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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Ilmiah Teknik Industri PERFORMA : Media Ilmiah Teknik Industri Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri SEMAR
Yusuf Priyandari
Jurusan Teknik Industri, Fakultas Teknik, Universitas Sebelas Maret Jl. Ir Sutami No. 36A, Surakarta, Indonesia 57126
Humanities Computer Science & IT Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Prototipe Alat Pemantauan Suhu untuk Rantai Dingin Produk Mengunakan Near Field Communication, Studi Kasus Distribusi Darah Priyandari, Yusuf; Suletra, I Wayan; Mas’ud, Azmi; Pujiharto, Adi Norrochmat
Jurnal Ilmiah Teknik Industri Vol. 16, No. 2, Desember 2017
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v16i2.3880

Abstract

Temperature monitoring apparatus is required for the distribution of certain products that are distributed using cold chain method. Temperature gauges that use analog and digital thermometers can not store temperature data in transit. The digital temperature register apparatus (logger) in the market temperature is relatively expensive and does not provide early warning if the temperature in the storage box products out of permitted temperature limits. The research developed a prototype of a temperature monitoring device for the distribution of cold chain products. Case studies on blood distribution are used as a basis for determining the need for temperature monitoring devices. The product prototype is made by stages in accordance with generic product development method. The resulting prototype can provide temperature information in the cold box during the course of blood distribution. The prototype can also provide warnings in the form of sounds and lights when the temperature inside the cold box is outside the ideal temperature limit / permitted for the blood distribution process. Temperature history data during the trip can be stored in NFC Tags. The data can then be read using smart-phone devices that feature NFC.
Redesign of OrthoLPPDUNS External Fixation for Bone Reconstruction Using the Function Analysis System Technique (FAST) Method Herdiman, Lobes; Priadythama, Ilham; Susmartini, Susy; Priyandari, Yusuf; Murdiyantara, I Nyoman Suci Anindya; Apriani, Durkes Herlina
Jurnal Ilmiah Teknik Industri Vol. 19, No. 02, December 2020
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v19i2.10732

Abstract

Taylor Spatial Frame (TSF) better known as an external fixation product from several types of fixation devices in the orthopedic field. The Laboratory of Product Planning and Design has manufactured TSF or called OrthoLPPDUNS external fixations. The OrthoLPPDUNS design found that frame instability forming ring-strut angles caused by strut screw rotations was feeling rough due to backlash. The purpose is how to redesign an OrthoLPPDUNS with a Function Analysis System Technique (FAST). FAST method is applied at each stage of starting from the information stage to the interpretation of the results. The OrthoLPPDUNS design with the joint system uses custom components that cause weakness in frame stability. The use of standard components in joint systems can provide solutions to external fixations, although there are still weaknesses in the ring-strut angle. The OrthoLPPDUNS redesign has a better success rate in terms of stability parameters, allowing more precise bone reconstruction.
Causal Inference to Predict Delayed Arrival of Ordered Production Materials at PT. XYZ Hanura, Muhammad Ridzky; Priyandari, Yusuf; Hisjam, Muhammad
Jurnal Ilmiah Teknik Industri Vol. 22, No. 2, December 2023
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v22i2.23020

Abstract

PT XYZ has a problem with the delayed arrival of ordered production materials. Although the company is aware of the delays based on data, the company does not yet know the causes or sources of problems that cause delays. On the other hand, not all factors can be controlled to reduce the delay in the arrival of production materials. The company intends to predict the change in delay time if control or intervention is carried out on certain factors by utilising data availability. The factor to be treated is requisition-to-order lead time A causal inference model is used using the Dowhy library (a Python library for causal inference by graphing the model, quantitatively evaluating causal effects, and validating the causal assumptions) to estimate the quantitative causal effect between requisition-to-order lead time and the arrival time of the ordered material by considering other factors that also affect the delay. The results of the causal effect estimation are that by intervening or controlling the requisition-to-order lead time factor by one day, there is a decrease in the average delay in material arrival time by one day
Desain Dashboard untuk Penyajian Informasi Publik Rumah Sakit berbasis Indikator Kinerja dan Evaluasi Dashboard Menggunakan Short-User Experience Questionnaire Priyandari, Yusuf; Setyoko, Rio Detri; Pujiyanto, Eko; Wicaksono, Hendro
Techno.Com Vol. 24 No. 2 (2025): Mei 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i2.12804

