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Perbaikan Fasilitas Kerja Area Finishing dengan Pendekatan Lean dan Metode MOST guna Meningkatkan Produktivitas PT. XYZ Prasetyo, Andiko; Puspanantasari Putri, Erni
Innovative: Journal Of Social Science Research Vol. 4 No. 6 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i6.16534

Abstract

XYZ is a company that produces paper products including the spiral division. The spiral finishing area has wasteful work areas including transportation waste, and movements that result in a lack of focus on work. The methods used are VSM, Nordic Body Map and MOST calculations. The results of processing data on the spiral division of the finishing section with an average book revision work per person produce one book revision unit taking a standard time of 60.23 seconds/pcs and in 7 working hours producing 1720 books for 4 operators, while after improving the work system with the proposed shelf design and placement as minimal as possible in the finishing area, the results were obtained for three revision operators 22.46 seconds/pcs revision, per person and one person for wire button work and quality check 15.41 seconds and in 7 working hours produces 2562 book revisions for 4 operators.
Pelatihan Pembuatan Barcode Paket Wisata Grand Watudodol Banyuwangi Ratna Mustika Yasi; Fathul Hadi, Charis; Fita Lestari, Riska; Arya T Candra; Prasetyo, Andiko
TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Vol. 2 No. 2 (2022): TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat
Publisher : Fakultas Teknik, Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tekiba.v2i2.2260

Abstract

Banyuwangi Regency is one of the participating districts in order to accelerate local economic growth through the tourism industry. Banyuwangi Regency has a very diverse appeal in the tourism sector. There are natural sights such as beaches, mountains, forests, national parks, culture, and others. Grand Watudodol Beach is a beach that has trip packages for water tourism to Menjangan Island and Tabuhan Island. The tour package is only focused on water travel, but the beach (costal) has not been explored much and the visitors just sit back and do not enjoy the natural resources available at Grand Watudodol. In the digital age, the use of technology as a means of promotion, especially for the world of tourism, has become one of the marketing strategies. One of the uses of this technology is the creation of tour package barcodes at Grand Watudodol. A bar code (or barcode) is a collection of data that can be read by a machine, this barcode works by the system collecting data in widths (lines) and space parallel lines which is referred to as a barcode or linear symbology. Based on the results of community service activities, it was found that the use of barcodes in the medium for conveying information on tour packages can attract buyers, especially the effectiveness in displaying package descriptions to make it easier and more efficient so that tourism business development can compete.
Model Decision Tree Forecasting Berbasis DHT22 pada Smart Hydroponic Microgreen Hadi, Charis Fathul; Yasi, Ratna Mustika; Prasetyo, Andiko
Journal of Telecommunication Electronics and Control Engineering (JTECE) Vol 6 No 1 (2024): Journal of Telecommunication, Electronics, and Control Engineering (JTECE)
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/jtece.v6i1.1218

Abstract

Sensor DHT22 diharuskan aktif selama 4 hari penuh, jika dilihat dari waktu rata-rata budidaya microgreen kacang hijau menggunakan smart hydroponic. Penggunaan sensor DHT22 dalam jangka waktu tertentu dapat mempengaruhi kestabilan jangka panjang dalam hal pembacaan suhu. Jika pembacaan DHT22 mulai tidak akurat, smart system tidak mampu bekerja maksimal. Peneliti mengusulkan sebuah sistem untuk menggantikan peran sensor tanpa mengurangi atau mengganggu kinerja dari smart system untuk mengurangi ketergantungan komponen elektronika seperti sensor suhu. Seiring kemajuan teknologi, terdapat salah satu model machine learning yang dapat diterapkan untuk menggantikan peran sensor yaitu prediksi suhu melalui forecasting. Algoritma forecasting yang digunakan adalah decision tree. Algoritma ini dipilih karena mampu memprediksi data hanya dengan satu jenis input data berupa waktu dengan proses pelatihan yang cukup cepat. Data latih dihasilkan dari perekaman data selama 4 hari pada smart hydroponic microgreen kacang hijau. Model akan dibuat menggunakan grid search cross validation dan feature scaling. Hasil penelitian menunjukkan channel 80 layak dipilih menjadi model prediksi. Prediksi suhu model decision tree forecasting menghasilkan nilai R-squared sebesar 0,870955 dan mean square error (MSE) sebesar 0,074171. Kedua nilai tersebut menunjukkan bahwa model cukup kuat dalam memprediksi suhu dan layak untuk diterapkan dalam memantau suhu smart hydroponic microgreen kacang hijau.