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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics Briliant: Jurnal Riset dan Konseptual Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) PERFORMA : Media Ilmiah Teknik Industri Technomedia Journal Minda Baharu Amalee: Indonesian Journal of Community Research & Engagement Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) Prosiding Konferensi Nasional PKM-CSR Jurnal Standardisasi

Setiadi, Haryono

Universitas Sebelas Maret

Author-ID : 1686571

Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences Other

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Discovering Drugs Combination Pattern Using FP-growth Algorithm Rini Anggrainingsih; Nach Rowi Khoirudin; Haryono Setiadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

A drug can be used to deal more than one diseases and to deal an illness often need a combination of more than one drugs. This paper present how to discover a pattern of a combination of medicines related to a diagnosis of diseases using FP-Growth one of frequent pattern mining algorithm. We use FP- Growth because it has better performance than Apriori and Eclat. Data is collected from outpatients pharmacy of Sukoharjo state hospital, Central Java, Indonesia during January 2015 to June 2016 and obtain 526,195 records of prescription data and use a diagnosis of diseases base on the ICD-10 standard. This studies just apply on the top ten of the most frequently occurred illness in the outpatient's services of Sukoharjo state hospital. Then the pattern of association between diseases and combination of drugs was reviewed by pharmacist committed to being validated. These studies result in some combination of medicines for to top ten of the most frequent diseases. We also found 21 similar combinations of drugs for various diseases. In the future, this finding can be used to provide suggestions to physicians to select an appropriate mix of the drug to deal some diseases.

Decision Support System to Select Elective Courses Using Hybrid AHP-Promethee Method Haryono Setiadi; Noor Azizah Mosaik Suni; Dewi Wisnu Wardani
Performa: Media Ilmiah Teknik Industri Vol 21, No 1 (2022): Performa: Media Ilmiah Teknik Industri
Publisher : Industrial Engineering Study Program, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/performa.21.1.60307

The selection of elective courses is often confusing for students as indicated by the initial survey of class 2015 -2018 students in the Informatics Department of Sebelas Maret University which showed that 88,9% needed a system to assist in selecting elective courses. This study was conducted to accommodate students’ requirements by designing the decision support system to recommend elective courses by combining AHP and PROMETHEE methods. AHP was used to weight the criteria, after which they were then ranked using the PROMETHEE such that the elective courses were sorted partially using PROMETHEE I as scenario 1 and completely through PROMETHEE II as scenario 2. The accuracy test showed that scenarios 1 and 2 were 67.4% and 60.4%, respectively, accurate.

Perancangan Sistem Informasi Kepegawaian sebagai Pendukung Keputusan Daftar Urut Kepangkatan di Universitas Sebelas Maret dengan Metode RAD Retno Wulan Damayanti; Muh. Hisjam; Haryono Setiadi
Performa: Media Ilmiah Teknik Industri Vol 7, No 1 (2008): PERFORMA Vol. 7, No. 1 Maret 2008
Publisher : Industrial Engineering Study Program, Faculty of Engineering, Universitas Sebelas Maret

Compilation of Daftar Urut Kepangkatan (DUK) is one of the routine duty in human resource unit of Sebelas Maret University (UNS). Variable which must be paid attention in compilation of DUK are position, year of service, occupation practice, education and age. The change in structural PNS is very dynamic, so that DUK’s renewal done every months. Existence of some variable which must be paid attention in compilation of DUK and also the change in structural PNS UNS, hence needed of integrated information system so that DUK is up to date and valid. One of the information system development method by paying attention and desire requirement of consumer is Rapid Application Development (RAD). RAD method use approach of prototyping. Using this method, design of information system will be focused at desire requirement of human resource unit UNS.

