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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Eksakta : Berkala Ilmiah Bidang MIPA JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Empiris Jurnal Pengabdian Pada Masyarakat (EJPPM) Jurnal Pengabdian Pada Masyarakat Eldimas
Budy Santoso
Universitas Ichsan Gorontalo
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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PKM Usaha Kecil Menengah Kerajinan Karawo Di Kelurahan Padebuolo Kecamatan Kota Timur Kota Gorontalo Provinsi Gorontalo Ariawan, Ariawan; Santoso, Budy
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 2 No 2 (2018): JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Forum Dosen Indonesia JATIM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.805 KB) | DOI: 10.36339/je.v2i2.163

Abstract

Karawo's handicrafts as a superior cultural product of the region, is the identity and also the cultural heritagein Gorontalo City. However, the development of the two partners has problems both in terms of production process,management aspects, and marketing as well. The approach used in achieving the objectives of the CommunityPartnership Program (PKM) is a training method by practicing directly with partners, counseling with lectures,discussions and mentoring each partner and evaluation. The results of the Community Partnership ProgramImplementation (PKM) to overcome partner?s problems are: (a) Production aspects such as cooperating with thegovernment and producers/ distributors of raw materials, so that each partner has one distributor to fulfill raw materials,providing training and mentoring of motif designs using the computer program, so that each partner has skilled personnelin designing motifs using a computer program, Providing training and mentoring procedures and slicing techniques, sothat each partner has additional skilled personnel in the slicing process, Providing equipment / machinery assistance insupporting the production process, so that equipment / machinery is available in supporting the production process ineach partner. (b) Management aspects by providing training and mentoring to the management of business management,so that each partner has human resources who have knowledge and skills in business management. (c) Marketing aspectsby providing training and mentoring on promotion and marketing strategies through social media as well as the practiceof making online stores, so that each partner has the knowledge and insight on promotion and marketing strategies andhas one social media based online store that partners are able to manage by themselves
Prediksi Penyakit Jantung Menggunakan Metode-Metode Machine Learning Berbasis Ensemble – Weighted Vote Alhamad, Apriyanto; Azis, Azminuddin I. S.; Santoso, Budy; Taliki, Sunarto
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 5, No 3 (2019): Volume 5 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v5i3.37188

Abstract

Kematian yang disebabkan penyakit jantung masih sangat tinggi, sehingga perlu peningkatan upaya-upaya pencegahannya, misalnya dengan meningkatkan capaian model prediksinya. Penerapan metode-metode machine learning pada dataset publik (Cleveland, Hungary, Switzerland, VA Long Beach, & Statlog) yang umumnya digunakan oleh para peneliti untuk prediksi penyakit jantung, termasuk pengembangan alat bantunya, masih belum menangani missing value, noisy data, unbalanced class, dan bahkan data validation secara efisien. Oleh karena itu, pendekatan imputasi mean/mode diusulkan untuk menangani missing value replacement, Min-Max Normalization untuk menangani smoothing noisy data, K-Fold Cross Validation untuk menangani data validation, dan pendekatan ensemble menggunakan metode Weighted Vote (WV) yang dapat menyatukan kinerja tiap-tiap metode machine learning untuk mengambil keputusan klasifikasi sekaligus untuk mereduksi unbalanced class. Hasil penelitian ini menunjukkan bahwa metode yang diusulkan tersebut memberikan akurasi sebesar 85,21%, sehingga mampu meningkatkan kinerja akurasi metode-metode machine learning, selisih 7,14% dengan Artificial Neural Network, 2,77% dengan Support Vector Machine, 0,34% dengan C4.5, 2,94% dengan Naïve Bayes, dan 3,95% dengan k-Nearest Neighbor.
PENGENDALIAN LAMPU LALU LINTAS CERDAS DI PERSIMPANGAN EMPAT RUAS YANG KOMPLEKS MENGGUNAKAN ALGORITMA ADAPTIVE NEURO FUZZY INFERENCE SYSTEM Santoso, Budy; Azis, Azminuddin I. S.; Bode, Andi
Jurnal Edukasi dan Penelitian Informatika (JEPIN) Vol 6, No 1 (2020): Volume 6 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v6i1.37311

