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All Journal Jurnal Manajemen dan Organisasi Jurnal Rekayasa Sistem Industri The Asian Journal of Technology Management (AJTM) JRSI (Jurnal Rekayasa Sistem dan Industri) Jurnal Teknik Logistic and Operation Management Research
Kadarsah Suryadi
Industrial Engineering Department, Bandung Institute of Technology, Indonesia
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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KEEFEKTIFAN ONLINE KNOWLEDGE SHARING BEHAVIOR (STUDI KASUS: BLENDED LEARNING ITB) Amila, Khuria; Suryadi, Kadarsah
Jurnal Rekayasa Sistem & Industri Vol 1 No 01 (2014): Jurnal Rekayasa Sistem & Industri - Juli 2014
Publisher : School of Industrial and System Engineering, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.495 KB)

Abstract

Penerapan blended learning dapat mengintegrasikan manfaat yang diperoleh dari knowledge management dan e-learning. Pendekatan dengan mengombinasikan interaksi tatap muka dan interaksi online ini idealnya mampu meningkatkan kualitas pembelajaran di perguruan tinggi. Salah satu tantangan dalam penerapan blended learning adalah pelaksanaan online knowledge sharing yang konsisten dan berkesinambungan. Penelitian ini berupaya untuk menemukan cara meningkatkan keefektifan Online Knowledge Sharing Behavior (OKSB). Model OKSB pada penelitian ini mengintegrasikan model Knowledge Sharing Behavior dari Chen dkk. (2009) yang berbasis pada Theory of Planned Behavior dengan model Ma dan Yuen (2010) yang berbasis pada teori pengembangan dan pemeliharaan hubungan sosial. Penelitian ini memandang OKSB dipengaruhi oleh faktor intention, self-efficacy, social interaction, serta faktor kepuasan teknologi. Uji empiris dilakukan dengan melibatkan 110 orang mahasiswa peserta kelas blended learning ITB. Pengolahan data dengan menggunakan metode PLS menunjukkan bahwa social interaction yang terdiri dari perceived online attachment motivation dan perceived online relationship commitment menjadi faktor yang paling mempengaruhi OKSB. Namun, penelitian ini tidak mampu membuktikan bahwa knowledge sharing intention memengaruhi OKSB.
Analisis Sentimen Data Ulasan Pengguna MyPertamina di Twitter dengan Metode Text Mining Hutabarat, Andita Widya Valencia; Adnyani, Ni Luh Saddhwi Saraswati; Suryadi, Kadarsah
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6958.145-154

Abstract

To ensure that the distribution process of subsidized fuel is more well-targeted, PT Pertamina has developed an application called MyPertamina. The increasing number of MyPertamina users has led to an increasing number of reviews related to the use of MyPertamina. Reviews of MyPertamina fill various social media channels, including Twitter. However, the analysis of user perceptions through social media has not been optimal. Therefore, a better user sentiment mapping is needed. This study was conducted to answer this need by building a text mining model and designing a prototype that can extract and analyze sentiments from tweets related to MyPertamina. This research adopts the CRISP-DM methodology, which consists of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The data obtained for model development reached 6,920 tweet data. Each data was classified into one of three sentiment categories, namely positive, negative, and neutral. After data preparation, 2,057 data were used for model development. The models tested in this study consist of Support Vector Machine (SVM), Multinomial Naïve Bayes, Gaussian Naïve Bayes, Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory (Bi-LSTM) algorithms. The model that produced the best evaluation score and was selected for prototype development is the SVM model with an accuracy score of 83.74%, weighted precision of 83.96%, weighted recall of 83.74%, and weighted F1-score of 83.72%. The prototype is used for extracting and predicting sentiment for new datasets, which can then be visualized in the form of graphs and word clouds according to the user's needs.
Pembangunan Model Pendeteksi Risiko Preeklamsia pada Ibu Hamil dengan Menggunakan Metode Data Mining Ilham, Muhammad; Adnyani, Ni Luh Saddhwi Saraswati; Suryadi, Kadarsah
Jurnal Teknik: Media Pengembangan Ilmu dan Aplikasi Teknik Vol 23 No 1 (2024): Jurnal Teknik - Media Pengembangan Ilmu dan Aplikasi Teknik
Publisher : Fakultas Teknik - Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55893/jt.vol23no1.543

