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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Analitika : Jurnal Magister Psikologi UMA Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Informatika MEANS (Media Informasi Analisa dan Sistem) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Media Informatika Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT
Hasibuan, Mila Nirmala Sari
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Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Library & Information Science Mathematics Physics Public Health Social Sciences Other

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PERBEDAAN ANTARA KECERDASAN DAN KESADARAN MORAL SISWA SMA SEDERAJAT DITINJAU DARI JENIS KELAMIN DAN JENIS SEKOLAH muti ah, rahma; Rohana, Rohana; Saragih, Siti Zahara; Hasibuan, Mila Nirmala
Analitika: Jurnal Magister Psikologi UMA Vol 11, No 2 (2019): ANALITIKA DESEMBER
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1005.103 KB) | DOI: 10.31289/analitika.v11i2.2710

Abstract

Stigma yang ada di masyarakat beranggapan bahwa siswa kejuruan (SMK) lebih sering melakukan tindakan pelanggaran moral daripada siswa sekolah umum (SMA/MA). Umumnya pelanggaran moral terjadi karena tingkat kesadaran moral dan kecerdasan moral siswa rendah. Untuk itu dilakukan penelitian yang bertujuan melihat (1) apakah ada perbedaan kesadaran moral siswa laki-laki dan perempuan, (2) apakah ada perbedaan kesadaran moral siswa kejuruan (SMK) dan siswa sekolah umum (SMA/MA), (3) apakah ada perbedaan kecerdasan moral siswa laki-laki dan perempuan, (4) apakah ada perbedaan kecerdasan moral siswa kejuruan (SMK) dan siswa sekolah umum (SMA/MA). Populasi yang digunakan adalah seluruh siswa kelas X SMA/MA/SMK yang ada di Kabupaten Labuhanbatu yang berjumlah 46 sekolah dengan jumlah siswa adalah ± 6.128 siswa. Sedangkan sampel dalam penelitian ini menggunakan teknik Random Sampling dan penentuan jumlah sampel menggunakan rumus slovin sehingga diperoleh jumlah sampel dalam penelitian ini adalah 346 siswa. Alat pengumpul data menggunakan angket dan analisis data menggunakan uji parametrik yaitu Uji Independent Sample t test. Berdasarkan hasil penelitian diperoleh bahwa dari empat hipotesis yang diajukan ada dua hipotesis yang diterima yaitu (1) kesadaran moral perempuan lebih tinggi daripada kesadaran moral laki-laki dengan nilai signifikansi < 0.05, (2) Terdapat perbedaan kesadaran moral antara siswa yang berasal dari  sekolah umum (SMA/MA) dan sekolah kejuruan (SMK). (3) Tidak terdapat perbedaan kecerdasan moral antara siswa laki-laki dan siswa perempuan. (4) tidak terdapat perbedaan kecerdasan moral antara siswa yang berasal dari  sekolah umum (SMA/MA) dan sekolah kejuruan (SMK).
PENGARUH PERILAKU INOVATIF TERHADAP KOMPETENSI MANAJERIAL KEPALA SEKOLAH DASAR DI KABUPATEN LABUHAN BATU Siregar, Marlina; Situmorang, Benyamin; Rohana, R.; Adi, Panggih Nur; Hasibuan, Mila Nirmala Sari; Kartikaningsih, Reni
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol 4, No 2: July 2020
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (464.826 KB) | DOI: 10.36312/e-saintika.v4i2.190

Abstract

Penelitian ini bertujuan untuk menggambarkan pola hubungan antar variabel yang dilibatkan berdasarkan data empirik yang dikumpulkan dengan menggunakan instrumen yang dikembangkan. Penelitian ini merupakan penelitian kualitatuf yang dilaksanakan di Kabupaten Labuhanbatu selama 4 (empat) bulan terhitung mulai Juli  2019 hingga Oktober  2019. Adapun Populasi target  dalam  penelitian ini adalah kepala Sekolah Dasar Negeri di Kabupaten Labuhanbatu sebanyak 241 sekolah. Instrumen yang digunakan mengumpulkan data variabel perilaku inovatif, dikembangkan dan diuji cobakan  terlebih dahulu untuk menguji validitas dan reliabilitasnya sedangkan variabel kompetensi manajerial  kepala sekolah menggunakan instrumen yang telah ada yang diambil dari dokumen milik Dinas Pendidikan sehingga tidak dilakukan uji validitas dan reliabilitas. Hasil dari penelitian ini diketahui dari hasil olah data perilaku inovatif kepala sekolah diperoleh  nilai Mean = 68.37 dan Standar Deviasi = 13.739. Untuk mengidentifikasi kecenderungan atau pengkategorian tingkatan perilaku inovatif kepala sekolah berdasarkan nilai mean  dan standar deviasi. Berdasarkan hasil penelitian dapat disimpulkan bahwa Perilaku Inovatif berpengaruh terhadap Kompetensi Manajerial.The Effect of Innovative Behavior on Managerial Competence of Primary School Principals in Labuhan Batu DistrictAbstractThis study aims to describe the pattern of relationships between variables involved based on empirical data collected using the developed instrument. This research is a quality study conducted in Labuhanbatu Regency for 4 (four) months from July 2019 to October 2019. The target population in this study is the Principal of State Elementary Schools in Labuhanbatu Regency as many as 241 schools. The instrument used to collect innovative behavioral variable data was developed and tested first to test its validity and reliability while the managerial competency variable of principals used existing instruments taken from documents belonging to the Department of Education so that validity and reliability tests were not carried out. The results of this study are known from the results of the school principal's innovative behavior data obtained by the Mean value = 68.37 and Standard Deviation = 13.739. To identify trends or categorizing the level of innovative behavior of principals based on the mean and standard deviation. Based on the results of this study concluded that Innovative Behavior affects Managerial Competence.
Pengaruh Perilaku Inovatif terhadap Kompetensi Manajerial Kepala Sekolah Dasar di Kabupaten Labuhan Batu Siregar, Marlina; Situmorang, Benyamin; Rohana, R.; Adi, Panggih Nur; Hasibuan, Mila Nirmala Sari; Kartikaningsih, Reni
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 4 No. 2: July 2020
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/e-saintika.v4i2.190

