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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Proceeding of the Electrical Engineering Computer Science and Informatics E-Dimas: Jurnal Pengabdian kepada Masyarakat Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research SISFOTENIKA JURNAL INTEGRASI IT JOURNAL RESEARCH AND DEVELOPMENT JURNAL REKAYASA TEKNOLOGI INFORMASI JURNAL PENGABDI ILKOM Jurnal Ilmiah METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi MIND (Multimedia Artificial Intelligent Networking Database) Journal JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) EXPLORE METIK JURNAL JISKa (Jurnal Informatika Sunan Kalijaga) Sains, Aplikasi, Komputasi dan Teknologi Informasi JUKI : Jurnal Komputer dan Informatika Infotek : Jurnal Informatika dan Teknologi Innovation in Research of Informatics (INNOVATICS) Jurnal Kesehatan Saintika Meditory JUSTIN (Jurnal Sistem dan Teknologi Informasi) Transformasi EXPLORE Journal of Technology Research in Information System and Engineering Data Sciences Indonesia (DSI) Adopsi Teknologi dan Sistem Informasi Jurnal Pengabdian Pada Masyarakat Journal of Computer Science and Information Technology Inovasi Teknologi Masyarakat
Wati, Masna
Program Studi Informatika, Fakultas Teknik, Universitas Mulawarman
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Penentuan Kelayakan Masyarakat Miskin Penerima Bantuan Menggunakan Metode Naïve Bayes (Studi Kasus: Kabupaten Penajam Paser Utara) Nur Madia; Anindita Septiarini; Heliza Rahmania Hatta; Hamdani Hamdani; Masna Wati
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 1 (2023): Januari 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.1.36-49

Abstract

Contents Poverty is the inability to meet the necessities of life, such as food, clothing, and shelter. The poor have an average monthly per capita expenditure below the poverty line. The case of poverty in Indonesia is still unresolved; the Government continues to try to give the best to the entire community so that the problem of poverty can at least continue to decrease. One form of government concern for the poor is the assistance program provided to the poor. This study will classify based on data from the North Penajam Paser (PPU) community obtained from the results of the National Socio-Economic Survey (Susenas) to know how the Naïve Bayes method is in determining the eligibility of the poor recipients of assistance. Based on the research that has been carried out, a system for determining the poor recipients of assistance is produced, where the test results get the highest accuracy in the third scenario, namely 60% or 328 training data and 40% or 218 test data, where the accuracy obtained is 77.98%.
Pendidikan Seksual Anak Usia Dini melalui Media Audio Visual dan Body Mapping untuk Siswa TK Bina Ana Prasa III Zahra Ayu Qalbina; Masna Wati
Jurnal Pengabdian Pada Masyarakat Vol 8 No 1 (2023): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/jppm.v8i1.211

Abstract

Berdasarkan data Simfoni PPA Kalimantan Timur, pada tahun 2021 terdapat 450 kasus dan 513 korban, dengan jumlah insiden kekerasan terbanyak di Kota Samarinda dimana 66% adalah korban anak-anak. Kekerasan terhadap anak tertinggi adalah kekerasan seksual, yaitu 191 kasus. Pendidikan seksual diharapkan dapat disampaikan sejak dini agar anak mendapatkan informasi yang benar dan terhindar dari kekerasan seksual. Kegiatan pendidikan seksual anak usia dini ini bertujuan untuk memberi pemahaman dan kesadaran untuk melindungi diri dari kejahatan seksual kepada siswa TK Bina Ana Prasa III Kota Samarinda. Metode yang dilaksanakan berupa penyuluhan dan simulasi Iptkes menggunakan media audiovisual dan pendampingan body mapping. Hasil kegiatan menunjukkan bahwa media audio-visual dan body mapping yang merupakan metode simulasi Ipteks yang sangat efektif digunakan dalam penyampaian informasi dan edukasi bagi anak-anak. Berdasarkan hasil evaluasi, tingkat pemahaman anak-anak terhadap materi edukasi mencapai 92,5%. Dari kegiatan ini siswa mengenal bagian tubuh yang boleh disentuh dan tidak boleh disentuh oleh orang asing sebagai upaya untuk melindungi diri. According to data from the East Kalimantan PPA Symphony, in 2021, there were 450 cases and 513 victims, with the highest number of violent incidents in Samarinda City, where 66% were child victims. The highest violence against children was sexual violence, namely 191 cases. It is hoped that sexual education can be delivered early so that children get the correct information and avoid sexual violence. This early childhood sexual education activity aims to provide understanding and awareness to protect themselves from sexual crimes Bina Ana Prasa III Kindergarten students, Samarinda City. The method in this activity is counselling with science and technology simulation using audio-visual media and body mapping assistance. The activity results show that audio-visual media and body mapping effectively convey information and educate children. Based on the evaluation results, the children's understanding of educational materials reached 92,5%. From this activity, students learn which body parts are permissible to touch and which touch is not allowed by strangers to protect themselves.
Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Indonesian Crude Oil Price Masna Wati; Haviluddin Haviluddin; Akhmad Masyudi; Anindita Septiarini; Heliza Rahmania Hatta
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.v9i3.22286

