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Jumanto Jumanto, Jumanto
Faculty of Humanities, Dian Nuswantoro University
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Pengaruh Model Pembelajaran RADEC (Read, Answer, Discuss, Explain and Create) terhadap Keterampilan Berpikir Kritis Peserta Didik dalam Menyelesaikan Soal Cerita Kelas V SD Negeri Madyotaman Surakarta Widyasari, Alma; Wicaksono, Anggit Grahito; Jumanto, Jumanto
Jurnal Pendidikan Tambusai Vol. 8 No. 2 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

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Abstract

Dilaksanakannya penelitian ini bertujuan dalam mengetahui pengaruh model pembelajaran RADEC terhadap keterampilan berpikir kritis peserta didik dalam menyelesaikan soal cerita pada kalas V SD Negeri Madyotaman Surakarta. Peneliti menggunakan kuantitatif pre-experimental dengan one group pretest-posttest sebagai desainnya terhadap semua peserta didik di SD Negeri Madyotama Surakarta tepatnya kelas V berjumlah 26 peserta didik yang ditetapkan melalui teknik sampling jenuh. Data dikumpulkan dengan dokumentasi, wawancara, dan tes pada seluruh sampel. Kemudian hasilnya diuji dengan uji normalitas dan uji t-test. Hasilnya membuktikan bahwa ada pengaruh pada penerapan model pembelajaran RADEC terhadap keterampilan berpikir kritis peserta didik kelas V SD Negeri Madyotaman Surakarta dalam menyelesaikan soal cerita sebab nilai sig tidak melebihi 0,05 yakni 0,000. Dinyatakan juga bahwa Ha diterima sementara H0 ditolak sebab thitung melebihi nilai ttabel yakni 17.403 > 2.060 sesuai perhitungan t-testnya. Dibuktikan juga bahwa posttest yang dilaksanakan mendapat rata-rata senilai 68,08 sementara pretest-nya senilai 46,73.
Pengaruh Penerapan Model Pembelajaran RADEC terhadap Kemampuan Berpikir Kritis pada Mata Pelajaran IPAS Peserta Didik Kelas I Ferdiansyah, Dicky; Handayani, Sri; Jumanto, Jumanto
Jurnal Pendidikan Tambusai Vol. 8 No. 2 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

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Abstract

ABSTARK
Translation techniques of the positive politeness utterances in the Pay It Forward movie Widiaswara, R. Anantama; Jumanto, Jumanto
Diglosia: Jurnal Kajian Bahasa, Sastra, dan Pengajarannya Vol 7 No 2 (2024)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/diglosia.v7i2.932

Abstract

This descriptive qualitative research employed the methods of observation and auto-expert judgment for the data collection and applied Brown & Levinson’s politeness theory (1987) and Molina & Albir’s translation theory (2002) for the data analysis. This research focused on finding the positive politeness strategies and the translation techniques of the utterances obtained from Pay It Forward movie as the data source. Based on the findings of the research, there were 40 utterances with positive politeness strategies as the data under analysis. The research findings, among others, showed that the strategies of Intensify interest to hearer (17.50%) and Exaggerate (17.50%) were dominantly used in the Pay It Forward movie, while the translation strategy of Established equivalent (40.00%) was mostly used in the translation of positive politeness utterances in the movie. It can be concluded here that the translator translates the positive politeness utterances of the source language (English) into the target language (Indonesian) appropriately through the Established equivalent strategy without making any significant changes to maintain the meaning relatively the same in the Indonesian translation subtitles.
Deep Learning Model Implementation Using Convolutional Neural Network Algorithm for Default P2P Lending Prediction Nikmah, Tiara Lailatul; Jumanto, Jumanto; Prasetiyo, Budi; Fitriani, Nina; Muslim, Much Aziz
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26366

