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All Journal Jurnal Industri dan Teknologi Samawa (JITSA) Hexagon

Sis Yanti Arisma

Universitas Teknologi Sumbawa

Author-ID : 5327154

Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Industrial & Manufacturing Engineering

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ANALISA & ESTIMASI PENURUNAN RISIKO DENGAN JOB SAFETY ANALYSIS PADA DEPARTEMEN WAREHOUSE DI PT. AMMAN MINERAL NUSA TENGGARA Sis Yanti Arisma; Ismi Mashabai
JURNAL INDUSTRI DAN TEKNOLOGI SAMAWA Vol 1 No 1 (2020): JITSA
Publisher : Program Studi Teknik Industri, Fakultas Rekayasa Sistem

Setiap kegiatan maupun pekerjaan pasti memiliki resiko kecelakaan kerja. Kecelakaan tersebut dipengaruhi beberapa faktor seperti keadaan yang tidak aman, tindakan pekerja yang tidak aman, maupun kondisi fisik pekerja. Keselamatan para pekerja menjadi tanggung jawab Perusahaan. Penanggulangan terhadapat resiko terjadinya kecelakaan perlu di tanggulangi dan mejadi perhatian perusahaan. Salah satu metode yang dapat digunakan dalam persoalan tersebut adalah Job safety analisis (JSA), yaitu teknik manajemen keselamatan yang berfokus pada identifikasi bahaya dan pengendalian bahaya yang berhubungan dengan rangkaian pekerjaan atau tugas yang hendak dilakukan. Job safety analisis (JSA) tidak hanya membantu mencegah pekerja dari kecelakaan kerja, tetapi juga melindungi peralatan kerja dari kerusakan. Job safety analisis (JSA) adalah teknik manajemen keselamatan yang berfokus pada identifikasi bahaya dan pengendalian bahaya yang berhubungan dengan rangkaian pekerjaan atau tugas yang hendak dilakukan.

PERAMALAN JUMLAH PENJUALAN SEPEDA MOTOR MENGGUNAKAN METODE TIME SERIES STUDI KASUS: DEALER MOTOR NUSANTARA SURYA SAKTI (NSS) SUMBAWA Silvia Firda Utami; Sis Yanti Arisma; Koko Hermanto; Eki Ruskartina
Hexagon Jurnal Teknik dan Sains Vol 1 No 2 (2020): HEXAGON - Edisi 2
Publisher : Fakultas Teknologi Lingkungan dan Mineral - Universitas Teknologi Sumbawa

Nusantara Sakti Sumbawa (NSS) is a Honda agent company which sells motorcycles. The company encounters difficulty in determining the monthly sales target of their products. Therefore, the study aims to investigate the appropriate methodology to estimate the sales target for the next five months in NSS by involving 13 different brands of Honda. To achieve the goal, the researcher conducted several stages in forecasting methodology, including collecting the previous sales data of the company, plotting the collected data, and identifying the proper methods of forecasting to analyse the data. Based on the plotting data process, the researcher found that the Time Series methodology, consisting of Single Moving Average and Single Exponential Smoothing was the most suitable method to analyse the data. The results of the study showed that the prediction for the future sales target of the 13 different brands of Honda in the next five months in NSS was 182 units in total (Beat Sporty CW: 35 units, Beat street: 19 units, Vario 110: 14 units, Vario 125: 17 units, Vario 150: 15 units, Scoopy: 38 units, Revo: 1 unit, Blade: 1 unit, Supra X 125: 12 units, Supra GTR 150: 9 units, Sonic: 16 units, and CBR150R: 5 units). The study also revealed that the Single moving average was a proper method to predict the future sales target for the three brands of Honda, namely Vario 110, Revo, and Blade. While the other 10 brands, including Beat Sporty CW, Beat street, Vario 125, Vario 150, Scoopy, Supra X 125, GTR 150, Sonic, and CBR150R were appropriately predicted using the Single Exponential Smoothing method.

Co-Authors Eki Ruskartina Firda Utami, Silvia Hermanto, Koko Ismi Mashabai

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