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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) TELKOMNIKA (Telecommunication Computing Electronics and Control) Abdimas Lembaran Ilmu Kependidikan Scientific Journal of Informatics Jurnal Kajian Informasi & Perpustakaan JURNAL PROFESI KEGURUAN Dinamisia: Jurnal Pengabdian Kepada Masyarakat JMM (Jurnal Masyarakat Mandiri) Journal of Innovation in Educational and Cultural Research Journal of Soft Computing Exploration International Journal of Engineering, Science and Information Technology Journal of Advances in Information Systems and Technology Proceeding of International Conference on Science, Education, and Technology Recursive Journal of Informatics Scientific Journal of Informatics Jurnal Abdi Negeri Recursive Journal of Informatics
Aji Purwinarko, Aji
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Optimalisasi Budidaya Tanaman Hutan dan Buah untuk Masyarakat Sekitar Hutan di Kabupaten Kendal Dewi, Nur Kusuma; Melati, Inaya Sari; Purwinarko, Aji; Hadiyanti, Lutfia Nur
Jurnal Abdimas Vol 25, No 2 (2021): December 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v25i2.34756

Abstract

Strategi konservasi dalam pengembangan Kawasan Ekosistem Esensial (KEE) terestrial Gunung Ungaran dilakukan melalui kegiatan pengawetan, pelestarian, perlindungan dan pemanfaatan secara berkelanjutan. Upaya melakukan konservasi diperlukan kerjasama seluruh stakeholder, khususnya masyarakat yang berada disekitar hutan. Salah satu kelompok masyarakat di sekitar hutan yang telah turut serta berperan aktif dalam kegiatan konservasi dan mendukung kebijakan pengembangan KEE Gunung Ungaran adalah Kelompok Peduli Lingkungan Gunungsari Handarbeni selaku mitra kegiatan pengabdian ini. Kelompok Peduli Lingkungan Gunungsari Handarbeni baru terbentuk pada tahun 2020 yang bertujuan sebagai wadah organisasi masyarakat yang bergerak dalam kegiatan pelestarian Gunung Ungaran. Anggota mitra terdiri dari karang taruna dan tokoh masyarakat yang berjumlah 30 orang. Berdasarkan survei dan wawancara langsung terhadap mitra pengabdian, permasalahan yang dihadapi mitra dapat diketahui beberapa permasalahan yang dihadapai oleh mitra, yakni (1) aspek kelembagaan dan legalitas kelompok, (2) aspek produksi/budidaya, dan (3) aspek manajemen usaha. Target dari kegiatan pengabdian bagi dosen ini adalah adanya peningkatkan aspek kelembagaan khususnya legalitas kelompok, peningkatan kapasitas SDM mitra dalam teknik perbanyakan pembibitan, dan peningkatan kapasitas SDM mitra melalui pengembangan usaha penjualan bibit bernilai komersial. Metode yang dilakukan, meliputi kegiatan ceramah, pelatihan, pendampingan, dan monitoring serta evaluasi. Kegiatan pelatihan dan pendampingan ini dilakukan untuk mendorong adanya inventarisasi jumlah bibit, identifikasi tanaman, dan pemasangan barcode tanaman guna mendukung keberadaan KEE Gunung Ungaran.   
OFET Preparation by Lithography and Thin Film Depositions Process Sujarwata Sujarwata; Fianti Fianti; Langlang Handayani; Aji Purwinarko; Susilo Susilo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 1: February 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i1.6544

Abstract

The length of the channel OFET based thin film is determined during preparation takes place using the technique of lithography and mask during the metal deposition process. The lithography technique is the basic process steps in the manufacture of semiconductor devices. Lithography is the process of moving geometric shapes mask pattern to a thin film of material that is sensitive to light. The pattern of geometric shapes on a mask has specifications, as follows: long-distance source and drain channels varied, i.e. 100 μm, the width of the source and drain are made permanent. Bottom contact OFET structure has been created using a combination of lithography and thin film deposition processes.
The Telegram notification system for improving library services Universitas Negeri Semarang Kholiq Budiman; Mahargjo Hapsoro Adi; Akhmad Munawar; Aji Purwinarko
Jurnal Kajian Informasi dan Perpustakaan Vol 10, No 1 (2022): Accredited by Ministry of Education, Culture, Research and Technology of the Re
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jkip.v10i1.35533

