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Journal : Building of Informatics, Technology and Science

Perbandingan Algoritma Support Vector Machine dan Naïve Bayes dalam Menganalisis Sentimen Pinjaman Online di Twitter Ikhsani, Yulia; Permana, Inggih; Salisah, Pebi Nur; Mustakim, Mustakim; Rozanda, Nesdi Evrilyan
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6106

Abstract

Unemployment is one of the poverty factors in society, the large economic needs make it difficult for people to meet their daily needs, thus triggering high demand for loans in society. With the advancement of technology, online loans are now available to help people meet their economic needs. However, over time, many irresponsible parties have taken advantage of this. Marked by the emergence of many illegal online loans, which have triggered negative impacts such as the spread of customer personal data, terror on social media, to debt collection using debt collectors. So that it raises a lot of sentiment in society regarding online loans. For this reason, it is necessary to conduct a sentiment analysis with the aim of public response to online loans, which can be positive, negative or neutral responses. There are two datasets used, namely legal online loans and illegal online loans. This study uses two algorithms, namely SVM and Naive Bayes, the two algorithms will be compared to find out which algorithm is better at analyzing online loan sentiment. In addition, in its use, the two algorithms will also use the SMOTE technique to stabilize the data. The results obtained on legal loan data classification using SVM are quite better than Naive Bayes, with an accuracy rate of 69% with sentiment that often appears is positive sentiment. For illegal loan data, classification using the Naive Bayes algorithm is better than SVM with an accuracy of 75% and sentiment that often appears is neutral sentiment. Based on these results, it can be concluded that in analyzing sentiment using legal loan data, the best algorithm is the SVM algorithm, and for illegal loan data, the best algorithm is the Naive Bayes algorithm.
Analisis Sentimen Traveloka Berdasarkan Ulasan Google Play Store Menggunakan Algoritma Support Vector Machine dan Random Forest Rohimah, Siti; Afdal, M; Mustakim, Mustakim; Novita, Rice
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6300

Abstract

The internet has become a key element in supporting technological and information advances in various sectors of human activity. In the trade and tourism sector, the Traveloka application is the favorite choice of Indonesian people. Reviews or reviews from users play an important role for the Company to understand the level of customer satisfaction. However, currently there are several users who give high ratings but contain negative reviews. Based on these problems, this research aims to understand more deeply user opinions, so that they can be used to improve services and features as well as test and compare the accuracy of the two algorithms in classifying user sentiment. In this research, the Support Vector Machine and Random Forest classification methods were used. The research results show that Random Forest has superior and stable performance compared to SVM, with higher average accuracy for most features, such as Traveloka (71% & 67%) and Airplanes (75% & 74%). Evaluation with k-fold cross validation supports these results, with higher average Random Forest accuracy on features such as Traveloka (70% & 66%) and Airplanes (75% & 74%).
Implementasi Metode Holt-Winters dan FP-Growth dalam Melakukan Peramalan Stok Barang Pada Swalayan Berdasarkan Pola Asosiasi Loka, Septi Kenia Pita; Afdal, M; Novita, Rice; Mustakim, Mustakim
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6305

Abstract

At present, competition in the business world is extremely fierce, particularly in the convenience store sector. The development of retail trade is progressing rapidly, accompanied by the emergence of many small markets and online shops. This situation encourages store owners to make wiser decisions, such as managing stock replenishment. If overlooked, this matter way hinder employees from locating the necessary items, thereby increasing the potential risk of goods expiring or being damage before they are sold. Therefore, store owners need to understand consumer behavior and shopping habits to assist iin stock management. Based on this issue, the research aims to analyze consumer purchasing patterns and optimize inventory stock. The result of this experiment identified two best rules, namely biscuit and consumption/food, with a confidence of 53,61%, a support of 15,57%, and a lift ratio of 1,116 the error measurement MAPE shows a value of 6,79 using alpha, beta and gamma values of 0,1. The total predicted stock in 52,086 with an actual value of 72,275, which is close to actual value of data prior to the significant observed in the last three months.
Density-Based Spatial Clustering, K-Means and Frequent Pattern Growth for Clustering and Association of Malay Cultural Text Data in Indonesia Mustakim, Mustakim; Salisah, Febi Nur
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7512

