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All Journal Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) PROSIDING SEMINAR NASIONAL CENDEKIAWAN Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika NUSANTARA: Jurnal Pengabdian Kepada Masyarakat JURNAL ABDI MASYARAKAT INDONESIA (JAMIN) Intelmatics
Anung B Ariwibowo
Fakultas Teknologi Industri, Universitas Trisakti
Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Social Sciences Other

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APLIKASI PENCATATAN TRANSAKSI KOMUNITAS BAGINDA (BANK SAMPAH GUNUNG INDAH) Indah Pradhipta; Syandra Sari; Anung B Ariwibowo
PROSIDING SEMINAR NASIONAL CENDEKIAWAN Prosiding Seminar Nasional Cendekiawan 2017 Buku III
Publisher : Lembaga Penelitian Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/semnas.v0i0.2517

Abstract

Komunitas Bank Sampah adalah sebuah gerakan masyarakat yang bertujuanmendaur ulang sampah pada rumah-rumah masyarakat dengan sistem pencatatantransaksi untuk setiap anggotanya. Aplikasi Bank Sampah merupakan aplikasi yangbertujuan untuk membantu Komunitas Bank Sampah Gunung Indah (BAGINDA) RW 011Kp. Gunung Utara, Cirendeu dalam melakukan proses bisnis dan transaksi padakomunitas bank sampah, seperti penyetoran sampah, pengeluaran dana, dan pemasukandana. Pada aplikasi ini ada dua pengguna yang dapat memakainya yaitu Admin danNasabah. Pembuatan aplikasi menggunakan bahasa pemrograman JAVA, PHP dan basisdata MySQL. Evaluasi terhadap aplikasi berupa kuesioner menunjukkan dari 32pengguna nasabah 75% memberikan tanggapan yang baik untuk aplikasi ini.
Visualisasi Kinerja dan Persepsi Peserta Program Bangkit 2021 Menggunakan Microsoft Power BI Dedy Sugiarto; Rianti Dewi Sulamet-Ariobimo; Binti Solihah; Ahmad Zuhdi; Ratna Shofiati; Anung Barlianto Ariwibowo; Teddy Siswanto; Dimmas Mulya
Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 13, No 1 (2022): Juni
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jsit.v13i1.2311

Abstract

Penelitian ini bertujuan untuk membangun visualisasi kinerja dan persepsi peserta program Bangkit 2021 Fakultas Teknologi Industri Universitas Trisakti dalam bentuk dasbor. Data berasal dari respon kuesioner peserta Bangkit 2021 terkait dampak program MBKM, data transkrip mahasiswa yang diperoleh dari penyelenggaraan Program Bangkit dan data indeks prestasi mahasiswa yang didapatkan dari sistem informasi akademik (student information system) Universitas Trisakti. Pemodelan data menggunakan model skema bintang dengan tiga tabel fakta yaitu tabel nilai mata kuliah yang diikuti, tabel kehadiran dan status lulus serta tabel kuesioner. Tabel dimensi terdiri atas dimensi jalur pembelajaran, dimensi program studi, dimensi mata kuliah. Hasil visualisasi menunjukkan laporan kinerja dan persepsi peserta dapat dengan mudah dan singkat dilihat dalam masing-masing satu layar yang dapat disaring berdasarkan dimensi program studi, jalur pembelajran maupun mata kuliah yang diikuti. Secara umum 75% dinyatakan lulus penuh (full) dan 25 % lulus sebagian (parsial) serta salah seorang peserta berhasil mendapatkan predikat 50 tim terbaik. Seluruh peserta juga menyatakan kegiatan ini bermanfaat bagi mereka untuk meningkatkan keterampilan dan keahlian serta meningkatkan kemampuan bekerja sama dalam sebuah tim.
PROGRAM KEMITRAAN MASYARAKAT USAHA KECIL MENENGAH DODOL BETAWI MC DI JAKARTA Rina Fitriana; Wawan Kurniawan; Anung Barlianto Ariwibowo; Brahmantyo Anggoro; Ralph Vincent Sapulette; Jaquline Glenadys Siregar
Jurnal Abdi Masyarakat Indonesia (JAMIN) Vol 3 No 2 (2021): JURNAL ABDI MASYARAKAT INDONESIA (JAMIN)
Publisher : Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (702.941 KB) | DOI: 10.25105/jamin.v3i2.10580