Abstract

The pandemic period limits every activity, including library services, causing the communication distance between users and librarians to widen. Users often forgetting to return books, so the fines accumulated, and often forget and lose borrowed books. The communication distance between librarians and library users can be narrowed through an automatic reminder system to remind users of important information regarding fines, services, and others. This study aimed to know the Telegram notification system for improving library services. Universitas Negeri Semarang also supports the use of Telegram as a notification system. This study applied the Research and Development (RnD) method in The Senayan Library Management System (SLiMS) development, supported by an integration method using Middleware Integration. The use of the paired t-test in this study showed that this reminder mechanism successfully informed library members of the time limit for borrowing books and late fees. A significant relationship exists between before and after the installation of Telegram as a useful reminder system to avoid the accumulation of fines by customers. This reminder system was also beneficial to avoid users accumulating fines, it can be seen that the number of users who are late in returning books is decreasing as the notification system is implemented. Good communication between librarians and customers through an information system intermediary improves user service.
The Effect of Environmental Pollution Game-Based Learning on Improving Students' Conceptual Understanding and Environmental Awareness Arif Widiyatmoko; Muhamad Taufiq; Aji Purwinarko; Indah Urwatin Wusqo; Melissa Salma Darmawan
Journal of Innovation in Educational and Cultural Research Vol 3, No 4 (2022)
Publisher : Yayasan Keluarga Guru Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.388 KB) | DOI: 10.46843/jiecr.v3i4.344

Abstract

The purpose of this study is to analyze the effect of "Environmental Pollution Game-Based Learning (EPGBL)" on improving students’ conceptual understanding and environmental awareness. EPGBL is an android-based learning media that can be used in science learning, particularly for environmental pollution concepts. Quasi-experimental research with pretest and posttest group design was utilized to answer the research questions in this study. The average percentage of correct responses in the pre-test is 61.33, meanwhile, the percentage of correct responses in the post-test is 73.33. This result showed that the percentage of correct responses in the post-test is higher than in the pre-test. The results showed that EPGBL can improve students' conceptual understanding of environmental pollution concept. The average score of the students' environmental awareness character is 3.98 that include in the good criteria. In conclusion, EPGBL is effective in improving students' conceptual understanding and environmental awareness.
Aplikasi Layanan Penelusuran Informasi Berbasis Android di Perpustakaan FMIPA UNNES Adi, Mahargjo Hapsoro; Purwinarko, Aji; Munawar, Akhmad; Siswati, Sri
Lembaran Ilmu Kependidikan Vol 51, No 1 (2022): April: Technology and Innovation in Education, Leadership, Policy, and Educatio
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/lik.v51i1.40806

