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All Journal Riau Journal of Computer Science JSAI (Journal Scientific and Applied Informatics) Zonasi: Jurnal Sistem Informasi
Budi Yanto, Budi
Program Studi Teknik Informatika Fakultas Ilmu Komputer Universitas Pasir Pangaraian Jl. Tuanku Tambusai, Kumu Kec. Rambah Hilir Kabupaten Rokan Hulu Telp, 081365929997
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Languange, Linguistic, Communication & Media

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Penerapan BARS (Behaviorally Anchor Rating Scale) Berbasis Web Dalam Penilaian Kinerja Karyawan Rouza, Erni; Yanto, Budi
ZONAsi: Jurnal Sistem Informasi Vol 1 No 2 (2019): Publikasi Artikel ZONAsi : Jurnal Sistem Informasi, September 2019
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v1i2.3400

Abstract

Universitas Pasir Pengaraian (UPP)  adalah salah satu kampus yang terletak di kabupaten Rokan Hulu Provinsi Riau, sebagai instansi yang bergerak dibidang pendidikan, tentunya UPP membutuhkan suatu model baru untuk penilaian kinerja karyawan dalam mengevalusi dan mengukur kinerja karyawan sehingga harapan dari yayasan dapat tercapai dengan baik. Saat ini proses penilaian dan pengukuran kinerja karyawan masih menggunakan sistem yang manual, belum adanya teknologi IT ataupun sistem informasi sebagai alat bantu yang digunakan untuk proses pengarsipan, pencarian data  dan  mempercepat  proses pelaporan penilaian kinerja karyawan baik itu perbulan, pertiga bulan, bahkan pertahun. Selain itu penyebab lainnya adalah  belum ada pengarsipan pelanggaran yang telah dilakukan oleh pegawai, sehingga pimpinan baik itu di Prodi, Dekan dan lembaga yang ada di Universitas Pasir Pengaraian tidak mempunyai data yang jelas untuk penegasan punishment pelanggar pegawai tersebut. Maka dari itu, tujuan penelitian ini sendiri yaitu menganalisa, merancang, dan membangun suatu sistem informasi baru untuk penilaian kinerja karyawan menggunakan teknik penilaian BARS ( Behaviorally Anchor Rating Scale) berbasis web. Hasil penelitian berupa suatu sistem informasi yang dinamakan SIPENTAJA, yang menggunakan metode penilaian Behaviorally  Anchor  Rating  Scale (BARS). Dengan sistem informasi penilaian kinerja karyawan (SIPENTAJA) ini dapat mempermudah para pimpinan dalam menilai dan melaporkan kinerja pegawai dengan cepat dan tepat.
PENERAPAN BARS (BEHAVIORALLY ANCHOR RATING SCALE) BERBASIS WEB DALAM PENILAIAN KINERJA KARYAWAN Rouza, Erni; Yanto, Budi
ZONAsi: Jurnal Sistem Informasi Vol 1 No 2 (2019): Publikasi Artikel ZONAsi : Jurnal Sistem Informasi, September 2019
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v1i2.3690

Abstract

Universitas Pasir Pengaraian (UPP) adalah salah satu kampus yang terletak di kabupaten Rokan Hulu Provinsi Riau, sebagai instansi yang bergerak dibidang pendidikan, tentunya UPP membutuhkan suatu model baru untuk penilaian kinerja karyawan dalam mengevalusi dan mengukur kinerja karyawan sehingga harapan dari yayasan dapat tercapai dengan baik. Saat ini proses penilaian dan pengukuran kinerja karyawan masih menggunakan sistem yang manual, belum adanya teknologi IT ataupun sistem informasi sebagai alat bantu yang digunakan untuk proses pengarsipan, pencarian data dan mempercepat proses pelaporan penilaian kinerja karyawan baik itu perbulan, pertiga bulan, bahkan pertahun. Selain itu penyebab lainnya adalah belum ada pengarsipan pelanggaran yang telah dilakukan oleh pegawai, sehingga pimpinan baik itu di Prodi, Dekan dan lembaga yang ada di Universitas Pasir Pengaraian tidak mempunyai data yang jelas untuk penegasan punishment pelanggar pegawai tersebut. Maka dari itu, tujuan penelitian ini sendiri yaitu menganalisa, merancang, dan membangun suatu sistem informasi baru untuk penilaian kinerja karyawan menggunakan teknik penilaian BARS ( Behaviorally Anchor Rating Scale) berbasis web. Hasil penelitian berupa suatu sistem informasi yang dinamakan SIPENTAJA, yang menggunakan metode penilaian Behaviorally Anchor Rating Scale (BARS). Dengan sistem informasi penilaian kinerja karyawan (SIPENTAJA) ini dapat mempermudah para pimpinan dalam menilai dan melaporkan kinerja pegawai dengan cepat dan tepat
ELEKTRONIK PEMBELAJARAN SEMESTER (E-RPS) BERBASIS WEB FAKULTAS ILMU KOMPUTER UNIVERSITAS PASIR PENGARAIAN Yanto, Budi; Sari, Rika Perma
Riau Journal Of Computer Science Vol. 5 No. 2 (2019): Riau Journal of Computer Science
Publisher : Riau Journal Of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (957.074 KB)