Abstract

Masalah transportasi masih sering dihadapkan pada fenomena kemacetan arus lalu lintas yang berdampak pada kecelakaan lalu lintas, polusi, dan kerugian ekonomi. Salah satu cara untuk meminimalisir fenomena tersebut melalui pengendalian sistem lampu lalu lintas yang baik terhadap arus lalu lintas jangka pendek di persimpangan jalan. Pengendalian lampu lalu lintas secara statis terbukti belum optimal dalam meminimalisir kemacetan arus lalu lintas, salah satu penyebabnya karena kondisi arus lalu lintas yang bervariasi sehingga tidak mudah diprediksi. Fuzzy Inference System (FIS) sering terbukti mampu menunjukkan hasil yang lebih baik daripada pengendalian lampu lalu lintas secara statis. Namun FIS tidak dapat diterapkan pada kondisi arus lalu lintas yang bervariasi atau di persimpangan jalan yang berbeda karena metode tersebut tidak mampu mempelajari kondisi arus lalu lintas secara real time. Agar FIS mampu melakukan pembelajaran, maka pendekatan machine learning dapat diterapkan pada FIS. Salah satu pengembangannya adalah Adaptive Neuro Fuzzy Inference System (ANFIS) yang dapat mengendalikan lampu lalu lintas cerdas secara dinamis dengan hasil yang lebih baik daripada FIS. Namun umumnya ANFIS diuji coba pada persimpangan jalan yang normal. Bagaimana jika di persimpangan yang kompleks? Persimpangan yang memiliki beberapa ruas/jalur utama yang besar (jalur poros), sementara ruas laiinya kecil, bahkan terdapat ruas yang tidak berpotongan, sehingga ada prioritas untuk setiap ruasnya. Hasilnya, penerapan ANFIS (3 GaussMf) untuk pengendalian lampu lalu lintas cerdas/dinamis di persimpangan empat ruas yang kompleks mampu mereduksi Average Waiting Times (AWT) rata-rata sebesar 3,4071E-05 detik dengan 2,7156 RMSE rata-rata, menggunakan variabel Queues Quantity dan Priority Degree. Sedangkan jika menggunakan variabel Arrival Times, Transportation Type, dan Goal Junction, ANFIS (4 TrapMf) mampu mereduksi AWT sebesar 0,0779 detik dengan 19,7646 RMSE.
PENGARUH KEBERADAAN OBJEK MANUSIA TERHADAP STABILITAS RECEIVED SIGNAL STRENGTH INDICATOR (RSSI) PADA BLUETOOTH LOW ENERGY 4.0 (BLE) Budy Santoso
Telematika Vol 13, No 1 (2016): Edisi Januari 2016
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v13i1.1715

Abstract

There are many systems with diverse technologies such as GPS, Wi-Fi, Bluetooth, Zigbee, Ultra Wide Band, Ultrasound, Infrared can be used for location-based services. Of these technologies can be developed several applications for positioning purposes such as monitoring patients in hospitals or elderly people who are undergoing treatment at home. This paper proposes a simple method to estimate the presence of the object / user in a fixed area using parameter Received Signal Strength Indicator (RSSI) on Bluetooth 4.0 Low Energy (BLE). To determine the performance of the RSSI, conducted two experiments in a room scenario dimensions 3 x 2.80 x 2.5 m (present and not present). Two experiments were conducted to test the performance of the RSSI signal. The first experiments with conditions not present showed a good performance. However, in the second experiment (present) with the status of various objects that are in the same room, resulting in poor performance of RSSI, where there is a shift in the RSSI value at the first measurement was obtained average RSSI -73 dBm with a range distance of 2 m, the second measurement obtained an average RSSI value of -85 dBm at a distance of 3 m range. With these results it can be concluded that the human presence in the area of research is very influential on the performance positioning signal strength (RSSI) and the significant impact that the shift distance of up to 1 m.
Pendekatan Machine Learning yang Efisien untuk Prediksi Kanker Payudara Azminuddin I. S. Azis; Irma Surya Kumala Idris; Budy Santoso; Yasin Aril Mustofa
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (881.95 KB) | DOI: 10.29207/resti.v3i3.1347

Abstract

Breast Cancer is the most common cancer found in women and the death rate is still in second place among other cancers. The high accuracy of the machine learning approach that has been proposed by related studies is often achieved. However, without efficient pre-processing, the model of Breast Cancer prediction that was proposed is still in question. Therefore, this research objective to improve the accuracy of machine learning methods through pre-processing: Missing Value Replacement, Data Transformation, Smoothing Noisy Data, Feature Selection / Attribute Weighting, Data Validation, and Unbalanced Class Reduction which is more efficient for Breast Cancer prediction. The results of this study propose several approaches: C4.5 - Z-Score - Genetic Algorithm for Breast Cancer Dataset with 77,27% accuracy, 7-Nearest Neighbor - Min-Max Normalization - Particle Swarm Optimization for Wisconsin Breast Cancer Dataset - Original with 97,85% accuracy, Artificial Neural Network - Z-Score - Forward Selection for Wisconsin Breast Cancer Dataset - Diagnostics with 98,24% accuracy, and 11-Nearest Neighbor - Min-Max Normalization - Particle Swarm Optimization for Wisconsin Breast Cancer Dataset - Prognostic with 83,33% accuracy. The performance of these approaches is better than standard/normal machine learning methods and the proposed methods by the best of previous related studies.
LL-KNN ACW-NB: Local Learning K-Nearest Neighbor in Absolute Correlation Weighted Naïve Bayes untuk Klasifikasi Data Numerik Azminuddin I. S. Azis; Budy Santoso; Serwin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (602.934 KB) | DOI: 10.29207/resti.v4i1.1348