Abstract

Penelitian ini membahas tentang aplikasi penelusuran informasi berbasis android yang akan mempermudah pemustaka dalam menemukan informasi yang dibutuhkannya dalam menunjang perkuliahan. Aplikasi ini dibuat berbasis android dengan tujuan untuk memudahkan pemustaka perpustakaan FMIPA, karena peneliti yakin bahwa semua mahasiswa memiliki gawai berbasis android. Hal ini dikarenakan bahwa setiap informasi dari universitas kepada mahasiswa semuanya berbasis aplikasi (telegram) dan semua itu membutuhkan gawai. Aplikasi ini tidak berdiri sendiri melainkan terkoneksi dengan beberapa unit atau lembaga di luar perpustakaan FMIPA ( UPT perpustakaan dan Perpustakaan Nasional) guna memudahkan pemustaka dalam mencari informasi. Pemustaka bisa masuk ke repository Unnes, E-journal yang dilanggan oleh Unnes dan juga E-resouces Perpustakaan Nasional (E-Journal yang dilanggan Perpusnas), bahkan mendaftar sebagai anggota Perpusnas hanya dengan sekali klik dari gawai pemustaka. Ini tentunya sesuai dengan salah satu fungsi perpustakaan, yaitu fungsi informatif, dimana perpustakaan harus dapat memberikan informasi yang dibutuhkan oleh pemustaka dari manapun sumbernya. Pengembangan aplikasi dalam penelitian ini menerapkan metode Research and Development (RnD). Melalui aplikasi ini pemustaka juga dapat melakukan self checking terhadap bahan perpustakaan yang dipinjamnya, buku apa saja yang pernah dipinjam selama ini dan kapan saat pengembaliannya karena aplikasi sudah memfasilitasinya. Dengan adanya aplikasi ini diharapkan layanan Perpustakaan FMIPA semakin baik dan meningkat.
PENERAPAN TEKNOLOGI ROASTER DENGAN KENDALI INTERNET OF THING BERBASIS ANDROID DAN SACHET OTOMATIS PADA PENGOLAHAN KOPI PREMIUM Bambang Sugiantoro; YB. Praharto; Utis Sutisna; Tris Sugiarto; Amin Retnoningsih; Annindya Ardiansari; Aji Purwinarko; Danang Dwi Saputro
JMM (Jurnal Masyarakat Mandiri) Vol 7, No 1 (2023): Februari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v7i1.11899

