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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan MEANS (Media Informasi Analisa dan Sistem) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer BEES: Bulletin of Electrical and Electronics Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Teknik Mesin, Industri, Elektro dan Informatika Journal of Informatics, Electrical and Electronics Engineering Infolitika Journal of Data Science Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Irfan Sudahri Damanik
STIKOM Tunas Bangsa
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PORTAL AKADEMIK SEMI-REALTIME AMIK DAN STIKOM TUNAS BANGSA PEMATANGSIANTAR Damani, Irfan Sudahri
InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Vol 1, No 1 (2016): InfoTekJar
Publisher : InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (698.547 KB)

Abstract

Informasi akademik pada Akademi Manajemen Informatika Komputer (AMIK) Tunas Bangsa Pematangsiantar akan tetap menjadi kebutuhan bagi mahasiswa selama mahasiswa masih aktif dalam proses pendidikan. Hal ini akan sulit diperoleh mengingat jumlah perbandingan jumlah mahasiswa  dengan staff yang melayani bidang akademik yang cukup besar. Dengan menggunakan media internet tentu akan mempermudah mahasiswa memperoleh informasi yang di inginkan serta dengan aplikasi yang berbasis database internet, tentu mahasiswa akan memperoleh informasi yang selalu ter-update. Hal ini juga tentu harus didukung oleh aplikasi yang dapat dijalankan oleh dosen pengampu matakuliah dalam hal pengiriman nilai berbasis internet.
SISTEM PENDUKUNG KEPUTUSAN DENGAN MENGGUNAKAN METODE ELECTRE DALAM MENENTUKAN PENERIMA PROGRAM INDONESIA PINTAR (PIP) MELALUI KARTU INDONESIA PINTAR (KIP) (STUDI KASUS: SD SWASTA AL – WASHLIYAH MOHO KABUPATEN SIMALUNGUN) Ningsih, Sri Rahayu; Damanik, Irfan Sudahri; Gunawan, Indra; Saputra, Widodo
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v1i1.508

Abstract

The Smart Indonesia Program (SIP) is a government-funded education assistance program for all school-aged children (6-21 years old) or from poor and vulnerable families (eg from families / household holders of prosperous family cards / PFC) or children who fulfill Predefined criteria. Smart Indonesia Program through Smart Card Indonesia (SCI) is part of the improvement of the Poor Student Support Program (PSSP) since late 2014. The author takes a case study on SD SWASTA ALWASHLIYAH Moho. SD SWASTA ALWASHLIYAH Moho is one of the primary schools in Simalungun regency that get SIP programs for students who are less able and have difficult economic constraints. This research is based on the problem of giving Smart Indonesia Card where the process of handling aid sometimes does not match the target or target. Invalid data causes errors in SIC divisions that should be given to eligible recipients. To overcome these problems required Decision Support System (DSS) is expected to solve problems in the provision of KIP with Electre method. The Electre method is a multicriteria decision-making method based on each appropriate criterion. The criteria used are: Parent Job, Elderly Income, The Number of Dependents, Number of Dependents Still Schooled, Raport Value, KKS Holders, Child Status, Residence, Type of Home. DSS SIP is only a recommendation decision to the school, for the next process handed back to the school.
PENERAPAN METODE TOPSIS DALAM MENENTUKAN PEMILIHAN KARTU PRABAYAR HANDPHONE GOBAL SYSTEM FOR MOBILE (HP GSM) Masitha, Masitha; Damanik, Irfan Sudahri; Windarto, Agus Perdana
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.931

Abstract

Prepaid Card is a card that can only be used if there is a nominal number of pulses or data packets first. This card has an active period that varies depending on the policies and programs of each provider. Many card users are still confused about choosing a prepaid card that is good for use, so they really need information that can be used as a reference in choosing a prepaid card. In this study conducted to analyze a selection of prepaid cards using the TOPSIS (Technique For Order of Preference By Similarity To Ideal Solution) method in determining alternative choices for all prepaid card users, using several assessment criteria, namely: Cost (C1), Feature Completeness (C2), Signal (C3), Promotion / Advertising (C4), and Service Quality (C5). And also by using 6 alternatives, namely: Telkomsel (A1), Axis (A2), IM3 (A3), XL (A4), US (A5), and 3 (A6). And the results of this study were ranked first, namely: 3 (A6) as the first rank with a value of 0.5286 followed by XL (A4) with a value of 0.5238 as the second rank, and Telkomsel (A1) with a value of 0.5027. IM3 (A3) with a value of 0.4988, Axis (A2) with a value of 0.4765, then the last US (A5) with a value of 0.1905. It is hoped that this research can provide a better input to all prepaid card users.Keywords: TOPSIS, decision support system, pematang siantar, prepaid card
Analisa Metode Profile Matching Pada Pemilihan Susu Rendah Lemak Berdasarkan Konsumen Sari, Hanifah Urbach; Windarto, Agus Perdana; Winanjaya, Riki; Hartama, Dedy; Damanik, Irfan Sudahri
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 4, No 1 (2020): The Liberty of Thinking and Innovation
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v4i1.2590