Abstract

Naïve Bayes (NB) algorithm is still in the top ten of the Data Mining algorithms because of it is simplicity, efficiency, and performance. To handle classification on numerical data, the Gaussian distribution and kernel approach can be applied to NB (GNB and KNB). However, in the process of NB classifying, attributes are considered independent, even though the assumption is not always right in many cases. Absolute Correlation Coefficient can determine correlations between attributes and work on numerical attributes, so that it can be applied for attribute weighting to GNB (ACW-NB). Furthermore, because performance of NB does not increase in large datasets, so ACW-NB can be a classifier in the local learning model, where other classification methods, such as K-Nearest Neighbor (K-NN) which are very well known in local learning can be used to obtain sub-dataset in the ACW-NB training. To reduction of noise/bias, then missing value replacement and data normalization can also be applied. This proposed method is termed "LL-KNN ACW-NB (Local Learning K-Nearest Neighbor in Absolute Correlation Weighted Naïve Bayes)," with the objective to improve the performance of NB (GNB and KNB) in handling classification on numerical data. The results of this study indicate that the LL-KNN ACW-NB is able to improve the performance of NB, with an average accuracy of 91,48%, 1,92% better than GNB and 2,86% better than KNB.
IDENTIFIKASI AKUIFER MENGGUNAKAN METODE GEOLISTRIK RESISTIVITAS DI DAERAH BEBANDEM, KARANG ASEM, BALI Budy Santoso
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 19 No. 1 (2018): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1031.112 KB) | DOI: 10.24036/eksakta/vol19-iss1/101

Abstract

Bungaya Kangin Village, Bebandem District, Karangasem Regency, Bali Province consists of paddy fields and settlements, required therefore a water source / aquifer that can meet all these needs. One of the Geophysical Methods that can identify the aquifer is the Geoelectric Method. Geoelectric method used in this research is Resistivity Method. Data acquisition using Vertical Electrical Sounding (VES) and Electrical Resistivity Tomography (ERT) Methods. VES method is a method of measurement to determine the variation of resistivity vertically at one point. Electrical Resistivity Tomography (ERT) method is a method of measuring resistivity on soil surface / rock by using many electrode (51 electrode), to obtain sub-surface resistivity variation lateraly and verticaly, to obtain sub-surface image. The equipment used for geoelectric measurements is Resistivity Meter of Naniura NRD 300 Hf which has been equipped with a switchbox to adjust the displacement of 51 electrodes. Based on the resistivity modeling results, the aquifers in the study area were found in rough sandstones with resistivity values : (49 - 100) Ohm.m.
Stunting Literacy Strategy for the Community using a Website-Based Media Platform Budy Santoso; Yuliana Retnowati; Abubakar Sidik Katili; Margaretha Solang; Paulus Pangalo; Indra Domili; Novian Swasono Hadi
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 7 No 2 (2023): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Perkumpulan Dosen Indonesia Semesta (DIS) Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v7i2.721

Abstract

Stunting in toddlers is still a problem in Indonesia. Kalimas Village is one of the stunting village loci with a prevalence rate of 14.7 percent in Pohuwato District. Low community knowledge related to stunting and variations in complementary foods for children is one of the triggers for the high stunting rate in this village. Therefore, it is necessary to increase understanding related to handling stunting and its prevention. One strategy to increase understanding is to provide learning contents to improve stunting literacy through the development of a website that contains comprehensive stunting education articles and videos. In addition, educational videos on processing local food into additional food that has nutritional value for stunted children are also provided. With this educational website, the village can also publicize the potential of the village so that it can develop the existing village potential.
Klasifikasi Malware Menggunakan Teknik Machine Learning Evan Valdis Tjahjadi; Budi Santoso; Serwin
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v2i1.525

