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All Journal Jurnal Informatika Jurnal Teknik Elektro Jurnal Titra Record and Library Journal Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Surya Abdimas Journal of Documentation and Information Science International Journal of Industrial Optimization (IJIO)
Siana Halim
Fakulty of Industrial Technology,Industrial Engineering Department, Petra Christian University, Jl. Siwalankerto 121-131, Surabaya 60236
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Pelatihan Pembuatan Dashboard Data Stastistik Administrasi Gerejawi Berbasis Excel Halim, Siana; Widiawan, Kriswanto; Agustin, Karina
Surya Abdimas Vol. 9 No. 2 (2025)
Publisher : Universitas Muhammadiyah Purworejo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37729/abdimas.v9i2.5612

Abstract

Organisasi gereja umumnya memiliki banyak data gerejawi tentang demografi jemaat dan kegiatan-kegiatan yang telah dilakukan. Sayangnya, data itu umumnya masih berupa data mentah atau data asli yang belum diolah, sehingga pengurus gereja tidak langsung dapat memanfaatkannya untuk pengambilan keputusan, pengembangan layanan dan pengembangan kebijakan serta strategi. Pelatihan pembuatan dashboard Excel ini bertujuan membantu pengurus gereja memanfaatkan data untuk diolah, dianalisis, dan digali informasinya agar dapat melahirkan ide-ide program kerja yang berguna dan tepat bagi jemaat. Adapun mitra pengabdian masyarakat adalah Majelis Gereja Kristen Indonesia (GKI) Kutisari Indah Surabaya beserta para aktivis gereja dari berbagai komisi pelayanan. Hasil dari pelatihan ini adalah para peserta dapat membuat dashboard; dan capaiannya adalah program kerja tiap komisi telah memanfaatkan informasi yang disajikan dalam bentuk dashboard untuk meningkatkan pelayanan bagi para pengunjung gereja. Sebagai simpulan, dashboard Excel data administrasi gerejawi dapat menyajikan informasi yang membantu pengurus gereja dalam mengatur strategi, merancang program kerja, mengeval__uasi, dan mengambil keputusan dengan lebih baik dan tepat sasaran. Rekomendasi tindak lanjutnya adalah pelatihan penajaman kemampuan analisis pengurus gereja supaya hasil dari dashboard menjadi dasar penentuan yang strategis untuk pengembangan gereja ke depannya.
Integrating Real-Time IoT Based Monitoring and Dashboard Design for Closed-House Hen Farming Handojo, Andreas; Setijarso, Edyq; Halim, Siana; Octavia, Tanti
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 27 No. 2 (2025): December 2025
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.27.2.237-248

Abstract

This paper presents a comprehensive solution that integrates IoT-based hardware systems with a real-time dashboard specifically designed for closed-house poultry farming, focusing on laying hens. Since laying hens are homeothermic animals, they are sensitive to temperature and humidity. Therefore, it is essential to monitor and control these environmental factors, along with ventilation, in real time. We describe a smart monitoring system that combines sensors, microcontrollers, and Android-based dashboards to provide actionable insights into poultry health and egg production performance. This system tracks various parameters, including temperature, humidity, equipment status, and key production indicators such as Hen Day Production (HDP), Hen House Production (HHP), and Feed Conversion Ratio (FCR). Evaluations conducted with local poultry farmers have shown improved awareness, usability, and the potential for increased operational efficiency. Despite some limitations, the dashboard provides a clear overview and helps inform decisions aimed at enhancing conditions and boosting egg production. This tool enables breeders to monitor and improve the performance of their laying hens and manage feeding strategies effectively. Additionally, it can assist in controlling and enhancing the closed-house environments and ventilation systems. The system's performance and usability were evaluated through User Acceptance Testing (UAT) and production Key Performance Indicators (KPIs), confirming its potential to enhance operational efficiency.
Statistical Learning for Predicting Dengue Fever Rate in Surabaya Halim, Siana; Felecia, Felecia; Octavia, Tanti
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 22 No. 1 (2020): June 2020
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.901 KB) | DOI: 10.9744/jti.22.1.37-46