Abstract

Peer-to-peer (P2P) lending is one of the innovations in the field of fintech that offers microloan services through online channels without intermediaries. P2P  lending facilitates the lending and borrowing process between borrowers and lenders, but on the other hand, there is a threat that can harm lenders, namely default.  Defaults on  P2P  lending platforms result in significant losses for lenders and pose a threat to the overall efficiency of the peer-to-peer lending system. So it is essential to have an understanding of such risk management methods. However, designing feature extractors with very complicated information about borrowers and loan products takes a lot of work. In this study, we present a deep convolutional neural network (CNN) architecture for predicting default in P2P lending, with the goal of extracting features automatically and improving performance. CNN is a deep learning technique for classifying complex information that automatically extracts discriminative features from input data using convolutional operations. The dataset used is the Lending Club dataset from P2P lending platforms in America containing 9,578 data. The results of the model performance evaluation got an accuracy of 85.43%. This study shows reasonably decent results in predicting p2p lending based on CNN. This research is expected to contribute to the development of new methods of deep learning that are more complex and effective in predicting risks on P2P lending platforms.
Analysis of quality of service (QoS) wi-fi network in UNNES digital center building using wireshark Rianto, Nur Aziz Kurnia; Salsabila, Halimah; Jumanto, Jumanto
Journal of Student Research Exploration Vol. 1 No. 1: January 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v1i1.108

Abstract

The need for the internet is a very absolute target in today's all-digital era. The traffic of information that is so dense and always dynamic every second makes everyone want speed in capturing information circulating. The speed in gathering information in this all-digital era cannot be separated from the internet and networks. UNNES Digital Center is one of the facilities owned by Semarang State University which is used as a digital-based learning center to support the realization of the Smart Digital Campus. The availability of qualified network services at the UNNES Digital Center is needed to support the all-digital-based student learning process. This research was done to find out how fast and good the quality of the internet network provided by the UNNES Digital Center is. In the research conducted, the network analysis step uses the Quality of Service (QoS) method. In obtaining research data that will be used as a basis for analyzing throughput, packet loss, delay, and network jitter, Wireshark software is used as a tool. The research results show that the quality of the Digital Center's internet network is very good and very adequate for digital learning activities. This is evidenced by a network throughput value of 6122.37 /kbits/s, a packet loss value of 0.7%, a delay of 214 ms with a moderate or quite good value and jitter = 0.511 ms.
Increased accuracy in predicting student academic performance using random forest classifier Mulyana, Aditya Fajar; Puspita, Wiyanda; Jumanto, Jumanto
Journal of Student Research Exploration Vol. 1 No. 2: July 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v1i2.169

Abstract

This research aims to classify the academic performance of students who are successful and who have dropped out of school with high accuracy so that these matters can be addressed quickly. Things like this need fast handling to find out what factors influence it. In addition, this research was conducted to test how good the random forest algorithm is in classifying a problem. Random forest, which includes an algorithm that is commonly used for classifying a problem. By using the random forest algorithm, the accuracy results will be better than a single decision tree. This algorithm is quite good at handling and managing large datasets. From this study it can be concluded that this method can provide good prediction accuracy with a fairly high level of accuracy, namely 89%. Utilization of this random forest can be an alternative in classifying student academic achievement. This algorithm can work well in handling large datasets. This study discusses how the use of Random Forest can work to classify students' academic performance.
Subtitling Strategies Used in Translating Cultural Words in The Subtitle of Disney Animation Movie: Coco Subrata, Monika Rosalia; Jumanto, Jumanto
Journal of linguistics, culture and communication Vol 1 No 1 (2023): Journal of Linguistics, Culture, and Communication
Publisher : CV. Rustam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61320/jolcc.v1i1.1-25

Abstract

The study aims to identify the subtitling strategies used in translating cultural words in the subtitle of Disney Animation Movie: Coco. This descriptive qualitative study employed the data in words, sentences, and logical arguments related to the topic. The data were English combined with Spanish subtitle as the source language and Indonesian subtitles as the target language. The theories used in the analyzing process and describing the analysis were the classification of cultural words by Newmark (1988:94-103) and the subtitling strategies based on Gottlieb's theory (1992:66). There were 100 cultural words found in the subtitles, which were divided into five classifications of cultural words, namely: Ecology (26%), Material Culture (22%), Social Culture (20%), Gesture and Habit (18%) and also Organization (14%). On the other hand, after the researcher grouped the cultural words, then the words were analyzed using the subtitling strategies theory of Gottlieb (1992), in which the subtitling strategies were divided into ten types: Transfer (41%), Imitation (14%), Transcription (14%), Paraphrase (7%), Expansion (7%), Deletion (4%), Condensation (3%), Dislocation (3%), Decimation (2%), and Resignation (2%). The dominant subtitling strategy in translating the cultural words is Transfer with 41 data. Based on the analysis result, within this mainly used Transfer strategy, the translator directly translated the text, word-to-word, so that the translation result in the subtitle becomes complete and accurate with its literal meaning according to the source language.
Contrastive Analysis Between English Medical Terms with Affixes and Their Indonesian Equivalent in Dorland’s Illustrated Medical Dictionary Lutfiyah, Nur Indah Sulistyowati; Jumanto, Jumanto
Journal of linguistics, culture and communication Vol 1 No 2 (2023): Journal of Linguistics, Culture, and Communication
Publisher : CV. Rustam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61320/jolcc.v1i2.126-140

