Claim Missing Document
Check
Articles

Found 6 Documents
Search

Sistem Pendukung Keputusan Peramalan Jumlah Kunjungan Pasien Menggunakan Metode Extreme Learning Machine (Studi Kasus : Poli Gigi Rsu Dr. Wahidin Sudiro Husodo Mojokerto) Fardani, Delia Putri; Wuryanto, Eto; Werdiningsih, Indah
Journal of Information Systems Engineering and Business Intelligence Vol 1, No 1 (2015): April
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.829 KB)

Abstract

Abstrak— Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk meramalkan jumlah kunjungan pasien RSU Dr. Wahidin Sudiro Husodo Kota Mojokerto dengan menggunakan metode Extreme Learning Machine (ELM). Dengan adanya  sistem pendukung keputusan ini direktur Rumah Sakit dapat meramalkan jumlah kunjungan pasien dan membantu dalam pembuatan kebijakan rumah sakit, mengatur sumber daya manusia dan keuangan, serta mendistribusikan sumber daya material dengan benar khususnya pada poli gigi. Dalam rancang bangun sistem pendukung keputusan ini dilakukan dalam beberapa tahap. Tahap yang pertama, pengumpulan data untuk mengidentifikasi inputan yang dibutuhkan dalam penghitungan metode ELM. Tahap kedua, pengolahan data, data dibagi menjadi data training dan data testing dengan komposisi data training sebanyak 80% (463 data) dari total 579 data dan 20% (116 data) sisanya sebagai data testing yang kemudian di normalisasi. Tahap ketiga, peramalan jumlah kunjungan pasien menggunakan metode ELM. Tahap terakhir, perancangan sistem menggunakan sysflow dan pembangunan sistem berbasis desktop serta evaluasi sistem. Hasil penelitian berupa aplikasi sistem pendukung keputusan untuk meramalkan jumlah kunjungan pasien. Dan melalui uji coba menggunakan 116 data testing berdasarkan fungsi aktivasi sigmoid biner dengan jumlah hidden layer sebanyak 7 unit dan Epoch 500 diperoleh hasil optimal MSE sebesar 0.027 Kata Kunci— Sistem Pendukung Keputusan, Peramalan, Jaringan Syaraf Tiruan, Extreme Learning MachineAbstract— In this research, a decision support system to predict the number of patients visit RSU Dr. Wahidin Sudiro Husodo Kota Mojokerto was designed and developed using Extreme Learning Machine (ELM) method which aims to assist director in making decision for the hospital, managing human and financial resource, as well as distributing material resource properly especially in the Department of Dentistry. The design of this decision support system to predict the number of patients visit with ELM method is divided into several stages. The first stage is to identify the input data collection needed in the calculation method of ELM. The next stage is processing the data; the data is divided into training data and testing data and then normalized, in which training data is 80% (452 data) and testing 579 data 20% (116 data). The third stage is problem solving using ELM. The last stage is the design and development of systems using sysflow and desktop-based system that includes the implementation and evaluation of the system. The result of this research is an application of decision supporting system to predict number of patients. By using 116 testing data based on the binary sigmoid activation function using 7 units of hidden layer and 500 Epoch then Optimal MSE value that was obtained is 0.027. Keywords— Decision Supporting System, Prediction, Artificial Neural Network, Extreme Learning Machine
The development of lemma and meaning in the language variety used by adolescents on social media Fitri Amilia; Indah Werdiningsih; Rohmad Tri Aditiawan
BAHASTRA Vol. 42 No. 1 (2022): BAHASTRA
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/bs.v42i1.33

Abstract

This study examines the natural phenomena on the development of lemma and meaning in the variety of languages used by adolescents on social media. Research design was done naturally through the process of observation, taking notes, and writing down the case. The qualitative research appears in the development of the entry which is easily found as a definite phenomenon of linguistic development. The data collection method was carried out by tracing data on the use of various languages on social media. To analyze the data, the researcher uses padan and agih methods. This method is to test the accuracy of classification on the types of language used by adolescents in social media in the development of the entry and or the development of the meaning of the entry. The results showed that the variety of languages on social media is very dynamic, developing, arbitrary, but conventional. The variety of languages indicates the development of new lemmas, acronyms, and walikan. The development of meaning is marked along with the development of the entry in the form of synonyms and the use of the Indonesian language entry in the form of a polysemic. Based on the results of this study, adolescents can be considered a productive period in exploring the language, through direct interaction or social media. Becoming actively productive in language exploration led to a potential for concepting a new lemma and a new meaning according to the context of language use. In addition, this development becomes one proof of the self-existence of adolescence, community characteristics, and also the need for the development of Indonesian vocabulary.
EVALUATION AND USER INTERFACE DESIGN IMPROVEMENT RECOMMENDATIONS OF THE IMMIGRATION SERVICE APPLICATION USING DESIGN THINKING Hendarto, Alexander Ryan; Werdiningsih, Indah; Kartono, Kartono
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0001-0018