Abstract

Program Kemitraan Masyarakat berupa pendampingan untuk Usaha Kecil Menengah (UKM) dodol Betawi di Jakarta. UKM  dodol Betawi  MC merupakan usaha makanan tradisional khas Betawi. UKM dodol MC memiliki keinginan untuk membuat sistem informasi pemasaran, perbaikan kualitas produk, dan diberikan alat untuk menggulung dodol agar mempermudah pengemasan. Tujuan dari Program kemitraan masyarakat adalah untuk melaksanakan pendampingan dengan membangun suatu sistem informasi dalam pemasaran, perbaikan Good Manufacturing Practice (GMP) untuk menjamin kualitas produk. Sistem Informasi Pemasaran berbasis tautan http://dodolhjmamascondet.com/ yang dihasilkan untuk UKM pegusaha dodol Betawi MC bertujuan untuk memasarkan Dodol Betawi atau jenis makanan Betawi lainnya.  Peremajaan Good Manufacturing Practice (GMP) tersebut dilakukan dengan pemberian Tampilan GMP dan masker, sarung tangan, topi,  apron (celemek), dan sepatu. Perancangan dan pembuatan mesin pelinting dodol digunakan untuk mempermudah UKM Dodol untuk menggulung dodol sehingga tidak melakukan penggulungan hanya dengan menggunakan tangan.
PERBANDINGAN KINERJA KLASIFIKASI SENTIMEN ULASAN PRODUK PEMBELIAN BERAS DI MARKETPLACE SHOPEE Dedy Sugiarto; Syandra Sari; Anung Barlianto Ariwibowo; Fitria Nabilah Putri; Dimmas Mulya; Tasya Aulia; Arviandri Naufal Zaki
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 1 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

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

Abstract

This study aims to compare the performance of product purchase sentiment classification in market place shopee using four classification algorithms, namely support vector machine (SVM), naïve bayes (NB), logistic regression (LR),  k-nearest neighbor (KNN) and associated with the feature extraction model used, namely term frequency - inverse document. frequency (TF-IDF) and bag of word (BOW).   Data collection was carried out by extracting rice product review data through the Shopee website using a web scraping technique which was then saved in the form of a file with CSV format. The number of product reviews obtained is 3531 reviews and after pre-processing through the elimination of duplicate reviews, there are 464 reviews with details 16.17% having a negative label (rating 1 or 2), 15.52% having a neutral label (rating 3), and 68.32% have a positive label (rating 4 or 5). The composition of the rankings shows that the data is not balanced. The experimental results show that the combination of LR with TF-IDF shows the best performance with an accuracy of 80%.
Perolehan Informasi Kembali (Information Retrieval/IR) Menggunakan Topic Modelling untuk Dataset Tempo Wilda Anggriani; Syandra Sari; Anung B. Ariwibowo; Dedy Sugiarto
Intelmatics Vol. 1 No. 2 (2021): Juli - Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v1i2.5030

Abstract

In the era of technology as it is today, many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information., many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information.Search engines really help humans to get information. Usually the search engine is one example of information retrieval (Information Retrieval / IR). Documents that produced by search engines are relevant documents based on user requests.In this study, the author implemented the IR process to find relevant documents based on existing queries. The results will be compared with relevant documents from previous research using the same dataset, namely the Tempo dataset from 2000 to 2002. This can find out how far the performance of the method used in this research is based on previous research. The method used in this research is the doc2vec method.From the results obtained using the doc2vec model, the smaller the epoch on the doc2vec model, the smaller the results of the average percentage similarity between the relevant documents produced by the doc2vec model and the relevant documents beforehand. While the results of the percentage similarity average of the doc2vec model are based on the vector size which is after the vector size 30 the result is above 35%. Epoch which produces the highest percentage average is epoch 25 from epoch 25, 50, 75, and 100. Vector size that produces the highest average percentage similarity is vector size 40 from vector size 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100. The highest results of the highest percentage similarity are generated by the doc2vec model that uses epoch 25 and vector size 40 is 41,930. In the era of technology as it is today, many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information., many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information.Search engines really help humans to get information. Usually the search engine is one example of information retrieval (Information Retrieval / IR). Documents that produced by search engines are relevant documents based on user requests.In this study, the author implemented the IR process to find relevant documents based on existing queries. The results will be compared with relevant documents from previous research using the same dataset, namely the Tempo dataset from 2000 to 2002. This can find out how far the performance of the method used in this research is based on previous research. The method used in this research is the doc2vec method.From the results obtained using the doc2vec model, the smaller the epoch on the doc2vec model, the smaller the results of the average percentage similarity between the relevant documents produced by the doc2vec model and the relevant documents beforehand. While the results of the percentage similarity average of the doc2vec model are based on the vector size which is after the vector size 30 the result is above 35%. Epoch which produces the highest percentage average is epoch 25 from epoch 25, 50, 75, and 100. Vector size that produces the highest average percentage similarity is vector size 40 from vector size 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100. The highest results of the highest percentage similarity are generated by the doc2vec model that uses epoch 25 and vector size 40 is 41,930.
Ekstraksi Informasi Menggunakan Named Entity Recognition dan Pembuatan Association Rule Pada Dokumen Direktori Putusan Mahkamah Agung Republik Indonesia Muhammad Rizky Fadila Afgan; Syandra Sari; Anung B. Ariwibowo; Dedy Sugiarto
Intelmatics Vol. 2 No. 1 (2022): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v2i1.5031