Abstract

Crude oil is the main commodity of the global economy because oil is used as an ingredient for many industries globally and is the price base used in the state budget. Indonesian Crude Price (ICP) fluctuates following developments in world crude oil prices. A significant increase in crude oil prices will certainly disrupt the economy. Thus, the movement or fluctuation of ICP is essential for business players in the energy market, especially domestically. Therefore, crude oil price forecasting is needed to assist business people in making decisions related to the energy market. This study aims to find a suitable forecasting model for Indonesian crude oil prices using the Autoregressive Integrated Moving Average (ARIMA) method. The forecasting process used ICP time-series data per month for 50 types of crude oil within five years or 63 months. Based on the experimental results, it was found that the most fit ARIMA models were (0,1,1), (1,1,0), (0,1,0), and (1,2,1). The test results for April to September 2020 have a good and proper interpretation, except the type of BRC oil indicates inaccurate forecasts. The ARIMA error rate is very dependent on the value of the data before it is predicted and external factors, the more unstable the data value every month, the higher the error rate.
Penerapan Metode Fuzzy Sugeno dalam Memprediksi Permintaan Darah Novianti Puspitasari; Anindita Septiarini; Olivia Octavia; Masna Wati; Heliza Rahmania Hatta
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 10, No 4 (2022)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v10i4.52152

Abstract

Transfusi darah dibutuhkan ketika seorang manusia kehilangan banyak darah. Darah tersebut disediakan oleh pusat penyimpanan darah yang bertugas memperkirakan ketersediaan stok darah agar jumlah darah selalu tercukupi. Informasi terkait stok persediaan darah sangat diperlukan karena apabila stok persediaan darah tidak mencukupi maka akan berdampak pada meningkatnya kematian, sementara stok darah yang berlebihan harus dihindari karena darah memiliki masa kadaluarsa (masa simpan darah) selama 35 hari sejak darah tersebut didonorkan. Oleh karena itu, demi meminimalisir kerugian yang terjadi, maka perlu dilakukan sebuah penelitian tentang memprediksi jumlah permintaan darah yang seharusnya diterima oleh PMI dimasa yang akan datang. Penelitian ini menggunakan metode fuzzy Sugeno untuk memperkirakan jumlah permintaan darah dimasa yang akan datang. Metode ini memiliki toleransi terhadap data-data yang tidak tepat yaitu data yang belum ditentukan nilainya sehingga dapat digunakan untuk melakukan sebuah peramalan. Penelitian menggunakan data dari empat jenis golongan darah yaitu A, B, O dan AB dari bulan Januari 2017 hingga bulan Oktober 2021. Hasil pengujian validitas yang telah dilakukan menggunakan Mean Absolute Percentage Error (MAPE) dan Root Mean Square Error (RMSE) didapatkan nilai sebesar 27.55% dan 27.61, sehingga metode ini dapat dikatakan layak dan akurat dalam memprediksi jumlah permintaan darah.
Klasifikasi Penderita ISPA Menggunakan Metode Naive Bayes Classifier Syarah, May Siti; Wati, Masna; Puspitasari, Novianti
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 4, No 1 (2022): Maret 2022
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v4i1.4427