Abstract

Medical terms are language units used to describe medical conditions such as diseases, symptoms, anatomy, and procedures. Medical terms are composed of a combination of affixes and root words. This research focused on contrastive analysis, a study comparing two languages, the source language and their equivalent in the target language. This study aims (1) to find out similarities between English medical terms with affixes in English and their Indonesian equivalents in Dorland's Illustrated Medical Dictionary (2) to find out differences between English medical terms with affixes in English and their Indonesian equivalents in Dorland's Illustrated Medical Dictionary (3) to predict learning problems based on the differences between English medical terms with affixes in English and their Indonesian equivalents in Dorland's Illustrated Medical Dictionary. The data source of this research is "Dorland's Illustrated Medical Dictionary 31st edition" by W.A. Newman Dorland and translated into Indonesian under the title " Kamus Kedokteran Dorland Edisi 3" by Retna Neary Elseria et al. This research is qualitative, and the type of research is library research. The study's results revealed seven affix English medical terms that have similarities with Indonesian equivalents and 93 terms that differ from Indonesian equivalents. The similarities and differences are divided into prefixes and suffixes. There are 8 types of prefixes and 4 types of suffixes. Predictions of problems that may occur in these conditions are in different forms, uses, and meanings. This research is expected to help better understand affixes in English medical terms and their Indonesian equivalents. 
Pondering a Global BIPA: Politeness and Impoliteness in Verbal Interactions Jumanto, Jumanto; Rahayu, Emik
Journal of Pragmatics Research Vol 2, No 2 (2020): Journal of Pragmatics Research
Publisher : State institute of islamic studies salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18326/jopr.v2i2.97-112

Abstract

This opinionated research article is about politeness and impoliteness in verbal interactions within Indonesian interpersonal context. Accounts on politeness, camaraderie, distant language, close language, code-switching, and code-mixing are elaborated to come to the concept of impoliteness, i.e. rude situations and awkward situations. The interpersonal context here partly elaborates the types of hearer in the aspects of power and solidarity in Brown and Gilman’s theory (1968), the hearers of which are divided into superiors and close people in this article. Elements of both the Indonesian distant and close languages are presented, and how rude situations and awkward situations happen due to incompetence or ignorance of the two variants is illustrated. Illustrations of the Indonesian two variants and code-mixing of the two are given to highlight the rude and awkward situations. All this worldview on the teaching of Indonesian to non-native-speakers, i.e. pondering a global BIPA, should be regarded as efforts to develop as well as to market the Indonesian language to the global societies.              Keywords Politeness, camaraderie, impoliteness, distant language, close language, rude situation, awkward situation, incompetence, code-switching, code-mixing, BIPA  
The Analysis of Impoliteness within Grammar Nazi Context in Twitter Tweets Soehendro, Eunike Imanuela; Jumanto, Jumanto
Journal of Pragmatics Research Vol 4, No 1 (2022): Journal of Pragmatics Research
Publisher : State institute of islamic studies salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18326/jopr.v4i1.73-92