Abstract

The M-Paspor application is an immigration service application. It is an application that is officially managed by the Directorate General of the Ministry of Law and Human Rights of the Republic of Indonesia. With this online service system, people who wish to apply for passports do not need to come to the office and stand in line to make passports, now they only need to access the Directorate General of Immigration's website or this mobile-based application to submit an application. This study aims to evaluate and provide recommendations for user interface improvements that can be proposed to improve the user experience of the M-Paspor application. This research used the design thinking method. Design thinking itself consists of five stages, namely empathy, define, idea, prototype, and test. Some of the problems in the user experience of the M-Paspor application are the confusing flow and interface, the loading process takes too long, the information guide is not informative, the display is boring and inconsistent. The user experience of the M-Paspor application has been tested with 15 respondents through five usability test task scenarios. The test results shown that the average aspect of effectiveness is 100%, the average aspect of efficiency is 0.133 goals/second with a range of 0.197 goals/second, and the average aspect of user satisfaction is 5.1 with a range of 2.4 (from a scale of 1 to 7).
Analyzing the Online Reading Strategies of Indonesian In-Service EFL Teachers Laeli, Anita Fatimatul; Werdiningsih, Indah; Hanafi
JURNAL PENDIDIKAN DAN PENGEMBANGAN MANUSIA Vol 10 No 1 (2025): Education and Human Development Journal
Publisher : Universitas Nahdatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/ehdj.v10i1.7271

Abstract

The rapid advancement of technology in the 21st century has transformed English language learning, particularly in reading activities. The shift from print to digital texts not only requires adapting traditional reading strategies but also introduces new strategies, such as searching for and synthesizing information online. This study examines the online reading strategies employed by English language teachers in East Java. Using a quantitative research design with a survey method, 97 English language teachers participated by completing the SLORSI (Second Language Online Reading Strategies Inventory) questionnaire. The results revealed that Traditional Cognitive Strategies, including inferring, skimming, and translating, were the most commonly used, with high scores across all subscales. In the New Cognitive Strategies dimension, strategies like locating, synthesizing, saving, and navigating were also frequently employed, with the saving strategy being the most dominant (Mean = 4.24). The Evaluation Strategy dimension indicated that teachers frequently assessed the credibility of online information. However, Communication Strategies were used the least (Mean = 3.33), particularly in terms of online collaboration and discussion. In conclusion, the study highlights that English language teachers effectively use a range of cognitive, evaluative, and communicative strategies in reading online texts. Nevertheless, there is potential for further development, particularly in enhancing communicative strategies. This underscores the importance of equipping teachers with the skills to navigate and critically engage with digital texts in their teaching practices.
OPTIMIZING THE USE OF ARTIFICIAL INTELLIGENCE FOR THE CREATION OF PROMOTIONAL CONTENT AND LEARNING IN THE BOARDING SCHOOL Taufik, Taufik; Effendy, Faried; Purbandini, Purbandini; Purwanti, Endah; Werdiningsih, Indah; Nuzulita, Nania; Baihaqi, Joevans Mikail; Adhipratama, Javier Ihsan; Alfath, Muhammad Fauzan; Pratama, Muhammad Fadhil Putra; Muid, Faruq Abdul; Kastur, Annita; Agustin, Dewien Nabila
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 9 No. 3 (2025): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/.v9i3.2025.372-382

Abstract

Darul Ittihad Islamic Boarding School (Pondok Pesantren Darul Ittihad), as a traditional educational institution, faces challenges in optimizing the use of information technology, particularly Artificial Intelligence (AI), for the development of promotional and instructional content. This community service program (PKM) aims to enhance the pesantren's capacity to utilize AI and digital design applications such as Canva. The activity was conducted in three phases: preparation, implementation, and evaluation. During the preparation phase, the team conducted a needs assessment survey and developed relevant training materials. The implementation phase consisted of two training sessions, focusing on the creation of AI-based promotional and educational content. Evaluation was carried out by collecting participant feedback through a questionnaire distributed via Google Forms. The evaluation results indicated a high level of participant satisfaction, with an average score of 3.24 out of 4. Additionally, 88% of participants successfully completed the independent assignments provided after the training, demonstrating a significant improvement in skills. This program concludes that the integration of AI into teaching and promotional processes at Darul Ittihad has the potential to enhance communication effectiveness, increase content relevance, and better prepare students to face the challenges of the digital era.
Identifying Credit Card Fraud in Illegal Transactions Using Random Forest and Decision Tree Algorithms Werdiningsih, Indah; Purwanti, Endah; Wira Aditya, Gede Rangga; Hidayat, Auliya Rakhman; Athallah, R. Sulthan Rafi; Sahar, Virda Adisty; Wibisono, Tio Satrio; Nura Somba, Darren Febriand
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1730

Abstract

The use of credit cards is increasing in today's digital era. This increase has resulted in many cases of fraud which have had a negative impact on credit card owners. To overcome this, many financial institutions have developed credit card fraud detection systems that can identify suspicious transactions. This study uses a classification method, namely random forest and decision tree to identify illegal transactions using a credit card, which then compares the results and attempts to create a model that can be useful for detecting fraud using a credit card that is more accurate and effective. The result of this study is that the accuracy provided by the Decision Tree Classifier is 0.98, while the accuracy provided by the Random Forest Classification is also 0.975. The conclusion obtained that the decision tree has a higher level of accuracy compared to the Random Forest Classification Algorithm, which is 98%. On the other hand, the Random Forest classification algorithm has a slightly lower level of accuracy compared to the Decision Tree classification algorithm, with an accuracy rate of 97.5%