Educational Data Mining Using Cluster Analysis Methods and Decision Trees based on Log Mining Safira Nuri Safitri; Haryono Setiadi; Esti Suryani
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 3 (2022): Juni 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Educational Data Mining (EDM) often appears to be applied in big data processing in the education sector. One of the educational data that can be further processed with EDM is activity log data from an e-learning system used in teaching and learning activities. The log activity can be further processed more specifically by using log mining. The purpose of this study was to process log data from the Sebelas Maret University Online Learning System (SPADA UNS) to determine student learning behavior patterns and their relationship to the final results obtained. The data mining method applied in this research is cluster analysis with the K-means Clustering and Decision Tree algorithms. The clustering process is used to find groups of students who have similar learning patterns. While the decision tree is used to model the results of the clustering in order to enable the analysis and decision-making processes. Processing of 11,139 SPADA UNS log data resulted in 3 clusters with a Davies Bouldin Index (DBI) value of 0.229. The results of these three clusters are modeled by using a Decision Tree. The decision tree model in cluster 0 represents a group of students who have a low tendency of learning behavior patterns with the highest frequency of access to course viewing activities obtained accuracy of 74.42% . In cluster 1, which contains groups of students with high learning behavior patterns, have a high frequency of access to viewing discussion activities obtained accuracy of 76.47%. While cluster 2 is a group of students who have a pattern of learning behavior that is having a high frequency of access to the activity of sending assignments obtained accuracy of 90.00%.

Pemanfaatan Limbah Baglog Jamur Tiram Sebagai Bahan Baku Bio Briket Di Desa Polokarto Sukoharjo Jawa Tengah Retno Wulan Damayanti; Rahmaniyah Dwi Astuti; Haryono Setiadi
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 2 (2019): Peran Perguruan Tinggi dan Dunia Usaha dalam Mempersiapkan Masyarakat Menghadapi Era I
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Wilayah Polokarto, Sukoharjo dengan kondisi geografis 400 mdpl, mempunyai iklim tropis, kisaran suhu 25-280C dengan kelembapan udara mencapai 88%. Kondisi tersebut sangat sesuai untuk tumbuh kembang jamur tiram putih, tanpa ada rekayasa lingkungan. Kondisi ini mendukung masyarakat wilayah tersebut untuk berbudidaya jamur tiram. Seiring berkembangnya pembudidayaan jamur tiram di wilayah tersebut, teridentifikasi permasalahan berkaitan dengan limbah media baglog jamur tiram. Media baglog setelah melewati usia produktif (rata-rata 4 bulan) akan menjadi limbah padat. Pembudidaya jamur tiram di wilayah tersebut belum memanfaatkan limbah tersebut secara ekonomis. Solusi yang ditawarkan adalah dengan menjadikan limbah media tanam baglog menjadi bio briket. Bio briket dari limbah media tanam jamur tiram sangat bernilai ekonomis dan dapat dijual umum di pasaran. Hasil dari kegiatan pengabdian adalah implementasi teknologi tepat guna kepada mitra yang berupa alat produksi pengepres bio briket. Selain itu mitra juga diberikan sosialisasi dan pendampingan lapangan terkait dengan pengoperasian dan perawatan alat pengepres bio briket serta sosialisasi cara mengemas bio briket agar tampilan menjadi lebih menarik sehingga produk tersebut dapat dipasarkan kepada masyarakat umum. Selama kegiatan, mitra dilibatkan secara aktif mulai dari proses pengembangan alat hingga implementasinya. Hal ini bertujuan agar mitra memiliki kesadaran untuk menggunakan, merawat dan memanfaatkan teknologi yang telah diaplikasikan.