Abstract

Abstrak: Desa Gondang, Kecamatan Karangreja, merupakan salah satu Desa penghasil kopi arabika dan robusta bermutu tinggi di Kabupaten Purbalingga. Produk kopi selama ini belum optimal dikembangkan untuk mencapai produk premium, karena keterbatasan pengetahuan dan teknologi proses. Kopi premium mempunyai nilai jual tinggi pada pasar nasional maupun internasional, baik dalam bentuk green bean, roast bean dan serbuk. Kopi yang dihasilkan di Desa ini bercirikan butir yang besar, bersih dan merata, berpotensi dikembangkan menjadi produk kopi premium. Penerapan teknologi tepat guna (TTG) proses pengolahan kopi premium, dengan melakukan penyuluhan, pelatihan penggunaan TTG, studi banding dan mengundang narasumber pengolah kopi dari UKM yang sudah maju. Mesin pengolah kopi premium yang dibantu kepada kelompok terdiri dari: (1) TTG mesin roaster kapasitas 20 kg/proses, dengan monitoring Internet of Thing (IoT) berbasis android; (2) TTG mesin sachet otomatis dengan variasi berat (30-250 gr); (3) TTG Sealing Continues untuk paking kopi ukuran diatas 500 gr; dan (4) Dry House dilengkapi panel solar sel, untuk stabilisasi suhu dan kelembaban. Selain itu dalam rangka penerapan mesin produksi otomatis, untuk layanan dan monitoring perkembangan kelompok telah dikembangkan Website modern untuk meningkatkan branding produk yang terintegrasi layanan penjualan online. Hasil pemberdayaan kelompok tani ini menunjukkan bahwa dari 11 orang anggota kelompok yang dilatih khusus pengolahan kopi premium, setelah dilakukan post test, diketahui 8 orang (73%) hasil sangat baik, 2 orang (18%) baik, dan 1 orang (9%) cukup. Hasil penerapan TTG menunjukkan 11 orang anggota kelompok Tani Bawono Lestari mampu meningkatkan variasi produk kopi arabika dan robusta masing-masing 3 jenis rasa khas yang diproses untuk dipasarkan pada premium market. Dampak penerapan proses pengolahan kopi premium meningkatkan nilai ekonomis produk sebesar 57%, harga produk kopi roastbean arabika meningkat dari rata-rata per kilogram Rp. 175.000/kg meningkat menjadi Rp. 235.500-250.000/kg, kopi robusta dari Rp. 75.000/kg menjadi Rp 117.000-120.000/kg, peningatan kapasitas produksi kopi olahan sebesar 73%, dari 175 kg/hari menjadi 306,25/hari.Abstract: Gondang Village, Karangreja District, is one of the villages producing high-quality Arabica and Robusta coffee in Purbalingga Regency. Due to limited knowledge and process technology, coffee products have not been developed optimally to achieve premium quality Regency. Due to limited knowledge and process technology, coffee products have not been developed optimally to achieve premium quality. Premium coffee has a high selling value in national and international markets, both in the form of green beans, roasted beans, and powder. The coffee produced in this village is characterized by large, clean, and even grain, which has the potential to be developed into premium coffee products. application of appropriate technology for premium coffee processing by conducting counseling, training on the use of appropriate technology, comparative studies, and inviting resource persons from advanced SMEs. The premium coffee processing machines assisted by the group consist of: (1) an appropriate technology roaster machine with a capacity of 20 kg/process, with Android-based Internet of Things (IoT) monitoring; (2) appropriate technology automatic sachet machines with weight variations (30–250 gr); (3) appropriate technology sealing machines for packing coffee sizes above 500 gr; and (4) a dry house equipped with solar cell panels to stabilize temperature and humidity. In addition, in the context of implementing automatic production machines for service and monitoring group developments, a modern website has been developed to improve product branding that is integrated with online sales services. The results of the empowerment of this farmer group showed that out of 11 group members who were specifically trained in premium coffee processing, after the post-test, it was found that 8 people (73%) had very good results, 2 people (18%) had good results, and 1 person (9%) had enough. The results of the application of appropriate technology showed that 11 members of the Bawono Lestari Farmer Group were able to increase the variety of Arabica and Robusta coffee products, each of which had three distinctive flavors and was processed to be marketed at the premium market. The impact of using the premium coffee processing process raises the economic value of the product by 57%, raising the price of Arabica roast bean coffee products from an average of Rp. 175,000 per kilogram to Rp. 235,500 to 250,000 per kilogram and raising the price of robusta coffee from Rp. 75,000 per kilogram to IDR 117,000-120,000 per kilogram, resulting in a 73% increase in processed coffee production capacity from 175 kg per day to 306.25 kg per day.
Instrument Development for Measuring the Satisfaction Level from Service Provided by Administrative Staff of FMIPA UNNES Aditya Marianti; Woro Sumarni; Aji Purwinarko; Amidi Amidi
International Conference on Science, Education, and Technology Vol. 7 (2021)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to develop a valid and reliable measuring instrument to measure the satisfaction level from service provided by the administrative staff of FMIPA UNNES, as an effort to improve the service quality of higher education institutions. A research and development model, ADDIE, was applied in this research. Developed instruments were 20 questions that represented certain indicators, which were derived from 5 dimensions (1) tangible, (2) responsiveness, (3) reliability, (4) assurance, and (5) emphaty. Construct validity of the questioner was assessed by 2 experts and analysed using Confirmatory Factor Analysis (CFA). Internal reliability of the instruments was measured using Alfa Cronbach coefficient. These developed instruments were tested on 531 respondents that represented the user of the service. Results from expert testing stated that the instruments were proper for use with revisions. CFA results showed that all loading factors scored above 0.3 on path diagram. According to these results, the score for goodness of fit and measurement model fit were considered fulfilled. The alpha score for internal reliability analysis was 0,98 or was considered has high reliability. The conclusion of this research is the measuring instrument for satisfaction level of service provided by the administrative staff of FMIPA UNNES is valid and reliable.
Application of C4.5 Algorithm Using Synthetic Minority Oversampling Technique (SMOTE) and Particle Swarm Optimization (PSO) for Diabetes Prediction Damayanti, Dela Rista; Purwinarko, Aji
Recursive Journal of Informatics Vol 2 No 1 (2024): March 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v2i1.64928

