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All Journal Dinamika Informatika WARTA Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) E-Dimas: Jurnal Pengabdian kepada Masyarakat Fountain of Informatics Journal Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika INTEGER: Journal of Information Technology Turbo : Jurnal Program Studi Teknik Mesin JTERA (Jurnal Teknologi Rekayasa) Jurnal Informatika Universitas Pamulang JIPN (Journal of Informatics Pelita Nusantara) JIP (Jurnal Informatika Polinema) Multitek Indonesia : Jurnal Ilmiah KOMPUTEK JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) ScientiCO : Computer Science and Informatics Journal Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Teknik Informatika C.I.T. Medicom International Journal of Science, Engineering and Information Technology Journal of Computer, Electronic, and Telecommunication (COMPLETE) Insyst : Journal of Intelligent System and Computation International Journal Artificial Intelligent and Informatics Makara Journal of Science Literasi: Jurnal Pengabdian Masyarakat dan Inovasi
Ghulam Asrofi Buntoro
Universitas Muhammadiyah Ponorogo
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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Analisis Sentimen Calon Gubernur DKI Jakarta 2017 Di Twitter Buntoro, Ghulam Asrofi
INTEGER: Journal of Information Technology Vol 2, No 1 (2017): Maret 2017
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.3 KB) | DOI: 10.31284/j.integer.2017.v2i1.95

Abstract

Abstract. Jakarta Governor Election 2017 discussed in society or internet, especially Twitter. Everyone is free opine on Jakarta governor candidate 2017 so many opinions, not only positive or neutral opinion but also negative. Social media, especially Twitter now become promotions or campaigns are effective and efficient. This research is expected be useful to conduct on public opinion containing sentiment positive, neutral or negative. The method used in this study, for data preprocessing using tokenisasi, cleansing and filtering, to define class sentiment with methods Lexicon Based. For classification using Naive Bayes classifier (NBC) and Support Vector Machine (SVM). The data is 300 tweet in Indonesian by keyword AHY, Ahok, Anies. The results of research is analysis sentiment Jakarta governor candidate 2017. The highest accuracy when using the method of classification Naïve Bayes Classifier (NBC), with average 95% accuracy, 95% precision, 95% recall, TP rate 96,8% and TN rate 84,6%.Keywords: analisis sentimen, jakarta governor candidate 2017, lexicon based, naïve bayes classifier, support vector machineAbstrak. Pemilihan Gubernur DKI Jakarta 2017 ramai diperbincangkan di dunia nyata maupun dunia maya, khususnya di media sosial Twitter. Semua orang bebas berpendapat atau beropini tentang calon Gubernur DKI Jakarta 2017 sehingga memunculkan banyak opini, tidak hanya opini yang positif atau netral tapi juga yang negatif. Media sosial khususnya Twitter sekarang ini menjadi salah satu tempat promosi atau kampanye yang efektif dan efisien. Penelitian ini diharapkan dapat bermanfaat membantu untuk melakukan riset atas opini masyarakat yang mengandung sentimen positif, netral atau negatif. Metode yang digunakan dalam penelitian ini, untuk preprocessing data menggunakan tokenisasi, cleansing dan filtering, untuk menentukan class sentimen dengan metode Lexicon Based. Untuk proses klasifikasinya menggunakan metode Naïve Bayes Classifier (NBC) dan Support Vector Machine (SVM). Data yang digunakan adalah tweet dalam bahasa Indonesia dengan kata kunci AHY, Ahok, Anies, dengan jumlah dataset sebanyak 300 tweet. Hasil dari penelitian ini adalah analisis sentimen terhadap calon gubernur DKI Jakarta 2017. Akurasi tertinggi didapat saat menggunakan metode klasifikasi Naïve Bayes Classifier (NBC), dengan nilai rata-rata akurasi mencapai 95%, nilai presisi 95%, nilai recall 95% nilai TP rate 96,8% dan nilai TN rate 84,6%.Kata Kunci: analisis sentimen, calon gubernur dki jakarta 2016, lexicon based, naïve bayes classifier, support vector machine
PELATIHAN PEMANFAATAN BARANG BEKAS UNTUK PEMBUATAN BUKET BUNGA DAN CARA PEMASARANNYA Astuti, Indah Puji; Buntoro, Ghulam Asyrofi; Ariyadi, Dwiyono
WARTA WARTA LPM Vol. 22, No. 1, Maret 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (545.47 KB) | DOI: 10.23917/warta.v21i2.7739

