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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Informatika Pertanian Techno Nusa Mandiri : Journal of Computing and Information Technology ILKOM Jurnal Ilmiah KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) METIK JURNAL Jurnal Informatika Kaputama (JIK) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Mulia International Journal in Science and Technical JATI (Jurnal Mahasiswa Teknik Informatika) Science Midwifery JUKI : Jurnal Komputer dan Informatika Jurnal Sistem Informasi dan Sains Teknologi Jurnal Teknik Informatika (JUTIF) Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Arsitekno Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer Jurnal Tika Multica Science and Technology Andalasian International Journal of Applied Science, Engineering, and Technology Mejuajua Brilliance: Research of Artificial Intelligence AJAD : Jurnal Pengabdian kepada Masyarakat TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi International Review of Practical Innovation, Technology and Green Energy (IRPITAGE) Jurnal Ilmu Gizi dan Dietetik Journal Of Artificial Intelligence And Software Engineering Jurnal Malikussaleh Mengabdi Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Jurnal Solusi Masyarakat Dikara The Indonesian Journal of Computer Science Asian Journal of Science Education
Mutammimul Ula
Universitas Malikussaleh
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Journal : Multica Science and Technology

 1 
APPLICATION OF CLUSTERING GROUPS IN DETERMINING LAND SUITABILITY Angga Pratama; Salamah Salamah; Mutammimul Ula; Nadya Hayana
Multica Science and Technology Vol 1 No 2 (2021): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v1i2.281

Abstract

The problem of the suitability of planting land for planting types of plants is still a lot of unresolved farmers. land at the beginning of land selection is very decisive. This is to determine whether the land is productive or not. in the future is the result that farmers will experience considerable losses if this is not estimated, therefore a model is needed to know and estimate accurately whether the land or land is suitable for planting crops or not. The purpose of this study is that farmers do not experience losses and losses on land when planting crops on available land. So that it can improve the quality of food in Aceh and can improve the welfare of farmers. The result of the research is that it can be found a Clustering model or grouping of plant stock types using the k-medoid model, finally the application of this clustering model is able to provide a solution for the Office. Based on calculations using the K-Medoids method obtained for land compliance in North Aceh Regency is Corn with an adjustment of 53.6%, Peanuts 17.9%, Soybeans 14.3%, Bulbs 10.7% and the suitability for rice is 3 ,6%.
APPLICATION OF INTELLIGENT SYSTEM WITH BACKPROPAGATION MODEL IN CLOUD IMAGE CLASSIFICATION Mulyadi Mulyadi; Ichwan, Muhammad; Rizka, Muhammad; Ula, Mutammimul
Multica Science and Technology Vol 2 No 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.323

Abstract

The clouds have different patterns on each type and each type has different properties. The introduction of the type, shape, and nature of the cloud is indispensable in the weather forecasts so that the clouds can be classified. There are several methods used in the image classification process that is the method of the artificial neural network Backpropagation. The method of Backpropagation is one of the methods used for the classification process, in this research Backpropagation used on the training and testing process for the introduction of cloud imagery aimed at determining the type of cloud, before the second These stages are carried out imagery through the preprocessing process. From the training conducted using the Backpropagation method shows that this method generates the best weight value and saves that value into the database to do the testing process using a neural network Backpropagation. In addition, Backpropagation also has the ability to reduce errors by continuously correcting the weight until reaching the maximum target. Data used for training data as many as 92 cloud type image with each type of 10 imagery. In this study obtained a system success rate of 60.6%.
IMPLEMENTATION OF MACHINE LEARNING USING THE K-NEAREST NEIGHBOR CLASSIFICATION MODEL IN DIAGNOSING MALNUTRITION IN CHILDREN Mutammimul Ula; Ananda Faridhatul Ulva; Ilham Saputra; Mauliza Mauliza; Ivan Maulana
Multica Science and Technology Vol 2 No 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.326

Abstract

The problem faced today is the lack of nutrition for children which causes stunting. One way to prevent stunting problems is to provide input to the community in Aceh for the importance of providing adequate nutrition for children. This study classifies toddlers who are identified as stunting with the K-NN model technology which is modeled in machine learning, the results are grouped. The purpose of this study was to determine the detection of malnutrition in toddlers and to classify data on malnutrition in toddlers using the k-means clustering method and the system that was built could be used as a reference to monitor the growth and development of children. Then in classifying malnutrition in children based on the results of the nutritional status criteria in toddlers, it can be known based on the index of Body Weight for Age (W/U), Height for Age (TB/U), and Weight for Height (W/TB). by entering data values ​​from weight, height and gender of toddlers. The purpose of this study was to determine the detection of malnutrition under five at the Cut Meutia Hospital Kab. North Aceh. The process in the initial data analysis of Mr. ID, baby's name, gender, age, weight (kg), height (cm), the data to be classified for training data are 40 children in each region / village. In the assessment of nutritional status, it is classified as Malnutrition less than 3 SD or 70%, Malnutrition - 3 SD to < - 2 SD or 80%, Good Nutrition -2 SD to +2 SD, Over Nutrition >+2 SD. The results of the final score obtained are euclidean distance with a value of 1.3 with a ranking of malnutrition, age 1.6 months, weight (weight) 0.852, TB (height) 4.556 with euclidean distance with a value of 1.3 with a low ranking. For the second test data, age is 2.8 months, BB (weight) 0.222, TB (height) 4.556 with Euclidean distance with a value of 1.3 with a good rating of 0.778. The results of this study can be classified in children to children for each region in each region, village and sub-district of each Puskesmas in North Aceh Regency
APPLICATION OF MACHINE LEARNING IN PREDICTING CHILDREN'S NUTRITIONAL STATUS WITH MULTIPLE LINEAR REGRESSION MODELS Mutammimul Ula; Ananda Faridhatul Ulva; Mauliza; Muhammad Abdullah Ali; Yumna Rilasmi Said
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.363