Abstract

Penelitian ini bertujuan untuk menggambarkan pola hubungan antar variabel yang dilibatkan berdasarkan data empirik yang dikumpulkan dengan menggunakan instrumen yang dikembangkan. Penelitian ini merupakan penelitian kualitatuf yang dilaksanakan di Kabupaten Labuhanbatu selama 4 (empat) bulan terhitung mulai Juli  2019 hingga Oktober  2019. Adapun Populasi target  dalam  penelitian ini adalah kepala Sekolah Dasar Negeri di Kabupaten Labuhanbatu sebanyak 241 sekolah. Instrumen yang digunakan mengumpulkan data variabel perilaku inovatif, dikembangkan dan diuji cobakan  terlebih dahulu untuk menguji validitas dan reliabilitasnya sedangkan variabel kompetensi manajerial  kepala sekolah menggunakan instrumen yang telah ada yang diambil dari dokumen milik Dinas Pendidikan sehingga tidak dilakukan uji validitas dan reliabilitas. Hasil dari penelitian ini diketahui dari hasil olah data perilaku inovatif kepala sekolah diperoleh  nilai Mean = 68.37 dan Standar Deviasi = 13.739. Untuk mengidentifikasi kecenderungan atau pengkategorian tingkatan perilaku inovatif kepala sekolah berdasarkan nilai mean  dan standar deviasi. Berdasarkan hasil penelitian dapat disimpulkan bahwa Perilaku Inovatif berpengaruh terhadap Kompetensi Manajerial.The Effect of Innovative Behavior on Managerial Competence of Primary School Principals in Labuhan Batu DistrictAbstractThis study aims to describe the pattern of relationships between variables involved based on empirical data collected using the developed instrument. This research is a quality study conducted in Labuhanbatu Regency for 4 (four) months from July 2019 to October 2019. The target population in this study is the Principal of State Elementary Schools in Labuhanbatu Regency as many as 241 schools. The instrument used to collect innovative behavioral variable data was developed and tested first to test its validity and reliability while the managerial competency variable of principals used existing instruments taken from documents belonging to the Department of Education so that validity and reliability tests were not carried out. The results of this study are known from the results of the school principal's innovative behavior data obtained by the Mean value = 68.37 and Standard Deviation = 13.739. To identify trends or categorizing the level of innovative behavior of principals based on the mean and standard deviation. Based on the results of this study concluded that Innovative Behavior affects Managerial Competence.
Content-Based Image Retrieval for Songket Motifs using Graph Matching Yullyana, Yullyana; Irmayani, Deci; Hasibuan, Mila Nirmala Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11411

Abstract

Indonesia is a country that has abundant cultural wealth. One of the characteristics of Indonesian culture is Songket. Songket is a typical Malay woven cloth that has many variants of motifs, each of which represents a different meaning and philosophy. Songket is often found in Sumatra Island with different motifs in each region. With so many types of songket motifs, not everyone can recognize and distinguish between one songket motif and another, even Indonesian citizens themselves. With the help of computers, it is easier to find information about a songket motif or to find a similar songket motif. The field that can play a role in solving this problem is Content-Based Image Retrieval (CBIR). This study aims to carry out a content retrieval process on the songket core motif using graph matching-based processing. In this study, the method used is felzenzswalb segmentation, and graph matching through the VF2 isomorphism algorithm and graph edit distance. The number of songket core motif images used as data is 180 data in the form of color images measuring 64 x 64 pixels. Based on the results of the study, it was found that the optimal graph matching algorithm and parameters in this study were the VF2 algorithm for artificial images with an f-1 score of 91.05%, and Graph Edit Distance with GED≤8 parameters for songket motif images with an f1-score. by 53.36%.
Forecasting Health Sector Stock Prices using ARIMAX Method Aprilianto, Muhammad; Hasibuan, Mila Nirmala Sari; Harahap, Syaiful Zuhri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11418

