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All Journal Jurnal TIMES JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Eksplora Informatika Digital Zone: Jurnal Teknologi Informasi dan Komunikasi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Jurnal Ilmu Teknik dan Komputer Jurnal Teknik Informatika C.I.T. Medicom JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Sistem Informasi dan Sistem Komputer RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Bulletin of Information Technology (BIT) EXPLORER BEES: Bulletin of Electrical and Electronics Engineering Jurnal ABDIMAS Budi Darma Bulletin of Multi-Disciplinary Science and Applied Technology Jurnal Informatika Dan Tekonologi Komputer (JITEK) Jurnal Sains dan Teknologi Journal of Computing and Informatics Research Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Journal of Informatics, Electrical and Electronics Engineering Bulletin of Information System Research JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi ORAHUA : Jurnal Pengabdian Kepada Masyarakat
Efori Buulolo
STMIK Budi Darma, Medan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Veterinary Other

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Analisa Penerapan Metode MOOSRA dan MOORA dalam Keputusan Pemilihan Lokasi Usaha Sudarsono, Bernadus Gunawan; Zulkarnain, Iskandar; Buulolo, Efori; Utomo, Dito Putro
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2696

Abstract

In the world of work, competition certainly exists. Especially in the selection of the location of the business being run. The better the location of the place of business, of course, the more competition. In this study, we will discuss the selection of a strategic and appropriate business location. The location of the business greatly affects the development of the business being run, many businesses do not develop (loss) so they have to stop their business because the location of the business is far from residential areas, the location is narrow and so on. To avoid this, we need a system that can solve the problem which is called a decision support system. Decision support system is a structured system in making effective business location selection decisions using methods such as WASPAS, SPI, TOPSIS, WP, SAW, MOORA, MOOSRA, EDAS and many others. The selection of business locations used the MOOSRA and MOORA methods. Both methods are very simple and easy to understand with the assessment based on the criteria used, namely Number of Competitors, Crowd Center, Location Size, Place Rent Price and Location Cleanliness. The results obtained after applying the two methods in the selection of business locations, namely the highest alternative or the first rank is Alternative A1 with a reference value of 0.564
Algoritma Clustering Untuk Membentuk Cluster Zona Penyebaran Covid-19 Bu'ulolo, Efori; Purba, Bister
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 12 No. 1 (2021): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v12i1.6572

Abstract

Covid-19 yaitu suatu penyakit yang menyerang sistem pernapasan manusia dan dapat menular dengan mudah. Sumatera Utara salah satu daerah yang dilanda pandemi Covid-19. Melalui Gugus Tugas Percepatan dan Penanganan Covid-19 provinsi Sumatera Utara telah melakukan berbagai upaya untuk pencegahan penyebaran Covid-19 seperti belajar dan ibadah dirumah, himbauan pakai masker dan lain sebagainya. Untuk mempermudah identifikasi penyebaran Covid-19 Tim Gugus membagi zona penyebaran Covid-19 berdasarkan jumlah kasus positif. pembagian zona dengan menggunakan satu variabel yaitu positif menyebabkan penanganan Covid-19 tidak maksimal karena hanya terkonsentrasi pada zona dengan kasus positif yang terbanyak sedangkan potensi penyebaran bukan hanya dari kasus positif. Oleh karene itu, dibutuhkan teknik yang lain dapat mengelompokkan / cluster zona penyebaran Covid-19. Salah satu teknik yang sesuai untuk pengelompokkan / cluster yaitu algoritma clustering K-Medoids. Hasil dari implementasi algoritma Algoritma K-Medoids yaitu cluster zona penyebaran Covid-19 di Sumatera Utara dibagi dalam 3(tiga) Cluster yaitu cluster 1, cluster 2 dan cluster 3. Cluster 1 identik dengan zona merah, Cluster 2 identik dengan zona kuning dan cluster 3 identik dengan zona hijau. Abstract Covid-19 is a disease that attacks the human respiratory system and can be transmitted easily. North Sumatra is one of the areas hit by the Covid-19 pandemic. Through the Task Force for the Acceleration and Handling of Covid-19, the province of North Sumatra has made various efforts to prevent the spread of Covid-19, such as studying and worship at home, appealing to wear masks and so on. To make it easier to identify the spread of Covid-19, the Cluster Team divides the Covid-19 spread zones based on the number of positive cases. zoning by using one variable, namely positive, causes the handling of Covid-19 to be not optimal because it is only concentrated in the zone with the most positive cases, while the potential for spread is not only from positive cases. Therefore, another technique is needed to group / cluster the Covid-19 spread zones. One technique that is suitable for grouping / clustering is the K-Medoids clustering algorithm. The results of the implementation of the K-Medoids Algorithm algorithm, namely the Covid-19 spread zone cluster in North Sumatra is divided into 3 (three) clusters, namely cluster 1, cluster 2 and cluster 3. Cluster 1 is identical to the red zone, Cluster 2 is identical to the yellow zone and cluster 3 is identical to the green zone
Implementasi Matode Weighted Product Dalam Penentuan Aplikasi Tatap Muka Pembelajaran Daring Dimasa Pandemi Covid-19 Zega, Serta Kurniawan; Zai, Viktor Frank; Bu'ulolo, Efori
BEES: Bulletin of Electrical and Electronics Engineering Vol 4 No 1 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v4i2.3635