Abstract

Several studies state the need to develop information technology to disseminate information related to culture in Indonesia. There are many similar studies but they still have weaknesses, one of which is that they do not use machine learning and intelligent computing. This research answers the challenges of previous researchers, namely developing machine learning-based learning applications using the Density-Based Spatial Clustering of Application Noise (DBSCAN) and Frequent Pattern Growth (FP-Growth) algorithms. The results of the modeling of the two algorithms are deemed to still require improvement in the future, as it is proven that DBSCAN does not yet have optimal validity. So in this research, one of the comparison algorithms is used, namely K-Means Clustering, with a better evaluation than DBSCAN. The modeling results were implemented into mobile programming as a cultural learning application in Indonesia, especially Riau Malay Culture, the black box testing results had an accuracy of 100% and the User Acceptance Test (UAT) was 86%. Thus, it is concluded that this application can be used effectively and efficiently for general users.
Pengelompokkan Perguruan Tinggi di Indonesia Menggunakan Algoritma BIRCH Husna, Nur Alfa; Mustakim, Mustakim; Afdal, M; Rahmawita, Medyantiwi
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7234

Abstract

Accreditation is currently the main focus for all universities. Each institution strives to get superior accreditation. The evaluation and assessment process carried out by BAN-PT is based on data reported by universities to PDDikti. This research aims to assist universities in achieving superior accreditation, by providing recommendations regarding the most influential attributes and clustering to find patterns or data structures from PDDikti. This research uses two feature selection methods AHP and Chi-Square are used separately to identify the most influential attributes. The results of each method were used as input features for the clustering process using the BIRCH algorithm. The purpose of this approach is to evaluate the effect of feature selection from both methods on the quality of clustering results. The evaluation is done using the Davies-Bouldin Index (DBI) metric. The results showed that the Lecturer attribute has the highest eigenvalue in AHP which is 0.379, indicating its significant role in accreditation assessment. Meanwhile, the Year of Establishment Decree attribute has the highest Chi-Square value of 290.625 which indicates a strong correlation with accreditation results. In addition, based on the cluster DBI value, it shows that AHP is superior to chi-square, so AHP is considered more effective in this context. With the best Davies Bouldin Index (DBI) value of 0.73603 in cluster 7 with a threshold of 0.05 and a branching factor of 50.
Co-Authors . Ishomuddin . Ria Wulandari A'yunin, Elia Nur A.A. Ketut Agung Cahyawan W Abd. Rasyid Syamsuri Abdi Negara Abdillah, Fardan Abdul Fattah Abdul Fattah Abdul Hadid abdullah, akhyar abdullah, akhyar abdullah, akhyar abdullah, akhyar Abidah, Dinah Abror, Naufal Achmad Abubakar Adan, Ingrid Ayu Lestari Ade Rahmat, Ade Adelina Hasyim Adhiva, Jeni Adnan Adnan Adrian Adrian Adrianton A. Aedah, Nur Afandi, Rival Agustien Lilawati Agustina Ahirudin, Idul Ahmad Muzaki Ahmad, Hariadi Aini, Delvi Nur Akmalia Putri, Fina Aksa, Moh. Al Ayubi, Moch T A Alajai, Rafly Ali Akbar Ali Rosidi Ali, Akbar Aliffiani, Siti Almin, Muh. Robil Amin, Novi Nurul Andi Nikhlani