Abstract

Waste is one of the problems that often arise in life society. However, many ways are considered wiser in solving problems with garbage. One of them is by using it to produce new products that have economic value. Not only can it reduce the garbage stack, but this method can also bring additional income. This service activity was carried out in the village of Bulu Lor, Jambon Subdistrict, Ponorogo Regency. Aim to provide training in making a bouquet by utilizing used items to homemakers and their youth. Besides, it also teaches how to market handicraft products to be known to more quickly, so the possibility of selling products is getting bigger. The result of this activity is to increase entrepreneurial skills to the community by providing capabilities to homemakers and youth in making flower bouquets and teaching how to market product results online. Keywords: Waste, bucket flower, entrepreneurship, online marketing
Pemanfaatan Biogas Kotoran Sapi untuk Heater Kandang Ayam Jowo Super Winangun, Kuntang; Buntoro, Ghulam Asrofi; Puspitasari, Indah; Ain, M. Fadyanto Handynur
DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Vol 3, No 2 (2019)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.772 KB) | DOI: 10.32486/jd.v3i2.368

Abstract

Program Kemitraan Masyarakat (PKM) yang didanai oleh Kementerian Riset, Teknologi, dan Pendidikan Tinggi melalui Direktorat Riset dan Pengabdian Masyarakat Direktorat Jenderal Riset dan Pengembangan ini bertujuan untuk pembuatan biogas dari kotoran sapi untuk pemanas kandang ayam jowo super. Hal ini dilakukan agar mitra lebih efektif dalam pemanfaatan kotoran sapi yang selama ini hanya dibuang tanpa dikelola dengan maksimal. Biogas kotoran sapi kemudian dimanfaatkan kembali untuk pemanas kandang ayam jowo super oleh mitra. Selain bantuan teknologi, juga memberi pendampingan penggunaan alat kepada masyarakat mitra agar mampu menggunakan alat tersebut. Target kegiatan Program Kemitraan Masyarakat (PKM) ini adalah pembuatan digester biogas, pembuatan pemanas untuk kandang ayam jowo super, dan publikasi media masa agar lebih dikenal masyarakat luas. Metode pendekatan yang digunakan dalam kegiatan Program Kemitraan Masyarakat (PKM) ini adalah pendidikan dan pelatihan, pendampingan, evaluasi. Teknik pelaksanaan kegiatan dilakukan dengan cara memberikan motivasi usaha, pembimbingan manajemen usaha, pelatihan keterampilan masyarakat dalam pembuatan biogas dari kotoran sapi, pelatihan penggunaan alat pemanas kandang ayam jowo super. Diharapkan kegiatan ini dapat mengatasi permasalahan mitra khususnya dalam pemanfaatan kotoran sapi dan pembuatan pemanas kandang ayam jowo super.
Sentiments Analysis for Governor of East Java 2018 in Twitter Buntoro, Ghulam Asrofi
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 3 No 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (187.882 KB) | DOI: 10.33395/sinkron.v3i2.10025

Abstract

The East Java Governor Election which will be held in 2018 is also felt in the virtual world especially Twitter social media. All people freely argue about their respective governor candidates, the memorandum raises many opinions, not only positive or neutral but also negative opinions. Media growth is so rapid, revealing a lot of online media from the news media to social media. Social media alone is Facebook, Twitter, Path, Instagram, Google+, Tumblr, Linkedin and many more. Today's social media is not only used as a means of friendship or making friends, but also for other activities. Promos of trading or buying and selling, until political party promos or campaigns of candidates for regents, governors, legislative candidates until presidential candidates. The research objective is to conduct a method of analyzing the sentiments of 2018 East Java Governor candidates on Twitter social media with optimal and maximum optimization. While the benefits are to help the community conduct research on opinions on twitter which contains positive, neutral or negative sentiments. Analysis of the sentiments of East Java Governor candidates in 2018 on twitter social media using non-conventional processes that save costs, time and effort. The results of Khofifah's dataset are 77% accuracy, 79.2% precision value, 77% recall value, 98.6% TP rate and 22.2% TN rate. For the results of Gus dataset, the accuracy is 76%, the precision value is 74.4%, the recall value is 76%, the TP rate is 93.8% and the TN rate is 52.9%.
PREDIKSI PENYEBARAN PENYAKIT TBC DENGAN METODE K-MEANS CLUSTERING MENGGUNAKAN APLIKASI RAPIDMINER Al-Rizki, Muhammad Farid Iqbal; Widaningrum, Ida; Buntoro, Ghulam Asrofi
JTERA (Jurnal Teknologi Rekayasa) Vol 5, No 1: June 2020
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1227.115 KB) | DOI: 10.31544/jtera.v5.i1.2019.1-10