Abstract

Information related to the classification of ARI disease suffered by the community in a public health is essential. This is because the public health is one of the community health centers that is a reference for treatment for the community. Public health must identify the right type of ARI disease so that treatment for ARI sufferers can be given optimally. This study classified the data of patients with ARI in a public health based on the determining factors, namely the disease suffered, age, and period of stay. Classification is carried out using the Naive Bayes Classifier method with the Confusion Matrix testing method. The results of applying the Naive Bayes Classifier method to patient data resulted in three types of ARI, namely mild, moderate and severe. The highest number of ARI patients is severe ARI. The results of the Confusion Matrix test that have been carried out prove that this method has an accuracy of 93.33% so it is suitable for use to classify ARI diseases.
Sistem Pendukung Keputusan untuk Evaluasi Tingkat Kesejahteraan Masyarakat Menggunakan Metode PROMETHEE Masna Wati; Simbolon, R.H. Kimebmen; Widians, Joan Angelina; Novianti Puspitasari
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 12 No. 2 (2021): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v12i2.8115

Abstract

Salah satu faktor tercapainya kesejahteraan masyarakat yaitu rendahnya tingkat penduduk miskin. Pemerintah berperan penting dalam mensejahterakan masyarakat dan pengentasan kemiskinan. Seleksi tingkat kesejahteraan masyarakat adalah salah satu masalah yang memerlukan keputusan yang tepat agar bantuan disalurkan kepada masyarakat yang membutuhkan tepat sesuai target. Oleh karena itu, dibangun sistem decision support menggunakan metode Promethee. Data penelitian berupa 220 data sampel keluarga dan melibatkan 15 kriteria dalam mengevaluasi tingkat kesejahteraan masyarakat bersumber pada Survei Sosial Ekonomi Nasional oleh Badan Pusat Statistik Provinsi Kalimantan Timur. Sistem yang telah dibangun memberikan output berupa urutan prioritas kesejahteraan masyarakat yang dapat dijadikan pertimbangan bagi pemerintah atau pihak terkait dalam penyaluran bantuan agar tepat sasaran Abstract One of the factors in achieving community welfare is the low poverty level. The government has an essential duty in the welfare of society and alleviating poverty. The evaluation of the welfare level is one of the problems that require the right decision so that the social assistance provided to people in need can be right on target. The study aims to deploy a system that utilizes the Promethee method for decision-makers. There is 220 family as the sample data evaluated involves 15 criteria for assessing the community welfare level sourced from the National Socio-Economic Survey by the Statistics of East Kalimantan Province. The decision support system built was able to result in priority order of community welfare level so that it could be a consideration or reference to the government or related agencies in distributing aid to make it right on target.
Dipterocarpaceae trunk texture classification using two-stage convolutional neural network-based transfer learning model Wati, Masna; Puspitasari, Novianti; Hairah, Ummul; Widians, Joan Angelina; Tjikoa, Ade Fiqri
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6874-6882

Abstract

The importance of plant identification has been recognized by academia and industry. There have been several attempts to utilize leaves and flowers for identification. However, the trunk can also be helpful, especially for tall trees. In Borneo, the Dipterocarpaceae family are the main constituents of the tropical rainforest ecosystem. This research focuses on the classification of the dipterocarp family, which can reach a height of between 70 and 85 m. Leveraging convolutional neural network (CNN) models, this research proposes a two-stage transfer learning strategy. In the first stage, the pre-trained CNN models are refined by only modifying the classification layer while keeping the feature layer frozen. The second stage involves selecting and freezing several convolutional layers to adapt the model to classify dipterocarp stems. The dataset consists of 857 images of different dipterocarp species. Experiments show that the VGG16 model with a two-stage transfer learning strategy achieves a high accuracy of 98.246%. This study aims to accurately identify species, benefiting conservation and ecological studies by enabling fast and reliable tree species classification based on stem texture images.
Recommendation method for selecting the rice seeds based on group decision support system Hamdani, Hamdani; Wati, Masna; Suprihanto, Didit; Salsabila, Nur Maya; Septiarini, Anindita; Nurmadewi, Dita; Mawardi, Viny Christanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2656-2665