Abstract

Dengue fever happening most in tropical countries and considered as the fastest spreading mosquito-borne disease which is endemic and estimated to have 96 million cases annually. It is transmitted by Aedes mosquito which infected with a dengue virus. Therefore, predicting the dengue fever rate as become the subject of researches in many tropical countries. Some of them use statistical and machine learning approach to predict the rate of the disease so that the government can prevent that incident. In this study, we explore many models in the statistical learning approaches for predicting the dengue fever rate. We applied several methods in the predictive statistics such as regression, spatial regression, geographically weighted regression and robust geographically weighted regression to predict the dengue fever rate in Surabaya. We then analyse the results, compare them based on the mean square error. Those four models are chosen, to show the global estimator’s approaches, e.g. regression, and the local ones, e.g. geographically weighted regression. The model with the minimum mean square error is regarded as the most suitable model in the statistical learning area for solving the problem. Here, we look at the estimates of the dengue fever rate in the year 2012, to 2017, area, poverty percen­tage, precipitation, number of rainy days for predicting the dengue fever outbreak in the year 2018. In this study, the pattern of the predicted model can follow the pattern of the true dataset.
Predicting the Readiness of Indonesia Manufacturing Companies toward Industry 4.0: A Machine Learning Approach Tanjung, Sean Yonathan; Yahya, Kresnayana; Halim, Siana
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.23.1.1-10

Abstract

This research discusses Indonesia's readiness to implement industry 4.0. We classified the Indonesia manufacturing companies' readiness, which is listed in the Indonesia Stock Exchange, in industry 4.0 based on the 2018 annual reports. We considered 38 variables from those reports and reduced them using principal component analysis into 11 variables. Using clustering analysis on the reduced dataset, we found three clusters representing the readiness level in implementing industry 4.0.  Finally, we used the decision tree for analysing the classification rules. As the finding of this study, Total book value of the machine is the variable that defined the readiness of a company in industry 4.0. The bigger those values are, the more ready a company to compete in industry 4.0. The other measures, i.e., Total cost of revenue by total revenue; Direct labor cost; Total revenue/Total employee and Transportation cost/Total revenue, will define the readiness of a manufacturing company to transform into industry 4.0. or not ready to transform into industry 4.0.
Optimizing Shipping Operations through Real-Time Monitoring and Control: A Decision Support System for Container Stripping Processes Julio, Felix; Vanni, Angelina; Amanda, Shea; Joey, Vitover; Halim, Siana
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 25 No. 1 (2023): June 2023
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.25.1.43-52

Abstract

The shipping industry plays a vital role in the global economy, with container shipping being one of the critical components. Shipping companies outline the time for customer stripping days in its contracts. The availability of the containers depends on the stripping days. The stripping days’ tardiness will hinder the availability of the containers. Therefore, it is fundamental for shipping companies to monitor both the actual condition and the contract condition of stripping days to estimate container availability and prompt customers to expedite the unloading process. However, there has yet to be a tool for monitoring the actual and the contract conditions. In this study, we used the recorded container stripping data to analyze container stripping days, tardiness, and other important parameters that indicate the performance and reliability of stripping containers. These data were post-processed and analyzed using data mining methods, and the resulting information was visualized using a dashboard to facilitate quick and effortless monitoring the dashboard in this study depicts post-processed data on container stripping days and tardiness for each port of discharge, cargo, customer, and other parameters. The dashboard was constructed using Google Data Studio. As a result, the dashboard is expected to help companies monitor, control, and analyze customers with high tardiness, allowing companies to act and ensure that the number of available containers after stripping meets demand at a given time.
Co-Authors Adrian Michael Wibisono Adrian Michael Wibisono Agnes Eval Agnes Eval Agustin, Karina Aida Fitriani Tobing Aida Fitriani Tobing Aileen Tusita Devi Alexander William Brillianata Setiadi Amanda, Shea Amelia Agnes Sunjono, Amelia Agnes Andreas Handojo Arif Chandra Arif Chandra Christian Evan Budiawan Cicely Elviani David Christian, David David Soebiantoro Della Suci Anggraini Demmy Kasih, Demmy Derried Anwar Dian Wulandari Felecia - Felecia . Felecia . Felecia Felecia Felicia Tedja Widjaja, Felicia Tedja Gan, Shu-San Genesius Chandra Hendrik Sumawi Herman Mallian Herman Mallian Indriati Bisono Indriati Bisono Indriati N Bisono Indriati N Bisono Inggrid -, Inggrid Inggrid Inggrid Jani Rahardjo Jani Rahardjo Jeremia Jeremia Joey, Vitover Johan Widjaja Julio, Felix Karina Agustin Kresnayana Yahya Kristina Sanjaya Putri Kriswanto Widiawan Njo Anastasia Olivia Sigit, Olivia Oviliani Yenty Yuliana Pauline Astari Singgih Pauline Astari Singgih Putri, Kristina Sanjaya Reyner Shenjaya Giri Putra Riyyan Adiputra Sabar Kristianto Setijarso, Edyq Shirley Adelia Shirley Adelia Stefanie Hartanto Stefanie Hartanto Steven Davian Tan Didik Wardoyo Tanusi Tanjung, Sean Yonathan Tanti Octavia Tanti Octavia Valencia Suseno Vanni, Angelina veronica - Yohan Wahyudi Yohan Wahyudi Yuliana Vina Humira