Fast Naïve Bayes classifiers for COVID-19 news in social networks Hasan Dwi Cahyono; Atara Mahadewa; Ardhi Wijayanto; Dewi Wisnu Wardani; Haryono Setiadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1033-1041

The growth of fake news has emerged as a substantial societal concern, particularly in the context of the COVID-19 pandemic. Fake news can lead to unwarranted panic, misinformed decisions, and a general state of confusion among the public. Existing methods to detect and filter out fake news have accuracy, speed, and data distribution limitations. This study explores a fast and reliable approach based on Naïve Bayes algorithms for fake news detection on COVID-19 news in social networks. The study used a dataset of 10,700 tweets and applied text pre-processing, term-weighting, document frequency thresholding (DFT), and synthetic minority oversampling techniques (SMOTE) to prepare the data for classification. The study assessed the performance and runtime of four models: gradient boosting (GDBT), decision tree (DT), multinomial Naïve Bayes (MNB), and complement Naïve Bayes (CNB). The testing results showed that the CNB model reaches the highest accuracy, precision, recall, and F1-score of approximately 92% each, with the shortest runtime of 0.55 seconds. This study highlights the potential of the CNB model as an effective tool for detecting online fake news about COVID-19, given its superior performance and rapid processing time.

Enhancing Participatory Learning at SMP Negeri 2 Jaten Karanganyar through the Integration of Technology Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Setiadi, Haryono; Wijayanto, Ardhi; Doewes, Afrizal
Amalee: Indonesian Journal of Community Research and Engagement Vol 5 No 1 (2024): Amalee: Indonesian Journal of Community Research and Engagement
Publisher : LP2M INSURI Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/amalee.v5i1.4816

The development of knowledge and technology significantly impacts literacy skills, essential for academic growth and school adaptation. Technology literacy is crucial for awareness and academic support, but a lack of technological knowledge can hinder education. To address this, the Indonesian government introduced the belajar.id platform, integrating Google Suite for Education (GSuite) to aid academic activities during the pandemic. Challenges like limited teacher-student interaction persist, necessitating the encouragement of electronic media and diverse educational material availability. They aimed to bridge teaching gaps, enhance technological skills, and ensure effective knowledge sharing, using participatory rural appraisal (PRA). The team of Research Group Data Information Knowledge and Engineering (RG DIKE) at the Universitas Sebelas Maret (UNS) Surakarta conducted a study on technology literacy's importance for students in SMP Negeri 2 Jaten Karanganyar. It emphasized technology's role in disaster management and prevention, striving for a strategic approach to technology-based education. Training sessions were conducted on August 15 and October 26, 2023, focused on belajar.id, GSE, and OBS integration. Teachers played a key role in guiding and updating their GSE and OBS knowledge. In summary, these sessions aimed to equip teachers and students with vital GSE and OBS skills, enhancing education quality and learning outcomes.

PENINGKATAN KEAMANAN LINGKUNGAN DENGAN PENERAPAN CCTV DI DUKUH SRIMULYO Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Hendrasuryawan, Brilyan; Setiadi, Haryono; Doewes, Afrizal; Anggrainingsih, Rini; Wijayanto, Ardhi
MINDA BAHARU Vol 8, No 2 (2024): Minda Baharu
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/jmb.v8i2.7015

. Berdasarkan kegiatan Pengabdian kepada Masyarakat (PkM) yang sudah terlaksana, yakni penerapan closed-circuit television (CCTV) di Dukuh Srimulyo, Boyolali, didapatkan hasil bahwa dapat membantu menyelesaikan masalah mitra. Adapun permasalahan yang ditemukan adalah kurangnya pengawasan yang dapat memberikan rasa aman kepada warga. Hal ini terjadi akibat banyaknya jalur kendaraan yang dapat melintasi wilayah tersebut tetapi belum diterapkan adanya pengawasan secara real-time. PkM ini bertujuan untuk mengatasi masalah keterbatasan tersebut. Solusi yang ditawarkan kepada mitra adalah penerapan CCTV yang dapat merekam kejadian di titik yang penting. Pendampingan dilakukan dalam bentuk pelatihan penggunaan CCTV dan penyediaan fasilitas untuk pengawasan yang akan digunakan oleh mitra. Adapun hasil dari PkM ini adalah ditemukan bahwa para warga memberikan sambutan baik dengan diterapkannya CCTV ini pada kegiatan yang dilakukan berdasarkan umpan balik yang diberikan setelah kegiatan selesai. Selanjutnya CCTV yang terpasang pada titik penting berjumlah dua dan telah melalui proses penelaahan bersama dengan warga. Adapun dampak yang diperoleh secara nyata setelah PkM ini berakhir adalah sebagian besar peserta dapat melakukan pengawasan secara mandiri menggunakan aplikasi aplikasi CCTV yang telah terpasang