Abstract

Undang-Undang Nomor 14 Tahun 2008 tentang keterbukaan informasi publik mengatur setiap badan publik, termasuk rumah sakit pemerintah, membuka akses atas informasi publik. Sayangnya, informasi publik berupa kinerja rumah sakit hanya dapat diakses dalam format dokumen pdf dan spreadsheet melalui website internal rumah sakit dan website tertentu di tingkat provinsi, serta belum terorganisir dengan baik. Oleh karena itu, penelitian ini mengajukan sebuah rancangan aplikasi dashboard standar bagi semua rumah sakit di sebuah provinsi. Metode perancangan dilakukan dalam empat tahapan, yakni diagnosis sistem, analisis kebutuhan, pembuatan dashboard, dan evaluasi hasil rancangan. Pada setiap tahapan terdapat aktivitas dan secara khusus pada tahapan evaluasi digunakan Short - User Experience Questionnaire (UEQ-S). Hasil rancangan dashboard mampu menyajikan visualisasi informasi terhadap tujuh indikator kinerja rumah sakit sebagai informasi publik untuk tiga kategori pengguna, yakni akademisi perguruan tinggi, pimpinan/staff lembaga eksekutif/legislatif, dan peneliti/media independen. Berdasarkan respon pengalaman pengguna, diketahui bahwa dashboard telah mencapai tujuannya sebagai sebuah aplikasi untuk menyajikan informasi publik, pengguna merasa senang dan nyaman menggunakan dashboard, dan secara keseluruhan kesan pengguna terhadap sistem dashboard sangat baik. Hal ini terlihat dari hasil kuisioner UEQ-S bahwa impresi pengalaman pengguna yang menunjukkan bahwa kualitas pragmatis dashboard dinilai baik (good), kualitas hedonis dinilai sangat baik (excelent) dan secara keseluruhan sistem dashboard dinilai sangat baik (excelent).
Causal Inference to Predict Delayed Arrival of Ordered Production Materials at PT. XYZ Hanura, Muhammad Ridzky; Priyandari, Yusuf; Hisjam, Muhammad
Jurnal Ilmiah Teknik Industri Vol. 22, No. 2, December 2023
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v22i2.23020

Abstract

PT XYZ has a problem with the delayed arrival of ordered production materials. Although the company is aware of the delays based on data, the company does not yet know the causes or sources of problems that cause delays. On the other hand, not all factors can be controlled to reduce the delay in the arrival of production materials. The company intends to predict the change in delay time if control or intervention is carried out on certain factors by utilising data availability. The factor to be treated is requisition-to-order lead time A causal inference model is used using the Dowhy library (a Python library for causal inference by graphing the model, quantitatively evaluating causal effects, and validating the causal assumptions) to estimate the quantitative causal effect between requisition-to-order lead time and the arrival time of the ordered material by considering other factors that also affect the delay. The results of the causal effect estimation are that by intervening or controlling the requisition-to-order lead time factor by one day, there is a decrease in the average delay in material arrival time by one day
Multi-Objective Optimization of Machining Parameters for Multi-Pass CNC Turning to Minimize Carbon Emissions, Energy, Noise and Cost Fittamami, Bening Maulina; Pujiyanto, Eko; Priyandari, Yusuf
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 23 No. 1 (2021): June 2021
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.23.1.25-34

Abstract

Global warming is a huge environmental issue today. This is due to the high level of world carbon emissions. The manufacturing process accounts for 30% of the world's carbon emissions production.  Sustainable manufacturing is necessary to implement to reduce carbon emission levels caused by the manufacturing process. There are three aspects of sustainable manufacturing, namely environmental aspects, economic aspects, and social aspects. These three aspects can be implemented in the machining process by optimizing machining parameters in multi-pass CNC turning. This research aims to optimize CNC turning machining parameters by considering energy consumption, carbon emissions, noise, and production cost. The model is solved using a Multi-objective Genetic Algorithm in Matlab 2016b then the transformation and weighting functions are carried out from the feasible value. Based on the optimization results, the total energy consumption value obtained is 2.50 MJ; total production cost is $ 2.19; total carbon emissions are 5.97 kgCO2, and noise is 236, 19 dB. The sensitivity analysis exhibits the machining parameters that affect the objective function: The cutting speed parameter and the feed rate parameter. This model can be used to improve the manufacturing process and support sustainable manufacturing.
Peramalan Penjualan Sediaan Farmasi Menggunakan Long Short-term Memory: Studi Kasus pada Apotik Suganda Anshory, Maulana Ichwan; Priyandari, Yusuf; Yuniaristanto, Yuniaristanto
Performa: Media Ilmiah Teknik Industri Vol 19, No 2 (2020): Performa: Media Ilmiah Teknik Industri
Publisher : Industrial Engineering, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/performa.19.2.45962