Abstract

Forecasting is an important part of making plans and making decisions that can predict future events. Forecasting techniques in this study used multiple linear regression. This study aims to predict the number of cases of child nutritional status in children in each region. The purpose of this study was to see the results of predicting the number of children's nutritional status in each region and to make it easier to predict children's nutrition. The research method includes the analysis of the system built and the design of machine learning applications using the Multiple Linear Regression method. Then the system built can help predict the nutritional status of children in Aceh quickly, precisely, and accurately. The data used is data on the nutritional status of children in 2018, 2019, and 2020. Based on the results of forecasting for 2021 based on data obtained in previous years, the predicted results of total nutritional status in 2021 are 449,0912126. The results of this study indicate that the linear regression method obtains the best model results by being able to predict the implementation of machine learning.
LAMP MODIFICATION FROM HPLN TO LED TECHNOLOGY FOR SAVING ELECTRICAL ENERGY IN STREET LIGHTING Rosdiana Rosdiana; Arya Wiyangga Pradana; Muhammad Muhammad; Mutammimul Ula
Multica Science and Technology Vol 3 No 1 (2023): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v3i1.423

Abstract

Energy Efficiency is a business that is carried out with the aim of reducing the amount of energy needed, in using an equipment or even an energy-related system. In its development in the field of lighting, LED (Light Emitting Diode) lamps are now starting to be used as lighting lamps for homes, industries and factories. In Indonesia, the use of LED lamps in lighting is still rarely used, because the price of LED lamps is quite expensive when compared to ordinary lamps. With the saving of electric power through the use of LED lights, the problem of operational costs will be easy to overcome. Indeed, the price of this LED lamp is a little expensive, but with the research on the comparison of the use of this LED lamp with HPL-N type lamps, the industry will consider using this LED lamp with a generally accepted application method to reduce energy expenditure. The previous conditions for Jalan Dolok Merawan used HPLN 250 Watt lamps with a handlebar angle of 24,920 ornaments, the resulting light intensity was 2189 Candela, the intensity of the resulting lighting was 97.94 Lux and has now been changed to make it more optimal to use 120 Watt LED type lights, the height of the pole used is 4 meterss with an ornament handlebar angle of 24.920, light intensity of 1242 Candella, lighting intensity of 55.33 lux. The results of this illumination intensity are in accordance with the standard determined by BSN SNI regarding Collector road class 3-7 Lux. The results achieved after the process of modifying HPL-N lamps to LEDs are that they can reduce the use of electrical energy in the lighting system and achieve efficiency for electric power consumption so that they can provide added value to the company in reducing the company's operational costs.
Naïve Bayes Classification Algorithm Application on Nutritional Status of Pregnant Women in Lhokseumawe City Ilham Sahputra; Difa Angelina; Mutammimul Ula
Multica Science and Technology Vol 4 No 1 (2024): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v4i1.851