Abstract

In this paper, we provide group recommendations based on each decision makers (DMs) in choosing the best type of rice for replanting. This group decision support system (GDSS) aims to guide stakeholders who have a role in selecting rice types. In this method, we propose using technique for order preference by similarity to ideal solution (TOPSIS) to rank each DM, Borda to rank in groups, and then test it using Spearman's rank correlation to measure the relationship between system results and the method applied. The results of this study show that DM1 ranks highest in selecting Gelagai rice seeds with a preference of 0.7786. Then DM2 ranked highest with Ekor Payau rice seeds in preference 0.6529. Meanwhile, DM3 ranked highest in Gelagai rice seeds with a selection of 0.7728. The final group voting system uses Borda, where Gelagai rice seeds occupy the highest rank with the most accumulated votes from each DMs. The best option or the highest rating based on the assessment of the three DMs, DM1 as a farmer is the first rank A10 Gelagai with a score of Borda 26 in the decision group selection of superior rice seeds.
Penerapan Tool Google Workspace untuk Meningkatkan Efektivitas Belajar Mengajar di SMAN 9 Samarinda Wati, Masna; Hairah, Ummul; Manik, Filipus Adriel; Hidayat, Irfan Arman; Arabi, Muhammad Amin Quthbi; Alqarani, Hudzaifah; Rasid, Khairul; Wijaya, M Rangga Yaqub
Inovasi Teknologi Masyarakat (INTEKMAS) Vol. 1 No. 1 (2023): June 2023
Publisher : Wadah Inovasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53622/intekmas.v1i1.204

Abstract

Digitalisasi di bidang pendidikan perlu dilakukan di era revolusi industri 4.0 ini sehingga perkembangan dunia pendidikan sejalan dengan kemajuan teknologi. Keberadaan teknologi akan menjadi tidak termanfaatkan jika tidak dibarengi dengan pengajar dan pembelajar yang melek teknologi. Kesuksesan integrasi teknologi pendidikan dalam kegiatan belajar dan mengajar bersifat kompleks dan dipengaruhi oleh berbagai faktor yaitu keterbukaan terhadap teknologi, sikap guru, pengetahuan dan keterampilan juga waktu dan beban kerja guru. Google Workspace sebagai salah satu tools yang dihadirkan Google untuk mempermudah dalam hal proses produktivitas dan juga memperluas media belajar. Aplikasi tersebut dapat bermanfaat bagi pendidikan untuk peningkatan efektivitas proses belajar mengajar, keterampilan guru semakin berkualitas serta budaya sekolah yang terbuka dengan pemanfaatan teknologi. Kemampuan guru dalam menggunakan aplikasi ini perlu ditingkatkan lagi agar aplikasi ini dapat dimanfaatkan secara maksimal oleh para guru dalam proses belajar mengajar. Pelatihan penggunaaan Google Workspace kepada guru-guru belum pernah diadakan di SMAN 9 Samarinda. Oleh karena itu kegiatan Pengabdian Kepada Masyarakat (PKM) sangat tepat dilaksanakan di sekolah ini. Kegiatan ini merupakan salah satu solusi untuk menjalankan metode pengajaran yang fleksibel dan mudah dipelajari serta interaktif. Melaui kegiatan ini diharapkan dapat meningkatkan kualitas pembelajaran dan pendidikan serta guru mampu meningkatkan kemampuan diri sebagai tenaga pengajar yang profesional dan paham akan pentingnya Teknologi Informasi dan Komuniasi (TIK) dalam pembelajaran.
Classification for Determining the Level of Drugs Dependence Using the Naïve Bayes Classifier Puspitasari, Novianti; Ajay, Muhammad; Wati, Masna; Septiarini, Anindita
IT Journal Research and Development Vol. 9 No. 1 (2024)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2024.16319