Andriansyah Andriansyah Andriawan, Ahmad Rizky Anha, Hamna Anhar, Mujahid Anisa Putri anne Hafina, anne Ansar, Zulfitrah Anugrah Puspita Ayu Muhammad Anwar Syahputra, Syofyan ANWAR, DEDY Aprilla, Tyas Aprillia, Tyas Ardjanhar, Asni ARIASIH, ARUM Ariasih, Rr Arum Arif Marsal Ariyanti, Dyah Ariyanti, Fajar Arumsari, Imas Asbar Asbar, Asbar Asnawi , Meinarni Asni Asni Asnita Virlayani, Asnita Asrianto, Rudy Asrianto Asrori, Tamam Asrul Asrul Assiddiq, Muhammad Azwar Astri, Rahmi Aulia Astri, Zul Astuti, Farida Herna Aswar Aswar Atiqa, Nur Audina, Ayu AYU, GLADIS Azlan, Azlan Azzahra, Aura Baharuddin, Andi Farid Baiq Sarlita Kartiani, Baiq Sarlita Kartiani Balkis, Ratu Batubara, Ana Uzla Baya, Nur Berlian Berlian Cahyanti, Novi Putri Cholidi Cholidi Dani Hari Tunggal Prasetiyo Danial, Adang Darmadi, Herry Darmawan Darmawan Dewa Bagus Sanjaya Dewi Mustika Dewi, Bela Purnama Dewi, Luh Yuliani Dewi, Luthfia Dwynne, Zaira Cindya Dwynne ELIHAMI, ELIHAMI Elsye Souvriyanti, Elsye Eriany, Eriany F. Safiesza, Qhairani Frilla Fadhilah, Faiz Fadila Fadila, Fadila Fadloli, Ahmad Siraj Fadly, Imam Faisal, Fahikra Fandi Ahmad Fardan Abdillah M Farhan, Hamim Farida Farida Fathurrahman Fathurrahman Fauziyyah, Aisyah Nur Febi Nur Salisah, Febi Nur FEBRIANTI, THRESYA Fhadli Noer, Fhadli Fidela, Mia Fiqhuddin, Moh Agung Firda Firda Fitri, Li Idi'il Fitriah, Ma’idatul Fitriah Fitryana, Fitryana Ginting, Maulidna Giopani , Luna Aliska Giopani Gultom, Golfrid Gurning, Umairah Rizkya Hadi, M. Samsul Hafan Sutawardana, Jon Hakzah Hamka Ilyas Hamna, Hamna HANDARI, TRI Handayani, Dwi Iryaning Handayani Hanifah, Nida harni harni, harni Hartati Hartati Hartati, Aluh Harwan Harwan Haryono Haryono Hasan Hasan Hasan, Nurhatimah Hasbullah Hasbullah Hasia Marto Hasrudin, La Ode Hasrullah Hasrullah, Hasrullah Hayatudin, Hayatudin Herdiannisa, Zahra Adinda Herwina, Wiwin Herwina, Wiwin Heryanto Susilo Hidayat, Dinul Husainy, Husainy Husna, Nur Alfa I Nengah Suastika I Wayan Kertih I Wayan Lasmawan I Wayan Suastra Ichwanul Mustakim Ida Bagus Putrayasa igam, Mingriani Ikhsani, Yulia Inggih Permana Insiano, Dewi Angraini Ipah Saripah, Ipah Iqrawati, Iqrawati Irfan, Ahmad Zainul Irfan, M Zainul Irmayani Irmayani Irwan Irwan Irwandi, Erno IRWANSYAH Isa, Muhammad Ikhlasul Amalsyah Iskandar Iskandar Isma, Adi Ismail Ismail Ismail Ismaya Ismaya Israyani, Israyani Istianah Surury Iswardani, Kurnia Ita Sarmita Samad, Ita Sarmita Iwan Suyatna Jabri, Umiyati Jamal Bake, Jamal Jamal Rauf Husain Jamsir Jamsir, Jamsir Jasman Jasman Jaswandi, Lalu Jaya, Nur Musfirah Jeki , Jeki Jeki, Jeki jenianti, rina Jeniska, Jeniska Jumiati Jumiati Juraeba, Juraeba justawan, justawan K, Dwi Putri KA Bukhori Kadriani, Kadriani Kambolong, Makmur Karo-Karo, Justaman Arifin Kartika Nugraheni Kartini, Dwi Putri Kartini, Ragita Ayu Kasim, Nursidah Kasmaida kasmaida Kasmar, Kasmar Katimin, Katimin KETUT SUKARMA . Khojin Supriadi, Khojin Khozin, Khozin Kisman Salija, Kisman Kurdi Kurdi Kurnia Dermawan, Aji Kurnia, Dian Kurniawansyah, Fito Cahya Kusumaningati, Walliyana Kusumastuti, Nurry Ayuningtyas Ladamay, Ode Mohamad Man Arfa legito, Legito Lin, Ming Lisa Andriani Listiani Listiani Liwaul, Liwaul Liwaul, Liwaul Loka, Septi Kenia Pita loko, joko Lukman, Mutiara Sakinah M Afdal M Dyah, Mutmainnah Muinuddin M. Afdal M. Afdal, M. Afdal M. Faqih M.Pd Prof. Dr. I Nyoman Sudiana . Maemunah Maemunah malasari, elfi Marhayudi, Putut Marlisman, Desty Pratiwi Martinus Agus S Mas Ahmad Baihaqi Mas'ud, Anis Anshari Mas'ud, Hidayati Masnur Masnur