Abstract

The nutritional status of pregnant women is a measure of success in fulfilling nutrition for pregnant women. Poor nutritional status of pregnant women will cause an imbalance of nutrients which can cause nutritional problems in pregnant women. Therefore, we need a system that can predict the nutritional status of pregnant women. This can be implemented by utilizing the naïve Bayes classification algorithm. This research was carried out with the aim of further studying how to apply the Naïve Bayes algorithm to predict the nutritional status of pregnant women, and how the success of this application is based on the accuracy value of the resulting calculations. Based on data on the prevalence and condition of pregnant women in Lhokseumawe and calculations using a series of formulas for mean, standard deviation, probability, and gaussian values, it was found that 50 pregnant women were predicted to have normal nutritional status, while 19 others had nutritional status. not enough. From the results of the accuracy carried out, it was found that the error value (error) of the application used was 48% while the accuracy value of the application was 53% or low. That way, the calculation formula developed in this study needs to be further developed to encourage the accuracy of the application made so that the application results are reliable in real life.
Co-Authors - Fakhrurrazi -, Badriana -, Bakhtiar ., Muthmainah Abdi Zulfikri Achmad Rizal, Reyhan Ade Irfan Ade Luky Setiawan Agi Ayu Nurdianta Barus Akbar, Muhammad Zulfat Amri, Fajar Ananda Faridhatul Ulva Andik Bintoro Angga Pratama Angga Pratama Ar Razi Arief Rahman Arnawan Hasibuan Arpika, Asma Mauli Arya Wiyangga Pradana Asma Mauli Arpika Asmawi Asran Asrianda Asrianda Azhari SN Badriana, Badriana Bakhtiar Bakhtiar Bambang Suhendra Barus, Agi Ayu Nurdianta Budi Setiawan Burhanuddin Burhanuddin Burhanuddin Burhanuddin Burhanuddin Burhanuddin Bustami Bustami Bustami Cut Agusniar Cut Dewi Aida Soraya Cut Ita Erliana Dewi, Apriandini Sri Difa Angelina Edi Yusuf Adiman Elfiana Emi Maulani Eri Saputra Ericky Benna Perolihin Manurung Ermatita - Ermatita Ermatita Eva Darnila Eva Darnila eva darnila, eva darnila Ezwarsyah Ezwarsyah Fachrurrazi Fachrurrazi Fadillah, Tengku Farhan Fadliani Fadlisyah Fadlisyah Fadlisyah Fahrizal, Effan Fahrozi, Fazar Fahrozi, Mahlil Fajar Tri Tri Anjani Fajriana, Fajriana Fakhrurrazi Fakrurrazi Fakrurrazi Fakrurrazi Fasdarsyah Fathia Fauzi, Sri Wahyuni Febryanda, Inne Fidyatun Nisa Fitriana Fitriana Fitrianti, Uli Fuadi, Wahyu Fyanda, Dwi Auji Gita Perdinanta Hadi Riyadi Hafizh Al Kautsar Aidilof Harun, Rofiq Hasbi, Maulida ilham - sahputra Ilham Sahputra Ilham Sahputra Ilham Sahputra Ilham Sahputra Ilham Saputra Ilham Saputra Ilham Saputra Ilham Saputra Ilham Saputra Iramadhani, Dwi Irhamna, Ayu Irma Yurni Irma Yurni Irwansyah, Defi Iswadi Iswadi Ivan Maulana Iwan Pahendra Iwan Pahendra Iwan Pahendra Anto Saputra Juandana, Rio Adian Juniwan Ginting Laila, Dwi Nur'aini Mahdaliana, Mahdaliana Maryana Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza, Ade Mauliza, Mauliza Mochamad Ari Saptari Muarif Qumar Muhammad Abdullah Ali Muhammad Abdullah Ali Muhammad Danil Muhammad Fauzan Muhammad Ichwan Muhammad Ikhsan Muhammad Ikhwani Muhammad Muhammad Muhammad Rahmad Zainal Muhammad Rizka, Muhammad Muhammad Sadli Muhammad, Muhammad Multazam, T Mulyadi Mulyadi Munirul Ula Muthmainnah Muthmainnah Mutmainnah Mutmainnah Nadya Hayana Nasriah Nasriah Nasriah Nasriah Nayla Husna, Siti Nur Faliza Nur Hafni Nurdin Nurdin Nurfebruary, Nanda Sitti Nuri Aslami Nurmalina Nurmalina, Nurmalina Pahendra, Iwan Purba, Nur Alfi Rahma Fitria, Rahma Rahmat Kurniawan Rayhan Rahul Mutuahmi Razif Razif Renardi, Renardi Reyhan Achmad Rizal Reyhan Achmad Rizal Reyhan Achmad Rizal Ria Zulhusna Richki Hardi Ridha Maulana Ridwan Ridwan Risawandi, Risawandi Riyadhul Fajri Rizal Tjut Adek Rizal, Reyhan Achmad Rizki Putra Fhonna Rizky Putra Fhonna Rizky Putra Phonna Rizky Zuliyansyah Rosdian dian rosdian rosdian, Rosdian dian Rosdiana Rosdiana Rosdiana Rosdiana Rosya Afdelina Rozzi Kesuma Dinata Safriana Safriana Sahputra, Ilham Salahuddin Salahuddin Salahuddin Salamah Salamah Salamah Salamah Salamah Saptari, Mochamad Ari Satriawan, Ivan Sayed Fachrurrazi Sayed Fachrurrazi Setiawan, Ade Luky Shayravi Shayravi Shayravi, Shayravi Siregar, Dinda Saima Agustina Siti Aminah Siti Atikah Nabila Suheri Sujacka Retno Suriyanto Suriyanto Susanti Susanti syarifah asria nanda, syarifah asria Syibral Malasyi Syukriah Syukriah Syukriah Syukriah Tengku Farhan Fadillah Teuku Zulkarnaen Tiara Razaqa Sakinah Tsania Asha Fadilah Daulay Ulva , Ananda Faridhatul Umaruddin Usman Vera Novalia Veri Ilhadi Wahyu Fuadi Yella Cinni Ujung Yuli Asbar Yulisda, Desvina Yumna Rilasmi Said Yumna Rilasmi Said Yusniar Yusniar Zahratul Fitri Zahratul Fitri Zahratul Fitri, Zahratul Zainal Abidin Zikrina Zikrina Zul Akli Zulfikri, Abdi Zuraida Zurhijjah Zurhijjah