Abstract

Penambangan data (data mining) bertujuan untuk mendapatkan informasi penting yang bisa memberikan nilai tambah dari sekumpulan data yang sangat besar. Clustering merupakan salah satu teknik yang ada dalam data mining yang digunakan untuk mengumpulkan dataset pada database berdasarkan kriteria yang telah ditentukan. Clustering dapat digunakan salah satunya di bidang kesehatan, seperti untuk memprediksi penyebaran penyakit di suatu tempat. Tujuan dari penelitian ini untuk menentukan pola penyebaran penyakit Tuberculosis (TBC) yang terjadi di Kabupaten Ponorogo menggunakan algoritma K-Means Clustering dengan Cross-Industry Standard Process for Data Mining (CRISP-DM) yang merupakan standar pengolahan data mining untuk sebuah institusi maupan industri. Penelitian ini dapat digunakan sebagai data rujukan untuk Dinas Kesehatan Kabupaten Ponorogo dalam penanganan penyebaran penyakit TBC di Kabupaten Ponorogo. Berdasarkan hasil penelitian, diperoleh accuracy dan performa Area under the Curve (AUC) dari K-Means sebesar 84,13% dan 0,837. Pola penyebaran penyakit TBC tertinggi terdapat di daerah Puskesmas Ngebel, disusul kemudian daerah Puskesmas Babadan.
ANALISIS SENTIMEN HATESPEECH PADA TWITTER DENGAN METODE NAÏVE BAYES CLASSIFIER DAN SUPPORT VECTOR MACHINE Buntoro, Ghulam Asrofi
Dinamika Informatika Vol 5, No 2 (2016): Jurnal Dinamika Informatika Volume 5 Nomor 2
Publisher : Universitas PGRI Yogyakarta

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

Abstract

Today, social media, especially Twitter have enormous influence to the success or ruin the image of a person. Many movements are carried out in social media, especially Twitter, all of which can influence its success. There is a movement that aims good there is also a movement with malicious purposes, namely hatred to others. Usually the movement on Twitter was done using the hashtag (#), the latest movement there tagar Hatespeech (#HateSpeech), viewed from the name is already clear that hate speech. This study analyzes the hashtag proficiency level, all justified by the hashtag was the sentiment of hate. The classification process in this study using the method of classification Naive Bayes classifier (NBC) and Support Vector Machine (SVM) with the data preprocessing using tokenisasi, cleansing and filtering. The data used are in Indonesian tweet with the hashtag HateSpeech (#HateSpeech), with the number of datasets as much as 522 tweets were distributed evenly into two sentiments HateSpeech and GoodSpeech. The highest accuracy of results obtained when using the method of classification Support Vector Machine (SVM) with tokenisasi unigram, stopword list Indonesian and emoticons, with the average value reached 66.6% accuracy, precision value of 67.1%, 66.7% recall value TP value rate of 66.7% and 75.8% rate the value TN.
Analisis Sentimen Calon Gubernur Jawa Timur 2018 di Twitter Buntoro, Ghulam Asrofi
ScientiCO : Computer Science and Informatics Journal Vol 1, No 2 (2018): Scientico : November
Publisher : Fakultas Teknik, Universitas Tadulako

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

Abstract

The East Java Governor Election 2018 is also felt in the virtual world especially Twitter. All people freely argue about their respective governor candidates, memorandum raises many opinions, not only positive or neutral also negative opinions. Media growth is so rapid, revealing a lot of online media from the news media to social media. Today's social media is not only used of friendship, but also for other activities. Promos of trading or buying and selling, until political party promos or campaigns of candidates for regents, governors, legislative candidates until presidential candidates. The research objective is to conduct a method of Sentiments Analysis for Governor candidates East Java 2018 in twitter with optimal and maximum optimization. While the benefits are to help the community conduct research on opinions on twitter which contains positive, neutral or negative sentiments. Sentiments Analysis for Governor candidates East Java 2018 in twitter using non-conventional processes that save costs, time and effort. The results of Khofifah's dataset are 77% accuracy, 79.2% precision, 77% recall, 98.6% TP rate and 22.2% TN rate. For the results of GusIpul dataset, accuracy is 76%, precision 74.4%, recall 76%, the TP rate is 93.8% and the TN rate is 52.9%.
Rancang Bangun Aplikasi Belajar Membaca dengan Gambar Animasi Berbasis Android Buntoro, Ghulam Asrofi; Indah Puji Astuti; Dwiyono Ariyadi
Jurnal Informatika Polinema Vol 7 No 3 (2021): Vol 7 No 3 (2021)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v7i3.689