Abstract

The covid-19 pandemic as we have experienced lately has overwhelmed the community so that activities in various fields are hampered, one of which is in the field of education where the government shifts face-to-face learning to learning which can be done with various visual media such as Classroom, Zoom, Google Meet, E-learning and so on. Due to the large number of media that can be used for learning, a determination is needed to choose a face-to-face online learning application. In the determination, a system is needed, namely a decision support system where this system can provide efficient and objective decisions based on predetermined methods and data. , in this study determine the WP (Weighted Product) method as a decision-making tool which is part of the DSS method. And by setting 5 alternatives or applications that are calculated and determined the 5 criteria that are used as requirements in order to produce the right decision. So from the problems above, this study was made which discusses the implementation of the WP method in determining the application used for face-to-face during online learning during the covid-19 pandemic. Based on the implementation of this method, a face-to-face online learning application is produced, namely the A3 alternative, namely Elearning with a preference value of 0.341.
Algoritma K-Nearest Neighbor (K-NN) Dengan Normalisasi Max Min Untuk Menentukan Calon Mahasiswa Yang Layak Menerima KIP Kuliah Merdeka Bu'ulolo, Efori
Jurnal Sistem Informasi dan Sistem Komputer Vol 9 No 2 (2024): Vol 9 No 2 - 2024
Publisher : STIMIK Bina Bangsa Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51717/simkom.v9i2.445

Abstract

Calon mahasiswa penerima KIP Kuliah Merdeka pada Universitas Budi Darma tidak sebanding jumlahnya dengan kuota yang tersedia, sehingga kadang pengelola KIP Kuliah mengalami kesulitan dalam menentukan mahasiswa yang benar-benar layak menerima KIP Kuliah Merdeka atau yang tidak layak. Faktor lain adalah nilai ujian, prestasi, keadaan ekonomi dan lain sebagainya yang memiliki kemiripan. Untuk itu sangat diperlukan suatu teknik untuk menentukan calon mahasiswa yang layak menerima KIP Kuliah Merdeka, dan salah satu teknik dalam data mining yang sering digunakan adalah algoritma K-Nearest Neighbor (K-NN). Penggunaan normalisasi data untuk menghilangkan ketimbangan nilai antar kriteria dalam data. Perhitungan jarak dengan algoritma K-NN dengan normalisasi max min dan pegujian data dengan bahasa pemrograman python hasilnya adalah nilai class data yang baru berdasarkan nilai kedekatan nilai attribute data yang lama dengan data yang baru yang terdiri atas prestasi sekolah, hasil ujian, total penghasilan orang tua, mempunyai KKS dan kepemilikan rumah.
Pelatihan Dasar Rumus Ms. Excel Untuk Pembuatan Laporan Keuangan Syahputra, Rian; Bu'ulolo, Efori
ORAHUA : Jurnal Pengabdian Kepada Masyarakat Vol. 2 No. 01 (2024): Juli
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/orahua.v2i01.92

Abstract

Kebutuhan sekolah, banyak mata Pelajaran yang sudah bisa membantu dalam mempersiapkan setiap siswa dalam menghadapi dunia kerja, salah satunya adalah seperti mata Pelajaran ekonomi dan akuntansi yang mempelajari dasar dalam membuat laporan keuangan. Dalam pembuatan laporan bisa saja mengalami salah hitung karena masih menggunakan proses manual, maka untuk mengatasi masalah ini bisa menggunakan sebuah aplikasi pengolah angka. Salah satunya adalah menggunakan pengolah angka yaitu MS. Excel. Hal yang memerlukan aplikasi MS. Excel yaitu membuat laporan keuangan Dimana efektifitas dan efisiensi sangat diutamakan dalam pembuatan laporan tersebut.
Implementasi Algoritma K-Means dengan Normalisasi Sigmoidal Untuk Klastering Data Ternak Sapi Sari, Vingki Rapika; Buulolo, Efori; Fadlina
JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 2 No. 01 (2023): Desember
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/jikteks.v2i01.52