Strategi Analisis SWOT pada Pengembangan Website Pusat Studi: Dukungan Diseminasi Persebaran Informasi: SWOT Analysis Strategy in Developing Study Center Websites: Supporting the Dissemination of Information Damayanti, Retno Wulan; Setiadi, Haryono; Laksono, Pringgo Widyo; Triyono, Joko
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2166

The Center for Research and Development of Technology and Industrial Collaboration, which is part of the Sebelas Maret University Research and Community Service Institute (PKPTKI LPPM UNS) in 2023, requires the development of an agency website for the dissemination and distribution of information to the public. \textbf{The main objective} is to provide information on research products and services that need to be promoted to the wider community. This website is expected to support the socialization of research results, PKPTKI member consultation services, and collaboration results and other activities. Through qualitative research using primary data obtained through Forum Group Discussion (FGD), this research produced a bilingual PKPTKI website. The SWOT (Strength, Weakness, Opportunity, Threat) analysis process was carried out through brainstorming activities with 4 members and 6 PKPTKI partners, and the results were used to map website needs, technical design and website content, and overall evaluation. The strategies resulting from the SWOT analysis involve developing a backend system to improve the PKPTKI website in English, scheduling consistent content updates, coordinating with the UNS ICT unit for website security, and preparing administrative SOPs for risk mitigation. The final result of this study is an effective PKPTKI website for widespread information dissemination and supporting interaction with various parties, including industry partners, practitioners, and national and international researchers.

Comparative Analysis of Machine Learning Algorithms with RFE-CV for Student Dropout Prediction Utami, Sekar Gesti Amalia; Setiadi, Haryono; Rohmadi, Arif
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4695

The high dropout rate of students in higher education is a problem faced by educational institutions, impacting quality assessments and accreditation evaluations by BAN-PT. This study aims to develop an early prediction model of potential dropout students using demographic data with a learning analytics approach. Five classification algorithms are used in this research, namely Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), and Support Vector Machine (SVM). The dataset used consists of undergraduate student data of Sebelas Maret University in 2013 (n=2476) which is processed through preprocessing techniques, resampling with SMOTE, and validation using K-Fold Cross-Validation. The results showed that the RF model gave the best performance with an accuracy of 96.01%, followed by LGBM (95.26%), DT (91.24%), LR (83.68%), and SVM (83.19%). The use of the Recursive Feature Elimination with Cross-Validation (RFE-CV) feature selection method was able to improve the efficiency of the model by reducing the number of features without significantly degrading performance. The best feature selection was obtained when using 75% features, which provided an optimal balance between the number of features and model accuracy. The most contributing features include IPS_range (Semester GPA range), parents' income, students' regional origin, as well as several other demographic factors. This study contributes to the development of early warning systems in higher education by providing accurate predictive models and identifying key risk factors.

Co-Authors Afrizal Doewes, Afrizal Anggrainingsih, Rini Ardhi Wijayanto Arif Rohmadi, Arif Assahda, Talitha Nabila Atara Mahadewa Dewi Wisnu Wardani Dewi Wisnu Wardani Esti Suryani Fakhrina Fahma Hasan Dwi Cahyono Hasan Dwi Cahyono Hendrasuryawan, Brilyan Joko Triyono Muh. Hisjam Nach Rowi Khoirudin Noor Azizah Mosaik Suni Pringgo Widyo Laksono Rahmaniyah Dwi Astuti Retno Wulan Damayanti Retno Wulan Damayanti Retno Wulan Damayanti Rini Anggrainingsih Rini Anggrainingsih Rowi Khoirudin, Nach Safira Nuri Safitri Utami, Sekar Gesti Amalia Wijayanto, Ardhi

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