Abstract

[Retracted] The Prototype of the Reading Learning Application uses Animated images on Android with the Black Box Testing Method Buntoro, Ghulam Asrofi; Astuti, Indah Puji; Ariyadi, Dwiyono
Jurnal Informatika Universitas Pamulang Vol 6, No 1 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i1.7630

Abstract

This article has been withdrawn by the author (Ghulam Asrofi Buntoro) via WhatsApp message (+62 852-3507-????) on 20 August 2021 at 14:23. He stated that the article "The Prototype of the Reading Learning Application uses Animated images on Android with the Black Box Testing Method" written by Ghulam Asrofi Buntoro, Indah Puji Astuti, and Dwiyono Ariyadi had been published in another journal. Artikel ini telah ditarik kembali oleh penulis (Ghulam Asrofi Buntoro) melalui pesan WhatsApp (+62 852-3507-????) pada tanggal 20 Agustus 2021 jam 14:23. Dia menyatakan bahwa artikel dengan judul "The Prototype of the Reading Learning Application uses Animated images on Android with the Black Box Testing Method" yang ditulis oleh Ghulam Asrofi Buntoro, Indah Puji Astuti, dan Dwiyono Ariyadi telah diterbitkan di jurnal lain.
PELATIHAN PEMANFAATAN BARANG BEKAS UNTUK PEMBUATAN BUKET BUNGA DAN CARA PEMASARANNYA Indah Puji Astuti; Ghulam Asyrofi Buntoro; Dwiyono Ariyadi
WARTA LPM WARTA LPM, Vol. 22, No. 1, Maret 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/warta.v21i2.7739

Abstract

Waste is one of the problems that often arise in life society. However, many ways are considered wiser in solving problems with garbage. One of them is by using it to produce new products that have economic value. Not only can it reduce the garbage stack, but this method can also bring additional income. This service activity was carried out in the village of Bulu Lor, Jambon Subdistrict, Ponorogo Regency. Aim to provide training in making a bouquet by utilizing used items to homemakers and their youth. Besides, it also teaches how to market handicraft products to be known to more quickly, so the possibility of selling products is getting bigger. The result of this activity is to increase entrepreneurial skills to the community by providing capabilities to homemakers and youth in making flower bouquets and teaching how to market product results online. Keywords: Waste, bucket flower, entrepreneurship, online marketing
Co-Authors Agung Purniawan Agung Purniawan, Agung Ain, M. Fadyanto Handynur Al-Rizki, Muhammad Farid Iqbal Aliyadi Aliyadi Anas Nurgito Arifin, Rizal Arifin, Rizal Arin Yuli Astuti Atok Setiyawan Bambang Sudarmanta Charisma Audia Maghribi Didik Riyanto Dimas Aditya Dimas Nando Putro Widodo Dwiyono Ariyadi Dwiyono Ariyadi Dwiyono Ariyadi Dwiyono Ariyadi, Dwiyono Dyah Mustikasari Emi Wulandari Fauzan Masykur Heru Prasetya Ida Widaningrum, Ida Indah Puji Astuti Indah Puji Astuti Indah Puji Astuti Indah Puji Astuti INDAH PUSPITASARI KUNTANG WINANGUN Kuntang Winangun Miftakhul Arifin Moh Bhanu Setyawan Muh Ardiansyah Muhammad Farid Iqbal Al-Rizki Muhammad Furqon Fadli Munaji Munaji Munaji, Munaji Nizar Faisal Hakim Rachmad Mahendrajaya Rico Agus Prasetyo Riki Widiantoro Robi Etdji Pangestu Roikhatul Jannah Tinovia Prasetyo Tomi Wingga Pratama Wildan Muhammad Aminuddin Yoga Prasetia