Abstract

Peramalan data penjualan berperan penting dalam optimisasi persediaan produk pada bisnis retail. Apotek adalah satu bentuk bisnis retail yang menjual sediaan farmasi (obat, bahan obat, obat tradisional dan kosmetika), alat kesehatan, dan bahan medis habis pakai. Apotek Suganda yang berlokasi di Kabupaten Sragen, melakukan penentuan rencana pengisian kembali (pembelian) sediaan farmasi dengan manual berbasis kebiasaan semata. Mekanisme tersebut terkadang menyebabkan terjadinya kekurangan persediaan obat. Oleh karena itu, untuk memperbaiki perencanaan pembelian, perlu dilakukan peramalan permintaan sediaan farmasi. Beberapa metode dujikan untuk melakukan peramalan permintaan, salah satunya menggunakan metode Long Short-term Memory (LSTM), yakni suatu metode berbasis machine learning. Bersama dengan métode-metode lainya yakni Least Square, Single exponential Smoothing, Double exponential Smoothing, Triple Exponential Smoothing, Winter Exponential Smoothing, Weight Moving Average, dan ARIMA, peramalan penjualan sediaan farmasi dilakukan. Hasil pengujian menunjukkan bahwa peramalan penjualan sediaan farmasi secara mingguan yang menggunakan LSTM memiliki Mean Absolute Percentage Error (MAPE) yang paling rendah dibanding metode lainnya. Dengan demikian, implementasi peramalan penjualan berbasis machine learning perlu dimanfaatkan, salah satunya dengan membuat modul peramalan untuk diintegrasikan dengan aplikasi penjualan yang dimiliki oleh apotek tersebut.
Perancangan Dashboard Performansi di Bidang Kemahasiswaan dan Lulusan Murtiastuti, Noviana Dwi; Liquiddanu, Eko; Priyandari, Yusuf
Performa: Media Ilmiah Teknik Industri Vol 22, No 2 (2023): Performa: Media Ilmiah Teknik Industri
Publisher : Industrial Engineering, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/performa.22.2.80764

Abstract

Higher education institutions often face a number of challenges in managing data and reporting information effectively, such as limited availability and distribution of information. This also happened in the Industrial Engineering Study Program at Sebelas Maret University (PSTI UNS). PSTI UNS needs a performance monitoring platform for study programs in the field of student and graduate affairs to support study program management and quality assurance activities. The information system currently provided by UNS is not yet able to complete PSTI's needs for monitoring and quality assurance functions at the study program level. A solution that has been proven to be able to solve similar problems is through the use of an information dashboard or dashboard. The unavailability of dashboards and PSTI's urgent need for study program performance monitoring activities led this research to design a dashboard in accordance with PSTI's needs and ensure that the design developed could be used immediately. To ensure the success of the design, this research uses a user-centric method in the design process and heuristic usability testing as an evaluation stage. This research produced a dashboard design, data filling template, and a guidebook that was used to make dashboard use easier. The successfully designed dashboard has more complete study program level information from the information system provided by UNS and has succeeded in meeting the needs of PSTI users with a user satisfaction level of 7.6. Based on the level of implementation readiness, this dashboard scored 86.83% for its usability test with minor problems. The root of the problem identified has been found and repaired.
Analisis Alternatif Solusi Proyek TI Dengan Analytical Network Process & Best Worst Method Faizal, Muhammad; Priyandari, Yusuf; Rosyidi, Cucuk Nur
Performa: Media Ilmiah Teknik Industri Vol 21, No 2 (2022): Performa: Media Ilmiah Teknik Industri
Publisher : Industrial Engineering, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/performa.21.2.59846