Mastuti, Indah Maulidi, M. Irfan Maulidzam, Khofan Mediaty Meliana Meliana Melkisidik, Melkisidik MH, Nurdin Mirnandaulia, Meutia Misbahuddin Misbahuddin Mizna Sabilla Moh Nurul Qodir Moh. Erkamim Mohamad, Abdul Basir Bin Muh Yusuf Muh. Jabir Muhamad Ajwar Muhammad Basri Muhammad Farhan Muhammad Muhibbi Muhammad Natsir Muhammad Riza Muhammad Taufiq Muhammad, Gazali Mujiburrahman Mujiburrahman Mujiono Mujiono Munir Munir, Munir Munzir, Medyantiwi Rahmawita Murtaqib Murtaqib Musayyachah, Musayyachah musdalifah, sitti Mustakim, Ichwanul Mustari, Sri Hariati Mutmainnah Mutmainnah Nadir, Nadya Adillah Najamuddin Najamuddin, Najamuddin Najamuddin, M. Najwa, Lu'Luin Ni Wayan Widya Astuti Ningsih, Etik Susilowati Novianti Novianti Nugraha, Andhika Ghalyh Nunung Cipta Dainy Nur Eni Katmas Nur Insani Nur Khasanah NUR SELO WASI, NUR SELO Nur Siti Marchamah, Dwi Nur, Ahmad Ali Nur, Indria Nurabdiansyah, Nurabdiansyah Nuralfiliani, Nuralfiliani Nurhaliza, Nana Nurjannah Nurjannah Nurkholis Nurkholis Nursyawal Nacing Pangestu, Prayugo Penti Suryani Pertiwi, Tata Ayunita Pilu, Reski Prameswari, Nadisa Ardikha Prasetya, Agil Bagus Pratiwi, Rina Sekar Purba, Darry Christine Silowaty Purwati, Ninik Endang Purwati, Ninik Endang Putri, Celine Mutiara Putri, Shinta Ayunda Putri, Suci Maharani Qomariyah, Erni Rahayu, Dwi Sri Rahima Rahima Rahmadeyan, Akhas Rahmat Siddiq, Asep Muhammad Rahmawita, Medyantiwi Ramadani, Faradila Ramadhani, Indah Ramdani, Hendi Rasyid, Muhammad Nur A. Rasyid, Muhammad Rusdi Rasyidin Rasyidin Ratmi, Ratmi Raya Sulistyowati Rayani, Dewi Rice Novita Riski, Pratiwi Rivo Nugroho Rizka, M. Arief Rizki Amalia ROFIK JALAL ROSYANAFI Romadhon, Muhammad Rosmiana, Sri Rosyanne Kushargina Rozanda, Nesdi Evrilyan RR. Ella Evrita Hestiandari Rufaidah, Rufaidah Ruris Haristiani Rusman Efendi Rustiyan, Risma S, Galuh Arieliyna Anggraini Sadi Is, Muhamad Safitri, Annisa Apriani sahrun, sahrun sahrun, sahrun Sahrun, Sahrun Sakka Samudin Salamah, Sania Salisah, Pebi Nur Sami'an, Sami'an Samin, Andriyanto Sampurno, Andhika Sari, Shintya Terisna Sartono Sartono, Sartono Sedana, I Made Shadiq, Ja'far Sidek, Muhammad Silalahi, Meriahni Siti Maimunah Siti Rohimah Siti Sarah, Siti Siti Syahidatul Helma Sofiany, Intan Rosenanda Solikhin Solikhin Solly Aryza Sri Wulandari Suarti, Ni Ketut Alit Sugianto, Dedi Suhaimi Suhaimi Suhandini T.J, Yustina Suharjo, Imam Sukman S Sulfanita, Andi Sunarto Sunarto Sunyoto, Andrik Surahman Amin, Surahman Suryodinoto, Muh. Melyo Susanto, Shobri Firman Sutarto Sutarto Sutinah Made, Sutinah Suwitra, I Ketut Suwitra, I Nyoman Syabil, Irfan Syakura, Abd Syamsiar, Syamsiar Syamsu Yusuf Syaputri, Astia Weni Syarfi Aziz Syifaul Janan T, Nurfadila Takdir Takdir, Takdir Tantra, Kadek Mas Tarigan, Enda Rasilta TATI NURHAYATI Taufiq Taufiq Taufiqurrohman , A.H. Asari Tempo, Jesika Irena Gabela Thamrin Gama, Muh Tina Susanti Titin Sriwahyuni Tjahjaningsih, Yustina Suhandini Tri Prihatiningsih Tuhfatul Janan Udiarto, Bagus K Ulfiana , Umaya Usman Made utha, arifin Utha, Arifin utha, arifin wa yanti, wa yanti Wahidah Sulkaeda Aseh Syahda Wahyudi Winarjo, Wahyudi Wathan, Lalu Elgi Hizbul Wawuru, James Van Alex Wibisono, Yudistira Arya Wicaksono6, Febri Widiarni , Adyah Widyaswari, Monica WIWIN YULIANINGSIH Yanti Komala Sari Yazika Rimbawati Yogaswara, Andre Yus Darusman, Yus Yustina Suhandini Tjahjaningsih Yuyun Wahyuni Zahro, Siti Fatimatus Zakariyah, M Fahmi Zarkasih Zarkasih Zarnelly Zarnelly Zharvina, Nihlah Zharvina Zulfikar.Z Zulkifli Rangkuti Zusyah Porja Daryanto