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Journal : Petir

Penetapan Instruktur Diklat Menggunakan Metode Clustering K-Means dan Topsis Pada PT PLN (Persero) Udiklat Jakarta Nurul Dyah Budiana; Riki Ruli A. Siregar; Meilia Nur Indah Susanti
PETIR Vol 12 No 2 (2019): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (515.633 KB) | DOI: 10.33322/petir.v12i2.454

Abstract

Instructor is the main aspect that exists in the implementation of the training. The increasing number of instructors and the need for training is also increasing every year there is no system that can help the process of determining quickly and precisely. In need of a method that can classify the instructor data in accordance with the title of training materials and can be assigned instructor each of the training materials and do not ignore aspects of assessment of the instructor. In this study data mining techniques are used to help recommend instructors for each subject matter of the training based on the cluster data group approach. So it can be used in determining the instructor's assignment per training materials in the future. K-Means clustering method is used to group data into clusters by looking at the centroid value that has been determined. And the Topsis method is used to assign one instructor's name through the rankings of preference values. In this research CRISP-DM method is used as software engineering method system work done in sequence or linearly. In the testing process has been generated if the manual data and data processing if the application system is the same. This application to facilitate the Supervisor and Learning Development staff in setting instructors per training materials.
RANCANG BANGUN APLIKASI MONITORING PENCADANGAN DAYA LISTRIK DENGAN MEMANFAATKAN TENAGA KINCIR ANGIN Meilia Nur Indah Susanti
PETIR Vol 8 No 2 (2015): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10361.203 KB)

Abstract

Wind power plant is a power plant that uses wind as an energy source to produce electricalenergy. This generator can convert wind energy into electrical energy using a wind turbine orwindmill. Power generation system using wind as an energy source is an alternative system that isgrowing rapidly, considering wind energy is one that is not limited in nature.Computer technology is a part of human life and society today, even basically technology ingeneral and computers in particular is one of the primary means for people to improve their qualityof life. Technological developments lately running so fast, and computer technology including veryfast reaching up in almost all aspects of life so that eras experts now call it the computerized era.Computer technology can be used for field electrical one of them to do the monitoring.Computer engineering includes system design hardware and computer programs. Where the latterelectrical energy generated from the wind before being used will be stored in advance in thebattery, in this research by using application monitoring to determine how much current is enteredby using the current sensor and a voltage sensor to determine the current out using arduino.
Prediksi Kuota Pemesanan Bahan Bakar Pada SPBU dengan Metode Regresi Linear Berganda Abdurrasyid Abdurrasyid; Indrianto Indrianto; Meilia Nur Indah Susanti
PETIR Vol 14 No 2 (2021): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/petir.v14i2.1142

Abstract

Bahan bakar minyak menjadi komoditi penting dalam menjalankan roda perekonomian suatu negara, data Badan Pengatur Hilir Minyak dan Gas(BPH MIGAS) mencatat Indonesia menghabiskan 28,25 juta kiloliter selama tahun 2019, angka ini dihimpun dari seluruh Stasiun Pengisian Bahan Bakar Umum (SPBU) yang menjadi hilir distribusi BBM kepada masyarakat, namun disisi lain SPBU sering kehabisan stok karna kurangnya pengendalian terhadap stok, dampaknya adalah antrian panjang masyarakat di SPBU, bagi SPBU yang kehabisan stok jelas akan mengurangi pemasukan karna delay tidak ada penjualan selama proses pengiriman dari hulu ke hilir, maka dibutuhkan adanya sistem yang mampu membantu memprediksi berapa kuota yang harus dipesan sehingga kondisi out of stock tidak terjadi, untuk melakukan peramalan kuota bahan bakar digunakan metode regresi linier berganda yang terdiri dari variabel independent stok sisa (X1), stok masuk (X2) dan variabel dependent stok keluar (Y). Setelah dilakukan uji asumsi klasik dapat disimpulkan bahwa variabel independent (X1 dan X2) berpengaruh positif terhadap variabel dependent (Y). Dari hasil pengujian tingkat error menggunakan metode MAPE (Mean Absolute Percent Error) diperoleh tingkat error untuk peramalan pertalite selama seminggu sebesar 11,0% dan untuk tingkat error peramalan solar sebesar 13,2%.