Abstract

The teaching plan is a guideline for the learning process which is then known as the Semester Learning Plan (RPS). Objectives should be clearly formulated to be achieved by the material or material to be taught, teaching and learning activities and tools used, evaluation and reference sources in the form of reading books. In the Faculty of Computer Science in filling out the Semester Learning Plan still using a manual system using Microsoft Word. Each Lecturer must fill in the Semester Learning Plan by typing Semester Learning Plan data according to the course taken on the form already made in Microsoft Word. Therefore, it is necessary to make the application of the Computer Science Learning Plan application. The E-RPS aims to make it easier for lecturers to fill out the Semester Learning Plan. The results of this practical work in the form of a website-based application that can facilitate the lecturer in filling out the Semester Learning Plan and with the lecturer no longer need to explain the contents of the Semester Learning Plan to students, because each student can see or print their own results according to the course what our want
Penerapan Metode Inferensi Fuzzy Takagi Sugeno-Kang Untuk Prediksi Hasil Panen Kelapa Sawit Yanto, Budi; Rouza, Erni; Saputra, Edi
Riau Journal Of Computer Science Vol. 5 No. 2 (2019): Riau Journal of Computer Science
Publisher : Riau Journal Of Computer Science

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

Abstract

Palm oil is one of the main crops and seeds in Indonesia. In oil palm plantations, oil palm crops are the most important things. Oil palm crops in the right time and quantity are what the farmers want. Therefore, harvest prediction is needed to be used as reference of palm oil harvest target. Determination of harvest targets required a method that is able to predict the yield of oil palm. In this research, built a system of fuzzy inference with TSK method (Takagi Sugeno Kang), which aims to predict the yield of oil palm farmers. The fuzzy rules in the form of IF antecedent THEN are consequent, using consequent linear equations of the input variables. The coefficients of each variable of linear equation are consequently derived based on the expected yield of the harvest. The results of prediction testing of Palm Oil harvest production in 3 seasons, namely Dry Season, Rainy Season, Fertilization, input the number by values of variable with to the given range prove that the fuzzy inference of the TSK method can calculate palm oil crop predictions well.
INDENTIFIKASI POLA AKSARA ARAB MELAYU DENGAN JARINGAN SYARAF TIRUAN CONVOLUTIONAL NEURAL NETWORK (CNN) Yanto, Budi; -, Basorudin; -, Jufri; Hayadi, B.Herawan
JSAI (Journal Scientific and Applied Informatics) Vol 3, No 3 (2020): Informatics Science and Implementation
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v3i3.1151

Abstract

Riau province has Malay Arabic script as a traditional cultural heritage of ancient characters that should be preserved; this script is adapted from Arabic writing. This script from Malay Arabic has a unique form that is different from the original Arabic writing adaptation, which is read in a combination of letters forming latin meanings as an introduction to the everyday language of Riau Malay people in the earlier kingdom. Malay Arabic writing became an introduction to the local content of traditional languages in schools. To foster a love for preserving culture, in accordance with current technology that is able to recognize scripting patterns when written in paper, a knowledge base was created by using Matlab software by applying a convolutional Neural Network (CNN) artificial neural network algorithm capable of recognizing script patterns well. The result of image input in the form of handwriting written on paper then in the scanner in the form of JPEG image format. Testing was carried out on four Arabic Malay characters namely alif, ha, la, kho and nun. The result of training for the letter alif (a) epoch is obtained 98 out of 100 iterations with a training length of 3 seconds, furthermore, in validation performance with a result of 0.25013 on epoch 92 of 98 epoch for gradient letters with a value of 0.0071991 on the next epoch 98 in the extras produces an accuracy value of 0.6548 which states the correct result accordingness because it is close to the alif script. In the process of train input the letter kho obtained epoch 80 out of 100 iterations with a training process for 3 seconds, validation performance 0.25153 on epoch 74 out of 80 epoch for check validation with a value of 0.0011682 on the next epoch 80 in the extras obtained an extra value of 0.9326 stated the value is incorrect. Because the result of the extras results in an image that does not come close to the kho letter. Therefore, a study of how the system can recognize Malay Arabic writing patterns with the Convolutional Neural Network (CNN) method because it is very good at identifying image pattern features with an accuracy value of 4.12% of the 10 sample image patterns that have been inputted. With the introduction of imagery patterns from the extraction of features scanned Malay Arabic characters can help the findings of ancient Malay Arabic script as morphological learning of the validity of abstraction of Malay Arabic script is good
Co-Authors -, Basorudin agung setiawan Ali Djamhuri EDI SAPUTRA Erni Rouza, Erni Hayadi, B.Herawan Jufri -, Jufri Kiki Yasdomi Sari, Rika Perma