics Engineering Vol 2 No 1 (2021): July 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

House chores that people do is still using human power, one of which is taking care of the yard in terms of cutting grass, which still uses simple tools such as knives or grass shears so that it is enough to spend energy and time. Technology is very appropriate in helping the community's workload, for example, an Arduino based lawn mower robot that is controlled via an android device with a Bluetooth HC-06 device connection then equipped with an L298n driver as a wheel motor drive, and the robot is equipped with a cutting blade made of nylon string a distance of 0.9 inches from the ground, we can control the robot through an android device via navigation commands on the application. The robot can move forward, backward, turn right, turn left, and the robot cuts the grass cut according to the command.

Sistem Pendukung Keputusan Untuk Dispensasi Pembayaran Uang Kuliah Poningsih Poningsih; Sundari Retno Andani
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 3 (2018): Edisi Juli
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v3i0.66

STIKOM Tunas Bangsa give facility to some students in tuition payment to the underprivileged students in economic but they achieve. For the convenience, it must suitable with applicable criteria established by the Institution. Because of the large number of students who apply for the tuition free dispensation was very much, it is necessary to build a decision support system to give a decision or recommendation associated with the tuition payment dispensation. This decision support system use fuzzy logic that will help STIKOM Tunas Bangsa Institution in determining who is eligible to receive a tuition free dispensation as well as a large percentage of tuition free delays. The criteria that established in this case study was the large of parents income, the number of parental dependent, the number of sibling. Not all who apply for dispensation will be accepted, but only those who meet the criteria will be accepted.

Metode Simple Multi Attribute rating Technique (SMART) Dalam Menentukan Penerima Dana Bantuan Yayasan AMIK Tunas Bangsa Sundari Retno Andani
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Foundation grants are funds that comes from foundation and given for student achievement and poor, which aims to prevent collage drop outs for students. The criteria used in determining the foundation grant recipients are GPA, parent’s income and the number of dependents. The method applied in determining the foundation grant recipients is SMART (Simple Multi Attribute rating Technique) method. Because this method able to solve the multicriteria decision making problems, base on theory that each criteria has a weight that describes how important these criteria with other criteria. The results of this research are recommendations from recipients of foundation grant.

Co-Authors Abdullah Ahmad Agung Pratama Agus Perdana Windarto Angga Riadi Angga Wisesa Bellarmino Wira Permana Dedi Suhendro Dedy Hartama Delima Syah Putri Sinaga Dewi, Rafiqa Gultom, Devi Handrizal Handrizal Handrizal Handrizal Hasudungan Siahaan Hendry Qurniawan Iin Parlina Ika Okta Kirana Ika Purnama Sari Ilham Syahputra Saragih Indra Gunawan Indra Gunawan Indra Gunawan Irawan Irawan Irawan Irawan Irfan Sudahri Damani, Irfan Sudahri Jalalludin Jalalludin Jalaluddin Jalaluddin Jaya Tata Hardinata Kiki Aidi Saputra Mario Junianto Manurung Mhd Gading Sadewo Muhammad Ifnu Suhada Muhammad Irfan Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Safii Muhammad Soleh Ni Luh Ari Yusasrini Nur, Khairun Nisa Arifin Poning Sih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih, Poningsih Qurniawan, Hendry Rika Asma Dewi Rika Nur Adiha Rizki Pratama Rusmansyah Rusmansyah Sadewo, Mhd Gading Sahendra Fahreza Sinaga, Rahmadani Fitri Siregar, Zulia Almaida Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Subastian Wibowo Suhada Suhada, Suhada Syahrul Ramadan Wanto, Anjar Widodo Saputra Zepri Pratama Zulaini Masruro Nasution Zulia Almaida Siregar

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