Abstract

Milk is a source of nutrition for humans, especially in infants who cannot digest food. Milk has a high calcium content and can strengthen human bones. This study aims to recommend low-fat milk as a recommendation to consumers to determine the right milk product. Data collection methods used were interview techniques and questionnaire random sampling to 60 respondents who used low-fat milk at STIKOM Tunas BangsaPematangsiantar. Based on the results of interviews and questionnaires, the assessment criteria were obtained, namely price (K1), side effects (K2), packaging (K3), and availability of goods (K4). The alternatives used in the study were Ultra Milk Low Fat (S1), Bear Brand Gold (S2), Frisian Flag (S3) and Hilo Teen (S4). The settlement method applied is POFILE MATCHING. The results of the algorithm show that the right alternative is for the highest ranking Hilo Teen (S4) with a final score of 88.95 and followed by Ultra Milk Low Fat (S1) with a final score of 86.325. The results of the study are expected to provide recommendations to consumers to determine the right low-fat milk.Keywords: Milk, Nutrition, Profile Matching, Decision Suport System, Product Selection
Implementasi Data Mining Dalam Mengelompokkan Jumlah Produktivitas Ubi Kayu Menurut Provinsi Menggunakan Algoritma K-Means Wulandari, Sri; damanik, irfan sudahri; Irawan, Eka; Tambunan, Heru Satria; irawan, irawan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 4, No 1 (2020): The Liberty of Thinking and Innovation
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v4i1.2727

Abstract

Abstract−Cassava is one of the main foodstuffs, not only in Indonesia but also in the world. In Indonesia, cassava is the third staple food after rice and corn. The spread of cassava plants extends to all provinces in Indonesia. Using data mining is one of the ideas of information to classify the amount of cassava productivity by province, by using the k-means clustering method the amount of cassava productivity will be collected based on the year (2011-2018) of 30 provinces. K-means is a method with unsupervised classification type where the data is grouped into one or more clusters. k-means modeling the dataset into clusters where one cluster has the same characteristics and has different characteristics from other clusters. This study aims to classify the amount of cassava productivity by province. Where the highest cluster results are obtained with a total of  2 provinces, medium cluster with 4  provinces, and a low cluster with 24 provinces.Keywords: Data Mining, K-means, Clustering, Cassava, RapidMiner Studio
Sistem Pendukung Keputusan Penentuan Pemberian Insentif Pegawai THL Menggunakan Metode Promethee Pada Kantor Walikota Pematangsiantar Sepridho, Jaka; Damanik, Irfan Sudahri; Okprana, Harly
Jurnal Sistem Komputer dan Informatika (JSON) Vol 2, No 3 (2021): Mei 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v2i3.2853