Abstract

Abstract Computer networks connected to the Internet can access information from all over the world very easily. However, the connection between the network and the Internet increases the potential for system failure. One of the methods that can be used in machine learning is the random forest algorithm method. Random forest is one of the methods in machine learning that is used to solve clarification problems. Based on the problems, it is necessary to classify malware where data is taken from malware datasets to make it easier to learn and distinguish the types of malware. The process consists of collecting datasets, pre-processing, training machine learning, and testing model performance. This study aims to find out the performance of Machine Learning using a random forest algorithm for malware- random forest classification. In this process, pre-processing of data is done by installing several Python libraries. Pandas is an open-source Python library that is usually used for data analysis needs. The model is trained on a dataset with various features and the results show a high accuracy of 99%. The random forest model provides excellent results without preprocessing the data. The results are good even if the data is not balanced. There is no need to use any technique to balance it. Scaling is not necessary. The random forest model is a recursive partitioning model that depends on data partitioning as it works on splitting the feature values and does not perform any calculations in it. The results indicate that the model has a precision of 0.99.
Pembuatan Briket dari Limbah Bongkol Jagung di Desa Bondawuna Kecamatan Suwawa Kabupaten Bone Bolango Irvan Salihi; Zohrahayaty Zohrahayaty; Budy Santoso; Swastiani Dunggio; Mochammad Sakir; Eka Zahra Solikahan
Empiris Jurnal Pengabdian Pada Masyarakat Vol. 1 No. 1 (2023): Volume 1 Nomor 1 Oktober 2023
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59713/ejppm.v1i1.664

Abstract

Desa Bondawuna Kecamatan Suwawa Kabupaten Bone Bolango merupakan salah satu daerah yang penduduknya merupakan daerah penanaman jagung lokal petani khususnya kelompok pengolah, karena jagung mudah dikembangkan dan jagung merupakan produk penting dengan potensi yang luar biasa. Metode yang digunakan untuk mencapai tujuan tersebut adalah dengan pelatihan dan praktek dimana tongkol jagung diubah menjadi bahan bakar dengan cara dicampur dengan lem. Hal ini membuat bahan bakar tersebut cocok untuk digunakan dalam memasak, seperti menggunakan kompor atau oven sebagai pengganti kayu, minyak atau gas. Operasi ini berharap dapat menghasilkan bahan bakar arang dari limbah tongkol jagung sebagai alternatif pengganti kayu, minyak dan gas. Solusi yang diusulkan adalah mengajarkan/membimbing cara membuat briket arang dari bahan dasar tongkol jagung, kanji, saringan dan cetakan untuk membuat bahan bakar. Mitra kami dalam usaha ini adalah petani jagung di Desa Bondawuna Kecamatan Suwawa Kabupaten Bone Bolango. Melalui KKNT ini dapat membuat masyarakat di Desa Bondawuna mampu berinovasi dalam hal berwirausaha berbasis teknologi dengan mengelolah potensi yang ada di Desa tersebut seperti jagung yang tadinya bongkol jagung hanya di jadikan limbah sekarang menjadi sebuah produk briket yang mempunyai nilai ekonomi sehingga dapat menciptakan lapangan pekerjaan bagi diri sendiri, keluarga, masyarakat, dan lingkungan sekitar Bondawuna Village, Suwawa Subdistrict, Bone Bolango Regency is one of the areas where the population is a corn casing area for local farmers, especially processing groups, because corn is easy to develop and corn is an important product with extraordinary potential. The method used to achieve this goal is training and practice where corn cobs are converted into fuel by mixing it with glue. This makes the fuel suitable for use in cooking, such as using a stove or oven as a substitute for wood, oil or gas. This operation hopes to produce charcoal fuel from corncob waste as an alternative to wood, oil and gas. The proposed solution is to prohibit/guide how to make charcoal briquettes from the basic ingredients of corn cobs, starch, filtered and molds to make fuel. Our partners in this business are corn farmers in Bondawuna Village, Suwawa District, Bone Bolango Regency. Through this KKNT, the people in Bondawuna Village are able to innovate in terms of technology-based entrepreneurship by managing the potential that exists in the village, such as corn, which was previously only used as waste corn cob, now it is a briquette product that has economic value so that it can create jobs for themselves. themselves, their families, communities and the environment
Co-Authors Abdul Mannan Abubakar Sidik Katili Andi Bode Apriyanto Alhamad Ariawan Ariawan Asniwati Zainuddin Azminuddin I. S. Azis Eka Zahra Solikahan Evan Valdis Tjahjadi Indra Domili Irma Surya Kumala Idris Irvan A. Salihi Margaretha Solang Mochamad Sakir Novian Swasono Hadi Pangalo, Paulus Serwin Sunarto Taliki Swastiani Dunggio Syahrir Abdussamad Yasin Aril Mustofa YULIANA RETNOWATI Zohrahayaty