Abstract

Teknologi komputer pada zaman sekarang telah banyak dimanfaatkan dalam bidang statistika. Hal ini disebabkan oleh kecepatan komputasi dari komputer yang dapat memangkas waktu yang dibutuhkan untuk menghasilkan nilai akhir yang diinginkan. Salah satu pemanfaatan teknologi komputer adalah dalam pengelompokan data ternak sapi untuk menentukan sapi berkualitas baik dari beberapa shipment yang masuk dalam satu tahun. Algoritma K-Means merupakan suatu metode yang digunakan untuk mengelompokkan data ternak sapi berdasarkan jarak terdekat dan terpendek atau berdasarkan kesamaan karakteristik. Pengelompokan data ternak sapi menentukan kriteria bobot beli, bobot jual dengan proses perhitungan menggunakan normalisasi sigmoidal. Hasil yang diinginkan dari penelitian ini ialah Algoritma K-Means pada pengelompokkan data ternak sapi membantu para pekerja untuk menentukan sapi berkualitas baik, dengan adanya pengelompokan ini memberikan saran untuk membantu para pekerja dalam mengetahui kualitas sapi terbaik.
Outlier detection in the clustired data Bu'ulolo, Efori; Syahputra, Rian; Simorangkir, Elsya Sabrina Asmita
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 6 (2025): January : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2025.1005.pp394-404

Abstract

The purpose of this study is to detect outliers in data clusters. Outliers in data cluster datasets often occur in the data clustering process, especially in the K-Means algorithm. Outliers in cluster data are members/cluster items that are far from the centroid value and are not found in the dominant cluster. Outliers in cluster data are caused by various factors such as inaccurate K values, inaccurate centroid point values, poor data quality and others. To detect outliers in cluster data using the blox plot method, Z-Score and relative size factor (RSF). The input value is the sum of squared error (SSE), calculated by summing the squares of the distance of each data point from the cluster centroid. The dataset used consists of 3 (three) variances, namely high data variance, medium data variance and low data variance. The method used for outlier detection in this study can detect outliers in all data variances used, only not all outlier detection methods are optimal for all data variances. The plox plot method is optimal for high data variance and medium data variance, the RSF method is optimal for medium data variance and the Z-Score method is not optimal for high data variance.
Data Mining Sistem Stock Opname Bahan Baku Catering Makanan Sehat Menggunakan Metode Min Max Stock Kesuma, Chyntia; Buulolo, Efori; Hutabarat, Hukendik
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/bios.v1i1.33

Abstract

Competition in today's business world is increasing, there are more and more innovations made by every entrepreneur to increase sales of the products they make so that they can be accepted in the market and in the community. One of them is Healthy Food Medan, a company engaged in healthy food catering. In making healthy food, it is necessary to stock up on good raw materials, so that one day the company does not lack stock of raw materials. Healthy Food Medan itself will not be separated from the so-called stock taking of raw materials. Of course, it is very interesting to be used as research material. Because of this, a computer program was created to determine the stock of raw materials so that there is no shortage of raw materials. In the application with the Min-Max method, it is expected that the user will no longer have difficulties in terms of stock of raw materials. The Min-Max method itself is a method that determines the maximum amount of inventory and minimum inventory so that there are no shortages and excess goods. Aims to avoid excess and shortage of raw materials by calculating the amount of raw material inventory
Implementasi Algoritma K-Nearest Neighbor(K-NN) Dalam Klasifikasi Kredit Motor Bu’ulolo, Efori; Tampubolon, Irma Suryani; Nababan, Christin Vebiola; Nasution, Lulu Nurhidayanti
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/bios.v1i1.34

Abstract

Determining the eligibility of applying for a motorbike loan to a leasing company is important, considering that if an error in decision making occurs it will have an impact on the loss of the FIF Group company. Therefore the authors created a Decision Support System using the K-nearest Neighbor method to determine the feasibility of applying for a motorcycle loan. The K-Nearest Neighbor (K-NN) algorithm is an algorithm in data mining to classify new objects based on the majority of the nearest neighbor categories. The K-NN clustering algorithm using data on income, employment, number of dependents and home ownership can group prospective new creditors to make it easier for staff to determine acceptance of prospective new motorcycle creditors
Aplikasi View Remote Camera CCTV Dengan Android Untuk Monitoring Kegiatan Mahasiswa Dilaboratorium Komputer Pada STMIK Budidarma Medan Azanuddin, Azanuddin; Buulolo, Efori
Jurnal TIMES Vol 6 No 1 (2017)
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.983 KB) | DOI: 10.51351/jtm.6.1.2017555