Abstract

Pematangsiantar Mayor Office is an institution that is used and functions to serve and protect the community. This paper proposes a decision support system research using the Promethee method. Promethee is one of several methods of determining the order or priority in multi-criteria analysis. This writing uses the Promethee method as a step in determining the provision of incentives for freelance daily staff at the Pematangsiantar Mayor's Office. In this study the authors took 10 alternatives with 5 assessment criteria including absenteeism, achievement, behavior, long history of work and teamwork. With the highest result obtained by alternative 9 on behalf of Triono with a value of 0.422 and the lowest result obtained by alternative 6 on behalf of Soraya with a value of -0.211.
Penerapan Metode Promethee pada Perekrutan Calon Pegawai Non PNS Bawaslu Kabupaten Simalungun Rodiah, Siti; Damanik, Irfan Sudahri; Suhendro, Dedi
TIN: Terapan Informatika Nusantara Vol 2 No 4 (2021): September 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The importance of the quality of the workforce that will be used makes management work hard and be careful in determining the criteria that will be determined for the decision making process for the recruitment of prospective workers. The authority to recruit non-civil servant election supervisors is also the full authority of Bawaslu in the process must be maximized. At present, the process of recruiting non-PNS Bawaslu employees in Simalungun Regency has not been systemized and computerized which results in suboptimal recruitment results because many employees recruited are still in doubt of their credibility. PROMETHEE is one of the Multi Criteria Decision Making (MCDM) methods, which means determining or sorting in a multi-criteria analysis, this method is known for its efficient and simple concept, in addition to solving problems related to multi criteria, this method is also very easy to applied rather than other methods. In this study, the PROMETHEE II method is used to obtain qualified employee recruitment in accordance with the desired criteria and the results of existing grades
ANALISIS EVALUASI SILHOUETTE COEFFICIENT DENGAN EUCLIDEAN DISTANCE PADA METODE CLUSTERING (STUDI KASUS : JUMLAH SEKOLAH NEGERI DI INDONESIA) Anjelita, Mawaddah; Irawan, Eka; Damanik, Irfan Sudahri
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 5, No 1 (2021): Peran Generasi Milenial Bertalenta Digital Pada Era Society 5.0
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v5i1.3642

Abstract

Penelitian ini bertujuan untuk mengetahui seberapa besar nilai silhouette coefficient yang diperoleh dari perhitungan jarak data terhadap centroid menggunakan euclidean distance pada metode k-means serta memberikan masukan dalam ilmu pengetahuan untuk penelitian selanjutnya dalam mengembangkan metode k-means. Untuk menyelesaikan permasalahan ini, peneliti menggunakan metode k-means dengan evaluasi silhouette coefficient. Dimana sumber data pada penelitian ini mengambil data langsung dari Badan Pusat Statistik (BPS) Indonesia dalam bentuk softcopy yang berjudul “Statistik Indonesia 2021” dengan URL : https://www.bps.go.id. Data yang digunakan pada penelitian ini menggunakan data tahun 2020 yang terdiri dari 34 provinsi. Data akan diolah menggunakan  metode k-means dengan silhouette coefficient menggunakan euclidean distance. Hasil yang diperoleh yaitu cluster = 4 merupakan cluster terbaik untuk mengelompokkan jumlah sekolah negeri di Indonesia menurut provinsi tahun 2020 dengan nilai silhouette coefficient sebesar -0,9944. Dengan dilakukannya penelitian dapat memberi masukan dalam ilmu pengetahuan untuk penelitian selanjutnya dalam mengembangkan metode clustering terutama k-means.
Penerapan Regresi Linier Berganda Dalam Mengestimasi Laju Pertumbuhan Penduduk Kecamatan Pematang Bandar Sari, Winda Permata; Irawan, Eka; Damanik, Irfan Sudahri
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 5, No 1 (2021): Peran Generasi Milenial Bertalenta Digital Pada Era Society 5.0
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v5i1.3641

Abstract

Penelitian ini bertujuan untuk menyelesaikan kendala yang membuat petugas kesulitan dalam mengestimasi laju pertumbuhan penduduk disetiap tahunnya dengan memanfaatkan variabel terikat dan variabel bebas. Data yang digunakan pada penelitian ini diperoleh langsung dari Badan Pusat Statistik Kabupaten Simalungun dalam bentuk softcopy yang berjudul “Kecamatan Pematang Bandar dalam Angka 2015-2019” dengan url http://simalungunkab.bps.go.id dengan data kependudukan kecamatan pematang Bandar dari tahun 2015-2019. Kecamatan pematang Bandar merupakan salah satu dari 32 kecamatan yang ada di Kabupaten Simalungun yang terdiri dari 10 nagori dan 2 kelurahan. Data yang digunakan telah diperoleh kemudian diolah menggunakan datamining estimasi terhadap laju pertumbuhan penduduk di Kecamatan Pematang Bandar, menggunakan metode regresi linier berganda. Dari hasil pengujian yang diperoleh dapat diketahui bahwa perhitungan manual dengan pengujian menggunakan software SPSS memiliki nilai persamaan regresi linier berganda yang sama, yaitu Y= (-129,857) + 1,337 X1 + 0,682 X2 dengan nilai constant (a) adalah -129,857 sedangkan nilai laki-laki [X1] adalah 1,337 dan nilai perempuan [X2] adalah 0,682. Dengan dilakukannya penelitian ini dapat memberikan informasi atau masukkan kepada petugas pencatatan kependudukan dalam mengestimasi laju pertumbuhan penduduk terutama disetiap tahun.
PENERAPAN KLASIFIKASI C4.5 DALAM MENINGKATKAN SISTEM PEMBELAJARAN MAHASISWA P, Dini Rizky Sitorus; Windarto, Agus Perdana; Hartama, Dedy; Damanik, Irfan Sudahri
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1665

