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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Simetris MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Prosiding SNATIKA Vol 01 (2011) Nusanatara of Engineering JOIN (Jurnal Online Informatika) Creative Information Technology Journal Applied Information System and Management Generation Journal Teknika Nusantara of Engineering (NOE) J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Journal of Research on Community Engagement
Fajar Rohman Hariri
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Transportation

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Klasifikasi Jenis Golongan Darah Menggunakan Fuzzy C-Means Clustering (FCM) dan Learning Vector Quantization (LVQ) Hariri, Fajar Rohman
MATICS Vol 10, No 1 (2018): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.709 KB) | DOI: 10.18860/mat.v10i1.5356

Abstract

Abstract— Blood is an important part of the body. Blood is divided into several groups A, B, O, and AB. Conventionally, detect blood group by dripping anti-A serum and anti-B serum into the blood to be recognized and direct measurement of the serum droplet reaction. This study will compare the processes that use segmentation and  without using segmentation to know the various segmentation information in introduction of human blood type image. From the test results that segmentation increase accuracy of recognition between 10% -24% of each test. By using JST Learning Vector Quantization (LVQ) as a classifier and Fuzzy C-Mean as segmentation, the optimal result on the system averages 92% to 98%.. Index Terms—Blood, Segmentation, Classification Abstrak–- Darah merupakan salah satu bagian penting dalam tubuh. Darah dibedakan menjadi beberapa golongan yaitu A, B, O, dan AB. Secara konvensional, mendeteksi golongan darah dengan cara meneteskan serum anti-A dan serum anti-B ke darah yang akan dikenali kemudian melakukan pengamatan langsung terhadap reaksi tetesan serum tersebut.  Penelitian ini akan membandingkan antara proses pengenalan yang menggunakan segmentasi dengan proses pengenalan tanpa menggunakan segmentasi untuk mengetahui seberapa besar pengaruh metode segmentasi dalam pengenalan citra golongan darah manusia. Dari hasil pengujian didapatkan bahwa dengan adanya metode segmentasi akurasi system pengenalan bertambah antara 10%-24% setiap uji coba. Dengan menggunakan JST Learning Vector Quantization (LVQ) sebagai pengklasifikasi dan Fuzzy C-Mean sebagai segmentasi citra darah dapat diperoleh hasil yang optimal pada sistem pengenala golongan darah manusia dengan prosentase keberhasilan rata rata 92% hingga 98%. Kata Kunci—Darah, Segmentasi, Klasifikasi Klasifikasi Jenis Golongan Darah MenggunakanFuzzy C-Means Clustering (FCM) dan Learning Vector Quantization (LVQ)
Pendekatan Box - Whisker Plot dan Regresi Liniear untuk Prediksi User Upgrade pada Start Up ayocpns Basid, Puspa Miladin Nuraida Safitri A; Rohman Hariri, Fajar
MATICS Vol 12, No 1 (2020): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (445.603 KB) | DOI: 10.18860/mat.v12i1.8932

Abstract

Munculnya banyak start up di indonesia mulai menjadi bagian penting dari perekonomian sebuah negara. Dalam pelaksanaanya perusahaan rintisan seperti ini masih berkembang dan membutuhkan banyak pendanaan untuk operasionalnya. Sehingga para perusahaan rintisan ini perlu memikirkan langkah untuk berkembang lagi. Selain melalui investor, merka juga melakukan langkah promosi untuk menarik user. Untuk melakukan promosi itu sendiri, perusahaan rintisan ini perlu memperhatikan bagaimana dampak dari promosi yang telah dilakukan. Sudah cukup atau belum, hal tersebut dapat di lihat dari jumlah user perharinya. Selain itu memprediksi user yang akan upgrade accont premium juga perlu dilakukan. Penelitian ini telah menghasilkan persamaan untuk melakukan prediksi tersebut dengan menggunakan metode regresi linier dan Box-Whisker Plot.
Chicken Menu Sales Forecasting System using Multiplicative Holt-Winters Triple Exponential Smoothing Fajar Rohman Hariri; Johan Ericka Wahyu Prakasa
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 1 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i1.21103

Abstract

Forecasting is an art and a science predict events that will occur in the future based on data in the past. The ability of the restaurant in Management shows success in taking advantage of business opportunities optimal for interpreting past performance and planning for the future. This research uses Triple HoltWinters Exponential Smoothing Multiplicative method for sales forecasting.  Multiplicative Holt-Winters Triple Exponential Smoothing Method has the smallest percentage error (PE) of 9.946% with parameter values (α=0.1, β=0.1, ϒ=0.3). While the largest percentage error (PE) is obtained Multiplicative models with parameter values (α=0.3, β=0.3, ϒ=0.1) produce percentage error (PE) value of 11.879%. Menu sales forecasting results chickens using the Holt-Winters Triple Exponential Smoothing Method Multiplicative in the next month using parameter values (α=0.1, β=0.1, ϒ=0.3) is 4782 pcs.
Chicken Menu Sales Forecasting System using Multiplicative Holt-Winters Triple Exponential Smoothing Hariri, Fajar Rohman; Prakasa, Johan Ericka Wahyu
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 1 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i1.21103

Abstract

Forecasting is an art and a science predict events that will occur in the future based on data in the past. The ability of the restaurant in Management shows success in taking advantage of business opportunities optimal for interpreting past performance and planning for the future. This research uses Triple HoltWinters Exponential Smoothing Multiplicative method for sales forecasting.  Multiplicative Holt-Winters Triple Exponential Smoothing Method has the smallest percentage error (PE) of 9.946% with parameter values (α=0.1, β=0.1, ϒ=0.3). While the largest percentage error (PE) is obtained Multiplicative models with parameter values (α=0.3, β=0.3, ϒ=0.1) produce percentage error (PE) value of 11.879%. Menu sales forecasting results chickens using the Holt-Winters Triple Exponential Smoothing Method Multiplicative in the next month using parameter values (α=0.1, β=0.1, ϒ=0.3) is 4782 pcs.
Co-Authors Agus Mukti Wibowo Ajib Hanani Armadyah Amborowati Danar Putra Pamungkas, Danar Putra Ema Utami Johan Ericka Wahyu Prakasa Lingga Wahyu Rochim Mashuri, Chamdan Prastyo, Edwin Hari Agus Puspa Miladin Nuraida Safitri A. Basid Ratih Kumalasari Niswatin Risky Aswi R, Risky Rizki Amelia Sari, Waskita Shoffin Nahwa Utama Syauqi, Ala Vivi Wahyuni, Vivi