Abstract

This research focuses on one of the phenomena namely the Grammar Nazi phenomenon. In the present paper, the Grammar Nazi phenomenon was a phenomenon where people did not hesitate to criticize other people's grammatical errors. This phenomenon of Grammar Nazi was associated with the theory of Impoliteness Strategy by Culpeper (1996). This research is a qualitative one, where 100 data employed were processed first using a coding technique. The results obtained from this study are 55% of the data using the Bald on Record strategy, 18% of the data using the Sarcasm or Mock Politeness strategy, 16% of the data using the Negative Impoliteness strategy, 11% of the data using the Positive Impoliteness strategy, while 0% data using the Withhold Politeness strategy. It was also found that 61% of the data of the Grammar Nazi phenomenon used verbal bullying only to attack the face of authors of the posts, while the remaining 39% of the data used verbal bullying with intentions to correct grammatical errors, hence providing benefits for authors of the posts. The Grammar Nazi phenomenon also has a different impact on everyone. It can be seen from the characteristics of the utterances used by the Grammar Nazi.Keywords: Grammar Nazi, Grammar Nazi Phenomenon, Impoliteness Strategy, Five Strategies, Twitter.
Co-Authors Ade Parlaungan Nasution, Ade Parlaungan Adi, Yogi Kuncoro Agus Harjoko Agustiani, Agustiani Al Hakim, M. Faris Alabid, Noralhuda N. Alamsyah - Anggit Grahito Wicaksono Apsari, Fitri Noor Ari Widodo Ascarya, Farrel Aulia, Muhammad Kahfi Aurelia, Bening Febri Badriyah, Fitria Nurul Budi Prasetiyo, Budi Chairunnisa, Tsania Damayanti, Dela Rista Dewi, Meilina Taffana Dullah, Ahmad Ubai Dwi Anggraeni Dwi Eko Waluyo DWI HAPSORO Ema Butsi Prihastari Ratna Widyaningrum, Ema Butsi Prihastari Endang Sugiharti, Endang Faizal Risdianto Fatahillah, Dimas Ferdiansyah, Dicky Feri Faila Sufa, Feri Faila HAJRIAL ASWIDINNOOR Hakim, M. Faris Al Hanafi Hanafi Handayani, Sri Haryati Sulistyorini Hendra Kurniawan Herlina Kurniawati Hidayat Hidayat Ilham Maulana Irmade, Oka Jati, Ismail Wahyu Khalifah, Viera Nur Khoirunnisa, Avicenia Nasywa KURNIATI, SRI AYU Kusuma, Novelia Salsa Dara Lestari, Apri Dwi Lintang, Irendra Luh Titi Handayani, Luh Titi Lutfiyah, Nur Indah Sulistyowati Machfudz, Machfudz Mardiansyah, M Fadil Marshanda, Putri Martha Yohana Sinaga Masa, Amin Padmo Azam Mellisa, Mellisa Minghat, Asnul Dahar Bin Much Aziz Muslim Mukarom, Rosyid Fadhil Al Mulyana, Aditya Fajar Mulyaningtyas, Lintang Ayu Murtafiah, Eni Muzayanah, Rini Nikmah, Tiara Lailatul Nina Fitriani, Nina Ningsih, Maylinna Rahayu Nugraha, Faizal Widya NUGROHO, MUHAMMAD IRFAN Pertiwi, Dwika Ananda Agustina Prabaswara, Ireneus Prabowo Yudo Jayanto Pratama, Rizka Nur Prihatsari, Ema Butsi Puji Purwatiningsih, Aris Pulung Nurtantio Andono Puspita, Wiyanda Putri, Chindi Dwi Ayu Prabowo Putri, Salma Aprilia Huda Raden Arief Nugroho Rahayu, Emik Rahmanti Asmarani Ramadhan, Taufiq Brahmantyo Lintang ramayanti, ismarita Rawat, Bibek Rianto, Nur Aziz Kurnia Riza Arifudin Rizkasari, Elinda Rofik Rofik, Rofik RUSMILAH SUSENO Sa'ud, Udin Syaefudin Sagimin, Eka Margianti Salsabila, Halimah Sam’an, Muhammad Sarafuddin, Sarafuddin Sinaga, Markus Soehendro, Eunike Imanuela Subhan Subhan Subrata, Monika Rosalia Sudarsono Sugiaryo, Sugiaryo Syamsu Rizal, Sarif Tanzilal Mustaqim Wahyu Sopandi Wibowo, Kevyn Aalifian Hernanda Wibowo, Kevyn Alifian Hernanda Wicaksono, Suntoro Widiaswara, R. Anantama Widyasari, Alma Wijaya, Dandi Indra Yahya Nur Ifriza Yosza Dasril Yulianingsih, Ratri Zaaidatunni'mah, Untsa