Abstract

Teknologi Informasi saat ini mempunyai peranan penting dalam organisasi. Salah satunya agar manajemen organisasi menjadi lebih efektif dan efisien dalam pengambilan keputusan. Dalam pengembangannya terdapat proyek-proyek teknologi informasi yang sukses dan juga proyek teknologi informasi yang mengalami kegagalan. Kegagalan dalam mengelola proyek teknologi informasi ini juga dialami oleh CV. Kadang Koding. Tujuan dari penelitian ini adalah mengidentifikasi penyebab kegagalan proyek teknologi informasi serta menentukan alternatif solusi terbaik yang dapat diterapkan segera oleh perusahaan. Hasil dari penelitian ini terpilih 5 sub kriteria yang memenuhi ambang batas(threshold) dalam penyebab kegagalan proyek TI. Threshold ditentukan peneliti dengan mengambil nilai Q3 (Quartile 3) sebagai nilai batas yaitu 0,121753. Metode Analytical Network Process digunakan untuk pemilihan sub kriteria paling berpengaruh. Sub kriteria paling berpengaruh dalam kegagalan proyek TI adalah E23 (perbedaan teknologi yang digunakan) dengan nilai prioritas akhir sebesar 0,169023. Pengolahan data alternatif solusi menggunakan Best Worst Method. Hasil pengolahan data tersebut didapatkan alternatif solusi terbaik yang diterapkan oleh perusahaan. Alternatif solusi terbaik adalah alternatif solusi 1 (Persyaratan dan ruang lingkup harus didefinisikan dengan jelas oleh manajer proyek sebelum meluncurkan proyek) dengan nilai prioritas akhir sebesar 0,950755.
Implementasi Deep Learning Menggunakan Metode Convolutional Neural Network untuk Mendeteksi Kehalaln pada Kosmetik Qonita, Hafsah; Laksono, Pringgo Widyo; Priyandari, Yusuf
Performa: Media Ilmiah Teknik Industri Vol 22, No 1 (2023): Performa: Media Ilmiah Teknik Industri
Publisher : Industrial Engineering, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/performa.22.1.76650

Abstract

The growth rate of the cosmetics industry shows good development, reaching 9.39% in 2020. With so many cosmetic products in the market, consumers must be more careful in choosing the cosmetic products. In addition to the safety factor, the halalness of cosmetics also needs to be considered, especially for Muslim consumers. This research aims to create a halal detection model in cosmetics by implementing one of the deep learning methods, namely convolutional neural network (CNN). .Previous research has successfully created a halal detection model on Korean cosmetics using CNN with an accuracy rate of 95.56%. This research intends to develop previous research by adding classes and the number of datasets. CNN will be used to create a halal detection model in cosmetics by learning the input features in the form of the image of cosmetic ingredient to determine its halalness. Classification is done based on two classes, which are Halal and Shubhat. The results show that the CNN model gets an accuracy value of 98.66% with a loss of 0.0615 in classifying the halalness of cosmetics. Model testing using the testing dataset gets an accuracy value of 98.67%. The F1-score value in each class is 98.66% for the halal class and 98.67 for the shubhat class. The CNN model that has been created is appropriate because it shows high accuracy and low loss on training, validation, and testing data without experiencing overfitting or underfitting,
Co-Authors Alfian Destha Joanda Alfian Destha Joanda Anshory, Maulana Ichwan Apriani, Durkes Herlina Cahyaningrum, Fransiska Endah Cucuk Nur Rosyidi Eko Liquiddanu Fakhrina Fahma Fittamami, Bening Maulina Hanura, Muhammad Ridzky Hendro Wicaksono Hisjam, Muhammad I Wayan Suletra Ilham Priadythama Irwan Irwan Joanda, Alfian Destha Kristanto Agung Nugroho, Kristanto Agung Kusuma, Hansen Kusuma, Hansen Lobes Herdiman Mas’ud, Azmi Muhammad Faizal Muhammad Hisyam Munifah Munifah, Munifah Murdiyantara, I Nyoman Suci Anindya Murtiastuti, Noviana Dwi Pringgo Widyo Laksono Pujiharto, Adi Norrochmat Pujiyanto, Eko Qonita, Hafsah Rochani, Renny Roni Zakaria Roni Zakaria Setyoko, Rio Detri Suprayogi Suprayogi Susmartini, Susy Wahyudi Sutopo Wakhid Ahmad Jauhari Yahuda Patria Christiawan Yuniaristanto Yuniaristanto Zakaria, Roni Zakaria, Roni