Abstract

Abstract. Diabetes is the fourth or fifth leading cause of death in most developed countries and an epidemic in many developing countries. Early detection can be a preventive measure that uses a set of existing data to be processed through data mining with a classification process. Purpose: Investigate the efficacy of integrating the C4.5 algorithm with Synthetic Minority Oversampling Technique (SMOTE) and Particle Swarm Optimization (PSO) for improving the accuracy of diabetes prediction models. By employing SMOTE, the study aims to address the class imbalance issue inherent in diabetes datasets, which often contain significantly fewer instances of positive cases (diabetes) than negative cases (non-diabetes). Furthermore, by incorporating PSO, the research seeks to optimize the decision tree construction process within the C4.5 algorithm, enhancing its ability to discern complex patterns and relationships within the data. Methods/Study design/approach: This study proposes the use of the C4.5 classification algorithm by applying the synthetic minority oversampling technique (SMOTE) and particle swarm optimization (PSO) to overcome problems in the diabetes dataset, namely the Pima Indian Diabetes Database (PIDD). Result/Findings: From the research results, the accuracy obtained in applying the C4.5 algorithm without the preprocessing process is 75.97%, while the results of the SMOTE application of the C4.5 algorithm are 80%. Meanwhile, applying the C4.5 algorithm using SMOTE and PSO produces the highest accuracy, with 82.5%. This indicates an increase of 6.53% from the classification results using the C4.5 algorithm. Novelty/Originality/Value: This research contributes novelty by proposing a hybrid approach that combines the C4.5 decision tree algorithm with two advanced techniques, Synthetic Minority Oversampling Technique (SMOTE) and Particle Swarm Optimization (PSO), for the prediction of diabetes. While previous studies have explored the application of machine learning algorithms for diabetes prediction, few have examined the synergistic effects of integrating SMOTE and PSO with the C4.5 algorithm specifically.
Neural Network Optimization Using Hybrid Adaptive Mutation Particle Swarm Optimization and Levenberg-Marquardt in Cases of Cardiovascular Disease Cahyani, Rima Ayu; Purwinarko, Aji
Recursive Journal of Informatics Vol 2 No 2 (2024): September 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v2i2.78550

Abstract

Abstract. Cardiovascular disease is a condition generally characterized by the narrowing or blockage of blood vessels, which can lead to heart attacks, chest pain, or strokes. It is the leading cause of death worldwide, accounting for approximately 31% or 17.9 million deaths each year globally. Deaths caused by cardiovascular disease are projected to continue increasing until 2030, with the number of patients reaching 23.3 million. As cases of death due to cardiovascular disease become more prevalent, early detection is crucial to reduce mortality rates. Purpose: Many previous researchers have conducted studies on predicting cardiovascular disease using neural network methods. This study extends these methods by incorporating feature selection and optimization with Hybrid AMPSO-LMA. The research is designed to explore the implementation and predictive outcomes of Hybrid AMPSO-LMA in optimizing MLP for cases of cardiovascular disease. Methods/Study design/approach: The first step in conducting this research is to download the Heart Disease Dataset from Kaggle.com. The dataset is processed through preprocessing by removing duplicates and transforming the data. Then, data mining processes are carried out using the MLP algorithm optimized with Hybrid AMPSO-LMA to obtain results and conclusions. This system is designed using the Python programming language and utilizes Flask for website access in HTML. Result/Findings: The research results demonstrate that the method employed by the author successfully improves the accuracy of predicting cardiovascular disease. Predicting cardiovascular disease using the MLP algorithm yields an accuracy of 86.1%, and after optimization with Hybrid AMPSO-LMA, the accuracy increases to 86.88%. Novelty/Originality/Value: This effort will contribute to the development of a more reliable and effective cardiovascular disease prediction system, with the goal of early identification of individuals exhibiting symptoms of cardiovascular disease.
Implementation of Synthetic Minority Oversampling Technique and Two-phase Mutation Grey Wolf Optimization on Early Diagnosis of Diabetes using K-Nearest Neighbors Arsyadani, Fathan; Purwinarko, Aji
Recursive Journal of Informatics Vol 1 No 1 (2023): March 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v1i1.64406