Abstract

Sistem pemantauan yang umum dipakai, menggunakan kamera Closed Circuit Television (CCTV) yang dihubungkan dengan televisi atau komputer untuk menampilkan hasil capture kamera. Sistem ini mempunyai kelemahan hasil tangkapan kamera hanya dapat diakses dari tempat yang relatif dekat.  Untuk mengatasi masalah tersebut dibuat sebuah aplikasi yang mampu mengakses hasil capture kamera CCTV melalui handphone, yaitu monitoring kegiatan mahasiswa di laboratorium komputer dengan kamera CCTV yang dapat diakses dengan handphone menggunakan jaringan internet. Sehingga pengaksesan kamera CCTV bisa dari jarak yang relatif jauh dari posisi kamera berada. Pada aplikasi ini, kamera CCTV dihubungkan ke Digital Video Recording (DVR) untuk proses perekamannya, untuk proses pengaksesannya, handphone mengakses IP Publik atau DNS suatu modem internet yang modem tersebut sudah dihubungkan dengan perangkat DVR.
Co-Authors A M Hatuaon Sihite A, Azanuddin Afnita, Devi Afri Nirmalasari Halawa Ahmad Fachriansyah Alan Bangun Siregar Alexander Pamdapotan Manullang Alwin Fau Amatilah Nasution Andreas Gerhard Simorangkir Ardi Kusuma Ari Pradana Arif Budiman Azhar Azhar Benny Sinaga Bernadus Gunawan Sudarsono Bister Purba Buulolo, Ananoma Defiyuliyanti Bazikho Desi Simanjuntak Devi Afnita Devi Sari Oktavia Panggabean Dito Putro Utomo Edizal Hatmi Eko Firdonal Simamora Endang Rismawati Erlinda Simamora Ewit Purba Fadlina Fauziyah Fifto Nugroho Fince Tinus Waruwu Fince Tinus Waruwu Fince Tinus Waruwu Ginting, Fransiskus Ginting, Permanan Hasanah, Lailatun Hendra Gunawan Hosianna Saragih Hot Riris Siburian Hukendik Hutabarat Hukendik Hutabarat Hutabarat, Hukendik Hutabarat, Sumiaty Adelina Ikhwan Lubis Ikwan Lubis Imam Saputra Iskandar Zulkarnain Kesuma, Chyntia Khairunnisa Khairunnisa Kurnia Ulfa Laia, Delisman Laia, Delisman Lucius Yupiter Telaumbanua M. Ibrahim Maharani Maharani, Maharani Maringan Sianturi Matias Julyus Fika Sirait Mauhati Pardede Meryance V. Siagian Meryance Viorentina Siagian Mesran, Mesran Muasir Pagan Muhammad Abdul Rohim Muhammad Fahriat Muhammad Zarlis Mutiah Mutiah Nababan, Christin Vebiola Nainel, Yane Laheroi Naomi Labora Saragi Nasib Marbun Nasution, Lulu Nurhidayanti Natalia Silalahi Natalia Silalahi, Natalia Ndruru, Eferoni Nduru, Ewin Karman Nduru, Ewin Karman Nelly Astuti Hasibuan Noferianto Sitompul Nurdiyanto, Heri Ojahan Sihombing Permanan Ginting Pristiwanto, Pristiwanto Pristiwanto, Pristiwanto Purba, Bister Purba, Citra Verawati Rahmi Ras Fanny Reka Safarti Rian Syahputra Rico Albert Andika Saragih Rivalri Kristianto Hondro Rizky Meliani Astri Hasibuan Rohan Kristini Purba Saidi Ramadan Siregar Saragih, Hosianna Sari, Vingki Rapika Sarumaha, Lukas Siagian, Edward Robinson Sianturi, Lince T Siburian, Henry Kristian Sihombing, Ojahan Silalahi, Eci Marcelina Simorangkir, Elsya Sabrina Asmita Sinaga, Ali Sabany Sirait, Annisa Corry Nauli Siregar, Alan Bangun Siska Kristiana Simanullang Sitepu, Rahmad Dani Sitepu, Rahmad Dani Siti Maryam Soeb Aripin Sri Devi Manullang Suginam Surya Darma Nasution Sutiksno, Dian Utami Tampubolon, Irma Suryani Tampubolon, Tigor Barata Victor Gultom Vini Kristin Septiani Situmorang Wahyu Prismawan Wulan Juni Andari Yani, Ika Fitri Yosa`aro Zai Yuhandri Yuhandri, Yuhandri Zai, Evi Safyan Sari Zai, Viktor Frank Zega, Serta Kurniawan Zulkifli Nasution