Abstract

Preeclampsia is a pregnancy complication indicated by an increase in blood pressure that occurs after 20 weeks of gestation and the presence of protein in the urine. If not treated quickly, preeclampsia can lead to maternal and fetal death. Therefore, a method that can help health workers to provide early detection of preeclampsia is needed. One method that can be used is data mining. This study was conducted with the aim of developing a model based on data mining methods that can be used as a tool to identify patients with preeclampsia and also to identify associated risk factors. This study was conducted using six data mining classification algorithms on 109 obstetric clinic patient data at the Jakarta Pondok Kopi Islamic Hospital (RSIJPK). The input features used as preeclampsia detection attributes were obtained based on the results of a literature study and consultations with obstetricians. Based on the results of the model evaluation, logistic regression has the best performance in detecting preeclampsia with accuracy value of 98% and precision level of 100%. In addition, this study also designed an application prototype that can be used by health workers to quickly detect the risk of preeclampsia in pregnant women.
Sustainability Balance Scorecard: Literature Review and Clustering of Performance Indicator Trisyulianti, Erlin; Suryadi, Kadarsah; Prihantoro, Budi
Jurnal Manajemen dan Organisasi Vol. 15 No. 4 (2024): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v15i4.61691

Abstract

Answering the challenges of sustainable development, companies require an integrated approach to performance management in economic, social, and environmental aspects. This approach is not only profit-oriented but also addresses the needs of human welfare, social, and environmental concern. The approach also includes the ability to link strategy with action. Therefore, it is important to apply the sustainability Balanced Scorecard (SBSC) in performance management. The research aims to study the development of SBSC studies for the last decade. A systematic literature review has been conducted to identify, evaluate, and interpret SBSC based on previous research. The results described publication map, the taxonomy of research, and meta-analysis of SBSC performance indicators.
Energy Consumption Model Based on User Behavior to Support Solar Panel Selection: Case Study of Dental Clinic Firdaus, Rifki; Suryadi, Kadarsah
The Asian Journal of Technology Management (AJTM) Vol. 17 No. 3 (2024)
Publisher : Unit Research and Knowledge, School of Business and Management, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12695/ajtm.2024.17.3.4

Abstract

Abstract. Electricity consumption continues to rise alongside population growth and infrastructure development. Unfortunately, the majority of energy consumption is still reliant on fossil fuels. Commercial buildings and residences are major contributors to electricity consumption, accounting for 63.04% of the total usage. In the healthcare sector, clinics and hospitals also require significant electrical energy, contributing to a 21% rise in national electricity demand. Additionally, occupants' behavior influences electricity consumption by 30%. Faced with these challenges, the use of renewable energy, such as solar power, holds great potential for providing sustainable energy. This research aims to simulate energy consumption to aid in the selection of solar panel technology, considering occupant behavior. By understanding accurate electricity consumption, solar panels that meet the needs can be chosen to ensure long-term sustainability. Simulation of electricity consumption using dynamic system methods is performed to acquire daily electricity consumption data, a critical criterion in solar panel selection. The study's results indicate that user behavior in utilizing electrical appliances significantly impacts overall energy consumption. The study implies the importance of understanding behavior to properly recognize actual electricity consumption. Keywords: Energy consumption, simulation, system dynamic, user behaviour.
Systematic Review of Sustainable Competitive Advantage Factors of SMEs in The Creative Industry Dewayana, Triwulandari Satitidjati; Gunawan, Akbar; Suryadi, Kadarsah; Marie, Iveline Anne
Logistic and Operation Management Research (LOMR) Vol. 4 No. 1 (2025): Logistic and Operation Management Research (LOMR)
Publisher : Research Synergy Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31098/lomr.v4i1.3331

Abstract

A sustainable competitive advantage refers to a combination of characteristics and capabilities that allow a business to fulfill customer needs more effectively than its competitors. It encompasses elements that enable a company to produce goods or services of superior quality or at a lower cost than others. These advantages help businesses achieve higher sales or profit margins in the market. This literature review aims to examine and identify various factors contributing to the development of sustainable competitive advantage in the creative industry, a topic that has gained significant importance and widespread attention. This research employs a systematic literature review (SLR) approach to investigate these factors in the context of creative industries. Using the SLR approach and the PRISMA framework, this research identified, evaluated, and synthesized 27 relevant articles from the Scopus and IEEE Xplore databases, published between 2014 and 2024. These articles contain results about the factors and problems that can influence sustainable competitive advantage in creative industries with relevant fields, such as social, economic, and technical. A total of 19 factors were found that influence sustainable competitive advantage.  All these factors are important, but production quality, environmental friendliness, finance, innovation, consumer behavior, and human resources are the most prominent. This meta-analysis provides valuable insights and serves as a foundation for advancing efforts to promote the implementation of competitive advantage practices.
Co-Authors Adnyani, Ni Luh Saddhwi Saraswati Dewayana, Triwulandari Satitidjati Erlin Trisyulianti Gunawan, Akbar Hilmi Aulawi Hutabarat, Andita Widya Valencia Iman Sudirman Iveline Anne Marie Khuria Amila Muhammad Ilham Prihantoro, Budi Rajesri Govindaraju Rifki Firdaus, Rifki