Abstract

Abstract. Diabetes is a disease attacking the endocrine system characterized by high blood sugar levels. International Diabetes Federation (IDF) estimates that there were 451 million people with diabetes globally in 2017. Without treatment, this number is expected to rise to 693 million by 2045. One method for preventing increases in the number of diabetics is by early diagnosis. In an era where technology has developed rapidly, early diagnosis can be made with the machine learning method using classification. In this study, we propose a diabetes classification using K-Nearest Neighbors (KNN). Before classifying the data, we select the best feature subset from the dataset using Two-phase Mutation Grey Wolf Optimization (TMGWO) and balance the training data using Synthetic Minority Oversampling Technique (SMOTE). After dividing the dataset into training and testing sets using 10-fold cross validation, we reached an accuracy of 98.85% using the proposed method. Purpose: This study aims to understand how to apply TMGWO and SMOTE to classify the early stage diabetes risk prediction dataset using KNN and how it affects the results. Methods/Study design/approach: In this study, we use TMGWO to make a feature selection on the dataset, K-fold cross validation to split the dataset into training and testing sets, SMOTE to balance the training data, and KNN to perform the classification. The desired results in this study are accuracy, precision, recall, and f1-score. Result/Findings: Performing classification using KNN with only features selected by TMGWO and balancing the training data using SMOTE gives an accuracy rate of 98.85%. From the results of this research, it can be concluded that the proposed algorithm can give higher accuracy compared to previous studies. Novelty/Originality/Value: Implementing TMGWO to perform feature selection so the model can perform classification with fewer features and implementing SMOTE to balance the training data so the model can better classify the minority class. By doing classification using fewer features, the model can perform classification with a shorter computational time compared to using all features in the dataset.
Co-Authors Adi, Mahargjo Hapsoro Aditya Marianti Akhmad Munawar Alfa Narendra Alfandy Himawan Bagus Rafli Amalia Langgundi, Fitri Amidi Amidi Amin Retnoningsih Amirul Mukminin Anggyi Trisnawan Putra Annindya Ardiansari Ardhi Prabowo Arif Widiyatmoko, Arif Arsyadani, Fathan Aryono Adhi, Aryono Bambang Sugiantoro Budi Prasetiyo, Budi Budiman, Kholiq Cahyani, Rima Ayu Damayanti, Dela Rista Dela Rista Damayanti Dimarti, Safira Chairani Edi Subkhan, Edi Fathan Arsyadani Fianti Fianti, Fianti Fitri Arum Sasi, Fitri Arum Fridiyanto, Fridiyanto Hakim, M. Faris Al Hapsari, Renita Arianti Hasan Mukhibad Hasani, Azharu Alfi Ian Yulianti, Ian Indah Urwatin Wusqo Insan , Shiva Maulana Khoiru Kasinyo Harto Langlang Handayani Lutfia Nur Hadiyanti, Lutfia Nur Mahargjo Hapsoro Adi Majidah Majidah Martien Herna Susanti Melati, Inaya Sari Melissa Salma Darmawan MHD. Reza M.I. Pulungan Muhamad Taufiq Munawar, Akhmad Mutoriq, Alfat Nor Hafizah Ngajikin Nuni Widiarti Nur Kusuma Dewi Putra, Ngurah Made Darma Rahmawati, Sinta Kurnia Renita Arianti Hapsari Rima Ayu Cahyani Ririanti, Novia Puji Sri Siswati Subagja, Mona Subhan Subhan Sugiyarta Stanislaus, Sugiyarta Sujarwata Sujarwata Sukestiyarno Sukestiyarno Susilo Susilo Syuja Zhafran Rakha Krishandhie Syukron Salam, Syukron Tris Sugiarto Tsabit Azinar Ahmad Utis Sutisna Wahyu Hardyanto Widiyanto Widiyanto Woro Sumarni Yanuarto, Alfath YB. Praharto Yuliantika, Atika