Abstract

Drug users or abusers are people who use narcotics or psychotropic drugs without supervision or medical indication from a doctor. Before undergoing rehabilitation, drug users must first undergo an examination to determine their level of drug dependence so that they can receive medical treatment according to their level of drug dependence. Determining the level of drug dependence requires a technique that can provide labels or categories of data for drug users based on the user's condition or influential criteria. This study applies the Naïve Bayes Classifier method to a system to determine the level of drug dependence. This study uses medical record data from 220 drug users. The user's medical record data is processed using data mining stages consisting of data selection, data cleaning, data transformation, and division of training and test data to produce 120 training data and 100 test data. The results of the Naive Bayes Classifier method calculation resulted in 29 users having a trial level of dependence (mild), 42 identified as having a regular level of dependence (moderate), and 29 others as users with a severe level of dependence. The confusion matrix testing was very accurate, namely, 94% accuracy, 95% precision value, and 92% recall. Meanwhile, the system that has been built can run very well. Based on the results of the research that has been conducted, this research can contribute to determining the level of dependence of drug addicts objectively so that related parties can provide rehabilitation or appropriate treatment to drug addicts.
Co-Authors -, Haviluddin Abdul Hadi Ade Chrisvitandy Adelowys Sinaga AHMAD ANSYORI Ahmad Nur Fauzan Aiman, Ahmad Zuhair Nur Ajay, Muhammad Akhmad Masyudi Alameka, Faza Alfajriani Alfajriani Ali Sholihin Alifah, Nur Juzieatul Alqarani, Hudzaifah Ambon, Matelda Yunanta Andi Maulana Andi Maulana, Andi Anggari, Ricky Anindita Septiarini, Anindita Anton Prafanto Arabi, Muhammad Amin Quthbi Asmita, Rizka Awang Harsa Kridalaksana Awang Zheri Rhesvianur Ayu Rusnawati A’yuni, Qurrata Bahtiar , Andi Alfian Bambang Cahyono Bambang Cahyono Bandhaso, Victor Bramantyo, Dimas Ari Brins Leonard Pailan Budiman, Edy Burhandenny, Aji Ery Cahyani, Oktari Indi Davina Putri Ananta Delvina Dwiani Samjar Didit Suprihanto, Didit Dwi Kinasih Widiyati Engla Despahari Eny Maria Ervan, Muhamad Gusti Keyandi Evi Wildana Fadli Suandi Farisha Rizky Amalia Fauzan, Ammar Nabil Faza Alameka Faza Alameka Fenny Indar Ferry Miechel Lubis Firdaus, Ardhifa Firdaus, Muhammad Firdaus, Muhammad Bambang Gading, Fazri Rahmad Nor Geni, Siti Putri Lenggo Hairah, Ummul Hairah, Ummul Hamdani Hamdani Hamdani Hamdani Hariati Hariati Hatta, Heliza Rahmania Haviluddin , Haviluddin Haviluddin Haviluddin Heliza Rahmania Hatta, Heliza Rahmania Hendi Hidayat, Irfan Arman Hijratul Aini Hutagalung, Wilson Boyaron Hutapea, Vedra Dian Sierrafina Ifandi, Muhammad Iin Nurkarima Islamiyah Islamiyah Joan Angelina Widians, Joan Angelina Julius Rinaldi Simanungkalit Kesuma, Muhammad Afrizal Lili, Juniver Veronika Lubis, Ferry Miechel Manik, Filipus Adriel Masyudi, Akhmad Medi Taruk Mega Yoalifa Merry, Felisitas Mewengkang, Alfrina Mochammad Taufiq As'arie Muhammad Abdillah Muhammad Bambang Firdaus Muhammad Firdaus Muhammad Ifandi Muhammad Rafif Hanif Mu’nisah Assisi Nanda Arianto Nggotu, Antonieta Aryuka Paskalia Novianti Puspitasari Nugraha, Cellia Auzia Nupa, Joy Disanto Nur Madia Nurkarima, Iin Nurmadewi, Dita Nuzulan, Alan Olivia Octavia Pakpahan, Herman Santoso Pebianoor, Pebianoor Prano Pebri Ansari Pratama, Arief Ardi Puspitasari, Novianti Putri, Septi Aulia Rasid, Khairul Rayner Alfred Razan, Muhammad Arya Fayyadh Reviansa Fakhruddin Aththar Rizqi Saputra Rosmasari, Rosmasari Sadewa, Bintang Putra Safitri, Hersa Salsabila, Nur Maya Saragih, Muhammad Nabil Sari, Lili Kurnia Sembiring, Wahyu Harry Saputra Septiani, Afra Amelia Setiawan, Maulana Agus Setyadi, Hario Jati Shiva Mutia Maffirotin Simanungkalit, Julius Rinaldi Simbolon, R.H. Kimebmen Sitompul, Tua Delima soleha, leha Syahputra, Andra Syarah, May Siti Taruk, Medi Tejawati, Andi Tjikoa, Ade Fiqri Vicky Pranandika Wijaksana Vina Zahrotun Kamila Viny Christanti M Wandi, Faizul Anwar Widians, Joan Angelina Wijaya, M Rangga Yaqub Wiji Astuti Yudi Kurniawan Yunus, Marlina Yusran, Sartiah Zahra Ayu Qalbina Zainal Arifin