Abstract

Land is fundamental to the needs of human life. Humans carry out activities on the ground, so that they are obstructed from getting all human activities both directly and indirectly carried out on the ground. Land is a natural resource that is given by God Almighty to the Indonesian people as national wealth and is a means of meeting all life activities that are important for human life. In this case everyone must need land. Land is often used as a case by disputes, because of the limited area of landInvolved a lot of land The author will extract information in the Directory file Decision Mahkmah Agung is done to produce a named entity taken from the file. PDF extracted. In this study, the author uses the introduction of an entity named (NER Entity Recognition or NER). NER is used to retrieve named entities. After that the author uses the Association Rule to inform data in the form of graphs for analysis Land is fundamental to the needs of human life. Humans carry out activities on the ground, so that they are obstructed from getting all human activities both directly and indirectly carried out on the ground. Land is a natural resource that is given by God Almighty to the Indonesian people as national wealth and is a means of meeting all life activities that are important for human life. In this case everyone must need land. Land is often used as a case by disputes, because of the limited area of land                                Involved a lot of land The author will extract information in the Directory file Decision Mahkmah Agung is done to produce a named entity taken from the file. PDF extracted. In this study, the author uses the introduction of an entity named (NER Entity Recognition or NER). NER is used to retrieve named entities. After that the author uses the Association Rule to inform data in the form of graphs for analysis
Recommendation System for Mental Health Article on Circle Application Gading Sectio Aryoseto; Is Mardianto; Anung B. Ariwibowo
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.16343

Abstract

Healthy mental health is a condition when minds are in a state of peace and calm and not disturbed, thus enabling us to enjoy our daily lives with respect for others. In Indonesia, there are quite a number of sufferers of mental health disorders, approximately 19 million people over the age of 15 experience mental and emotional disorders, both at mild to severe levels. These data show that the Indonesian state has not been able to properly address mental health problems and that the existence of a pandemic tends to increase sufferers of mental health disorders, which if left unchecked will have a negative impact. Based on this problem, the Circle application, that focuses on mental health using Android technology that supports self-help with several services, one of which is an article service. The article service in the Circle application requires a recommendation system that can recommend articles according to the mental health conditions experienced by users so that the articles are able to alleviate the mental health problems currently experienced by users. Topic Modeling is an approach to analyze a collection of text documents and group them into topics. Topic Modeling has several methods that can be applied in making topics, one of which is BERTopic. It is a technique that leverages Transformer and c-TF-IDF to create dense clusters, preserving keywords in topic descriptions while making topics easier to interpret. There are 3 important components of the BERTopic algorithm namely Document Embedding, Document Clustering, Topic Representation. This study uses Topic Modeling with the BERTopic method as the baseline for the mental health article recommendation system in the circle application.
Pelatihan Analisis Kinerja Konten Media Sosial Shofi Cookies dengan Data Analytics Syandra Sari; Dedy Sugiarto; Ratna Shofiati; Anung B Ariwibowo; Shabrina Teruri; Muhamad Ichsan Gunawan; Faiz Kumara; M Arya Octavianus
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 4 (2025): November: NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v5i4.6908

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the economy but still face challenges in utilizing digital technology for marketing. Shofi Cookies, as the partner of this program, has been using TikTok and a website, yet their utilization remains suboptimal. This community service activity aimed to enhance the partner’s digital capacity through social media analysis, website audits, and digital branding training. The methods included evaluating the TikTok account, auditing the website’s Search Engine Optimization (SEO), and providing training on the use of WordPress Content Management System (CMS) along with branding strategies. The results showed that the TikTok account was still personal, limiting analytic data, while the website audit produced a C- SEO score with issues in mobile access speed. The training, attended by the owner and operator, received positive responses with high satisfaction, although participants’ understanding still needs improvement. The implication of this activity highlights the importance of follow-up actions such as switching to a TikTok business account, increasing content upload consistency, and optimizing website SEO. With these efforts, Shofi Cookies is expected to strengthen competitiveness, expand market reach, and increase sales in the digital era.
Co-Authors Ahmad Zuhdi Anak Agung Istri Sri Wiadnyani Arviandri Naufal Zaki Binti Solihah Brahmantyo Anggoro Dedy Sugiarto Dimmas Mulya Faiz Kumara Fitria Nabilah Putri Gading Sectio Aryoseto Indah Pradhipta Is Mardianto Jaquline Glenadys Siregar M Arya Octavianus Muhamad Ichsan Gunawan Muhammad Rizky Fadila Afgan Ralph Vincent Sapulette Ratna Shofiati Rianti Dewi Sulamet-Ariobimo Rina Fitriana Shabrina Teruri Syandra Sari Syandra Sari Tasya Aulia Teddy Siswanto Wawan Kurniawan Wilda Anggriani