Abstract

The purpose of this research is to classify the improvement of student learning systems using the C4.5 datamining method. The source of the research data was obtained from the education section of STKOM Tunas Bangsa through interviews and questionnaires to semester 5 students (160 students) in the 2019-2020 academic year study program. The attributes used in the classification of student learning systems include: Teaching System (C1), Teaching Aids (C2), Environment (C3), Infrastructure Facilities (C4) and Assignment (C5). The calculation results mention the attribute Assignment (C5) is the attribute that most influences the improvement of student learning systems. The test was also carried out using the help of Rapidminer software and obtained an accuracy of 95%.Keywords: Datamining, Classification, C4.5, Student Learning, STIKOM Tunas Bangsa
Co-Authors Abdi Rahim Damanik Achmad Noerkhaerin Putra Agus Perdana Windarto Agustinus Liberty Pasaribu Andini Fadila Sari Anjelita, Mawaddah Azi Arisandi Azi Guntur Chairul Fadlan Chintya Carolina Situmorang Cici Astria Dea Dwi Rizki Tampubolon Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Deny Franata Pasaribu Dermawan, Sabaruddin Dewi, Rafiqa Dewinta Marthadinata Sinaga Dinda Nabila Batubara Dolli Sari Sinaga Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan F Fauziah Fajar Rudi Sartomo Samosir Fikri Wicaksono Frskila Parhusip Guntur, Azi Hadinata, Edrian Hanifah Urbach Sari Hanne Lore Br Siagian Hartama, Dedy Hasudungan Siahaan Hendry Qurniawan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan, Heru Satria Hutasoit, Rahel Adelina Ika Okta Kirana Ilham Syahputra Saragih Ilham Syaputra Saragih Indah Pratiwi M.S Indra Gunawan Ira Audita Irawan Irawan Irnanda, Khairunnissa Fanny Irvanizam, Irvanizam Jaya Tata Hardinata Laila Kumalasari M Fauzan M FAUZAN M Fauzan M Fauzan M. Fauzan M. Safii Manurung, Hotben Marina Rajagukguk Masduki Nizam Fadli Masitha Masitha Masitha, Masitha Mawaddah Anjelita Mian Manimpan Siahaan Mira Ariffiani Mita Ariffiani Muhammad Aliyul Amri Muhammad Fachrur Rozy Muhammad Ifnu Suhada Muhammad Ifnu Suhada Napitupulu, Flora Sabarina Nasution, Rizki Alfadillah Ningsih, Sri Rahayu Nur Arief Nur Hasanah Lubis Nurhidayana Nurhidayana Okprana, Harly P, Dini Rizky Sitorus Paulus Hendrico Silalahi Primatua Sitompul Rahel Nita Trides Siahaan Ria Annisa Saragih Ridho Hayati Alawiah Roni Kurniawan S Saifullah Sabaruddin Dermawan Sahendra Fahreza Saifullah Saifullah Sandy Putra Siregar Saputra, Widodo Saragih, Ilham Syaputra Saragih, Ria Annisa Sari, Hanifah Urbach Sari, Winda Permata Sepridho, Jaka Siahaan, Mian Manimpan Sinaga, Waris Pardingatan Siregar, Sandy Putra Siti Hadija siti rodiah Solikhun Solikhun Solikhun Sri Rahayu SRI RAHAYU Sri Rahayu Ningsih Sri Wulandari Suhada Suhada Suhada Suhada Suhada, Suhada Suhada, Muhammad Ifnu Suhendro, Dedi Sumantri Sihombing Sundari Retno Andani Susiani Susiani Susiani, Susiani Taufiq Hidayat Theresia Siburian Vikki, Zakial Wanayumini Wanto, Anjar Widodo Saputra Winanjaya, Riki Yumni Syabrina Agustina Lubis Zulia Almaida Siregar