Abstract

In daily stock trading activities, stock prices can experience ups and downs. The rise and fall of stock prices occurs due to changes in supply and demand for these shares. The COVID-19 pandemic did not have a negative effect, instead it had a positive impact on stock prices in health companies. companies in the health sector experienced a fairly good profit of 10.46% in the fourth quarter of 2021. This fact made investors interested in buying shares in companies in the health sector in the hope of selling them when demand increased, resulting in doubled profits. Stock conditions continue to fluctuate every day, making investors need to pay attention and study the past data of the health sector company that will be selected before deciding to invest. Therefore, it is necessary to forecast stock prices in the health sector for the next several periods as a step in making investment decisions. The health sector companies that will be modeled are PT Kimia Farma (Persero) Tbk and PT Kalbe Farma Tbk. The method used in this study is the ARIMAX model. The test and analysis results show that based on the RMSE and MAPE values, the best model is ARIMAX(5,13) for PT Kalbe Farma Tbk shares with a MAPE value of 1% in in-sample data and 0.6% in out-sample data.
Comparative analysis of resampling techniques on Machine Learning algorithm Amelia, Tri Suci; Hasibuan, Mila Nirmala Sari; Pane, Rahmadani
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11427

Abstract

Generally, classification algorithms in the field of data science assume that the classes of training data are equally distributed. However, datasets on real problems often have an unbalanced class distribution. Unbalanced dataset classes make up the majority class and the minority class. In general, minority classes are more attractive and more important to identify. In this case, the correct classification for the minority class sample is more valuable than the majority class. The unbalanced class distribution causes the classification algorithm to have difficulty in classifying minority class samples correctly. If the performance of the algorithm model is good for the majority class sample but bad for the minority class then this imbalance problem is a crucial thing to be addressed. Many solutions are offered for this problem, namely by oversampling techniques in the minority class and/or undersampling techniques in the majority class. In this study, the authors tried various sampling techniques and tested them on various machine learning classification algorithms to find out the combination of resampling techniques and algorithms that have high recall in classifying minority class samples and still considering the majority class classification.
Implementation of the K-Nearest Neighbor (kNN) Method to Determine Outstanding Student Classes Munazhif, Nanda Fahrezi; Yanris, Gomal Juni; Hasibuan, Mila Nirmala Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12227

Abstract

Education being one factor supporting students / I to be able to increase their knowledge. Each student has their own potential that they have obtained in the world of education. Therefore, every school has created an education program that functions to increase the potential of high achieving students. The program is a flagship class program. What is meant by a superior class program is a process of selecting and classifying students to be placed in the classroom superior (grade student / I achievement). Therefore, this study aims to implement classification on student data using the KNearest Neighbor (kNN) algorithm. K-Nearest Neighbor (kNN) is a method used to classify data based on training data (data set). The data that the writer will use is student data of 60 student data. In this classification using the kNN method aims to classify data on students who are eligible to enter the superior class (class of outstanding students). The first step is the process of determining data requirements. Then cleaning or pre-processing and the next is to design a widget model of the kNN method on the orange application to carry out the data classification process. The test results using 60 student data using the KNN method and using the Confusion Matrix obtained an Accuracy value of 91.6%, then a Precision value of 89.2% and a Recall value of 92.5%. The conclusion is that this study succeeded in obtaining a method that the best and also get the best results for Classification of superior student classes.
Analysis of Visitor Satisfaction Levels Using the K-Nearest Neighbor Method Violita, Putri; Yanris, Gomal Juni; Hasibuan, Mila Nirmala Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12257

Abstract

Visitors are people who come to a place, entertainment, shopping, and tourism. Visitors are one of the important factors for the progress and development of a place. With visitors, an entertainment, tourism and shopping area can progress and develop. Therefore researchers will make a study of the level of visitor satisfaction. This research aims to improve the quality of an entertainment venue, shopping and increase the quantity of visitors. This research was conducted using the K-Nearest Neighbor method. The K-Nearest Neighbor method is a classification method based on training data (dataset). The data used by researchers is 45 visitor data. The classification carried out using the K-Nearest Neighbor method aims to classify data of satisfied visitors and dissatisfied visitors at an entertainment or tourism place. In using the K-Nearest Neighbor method, the first stage is selecting sample data, the data to be selected, then preprocessing, then designing the widget with the K-Nearest Neighbor method and finally testing data mining using the K-Nearest Neighbor method. The K-Nearest Neighbor Method. This visitor data was obtained by researchers through a questionnaire and the results of the questionnaire that 41 visitors were satisfied. After classifying visitor data using the K-Nearest Neighbor method, the classification results were 41 satisfied visitors. The conclusion is that many visitors are satisfied.
Analysis of the Neural Network Method to Determine Interest in Buying Pertamax Fuel Sari, Mayang; Yanris, Gomal Juni; Hasibuan, Mila Nirmala Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12292

Abstract

Fuel is one of the needs that is used by the community as a material to be used on motorcycles or cars. Fuel has become an important need for society, because when there is no fuel, a motorbike or car that is owned by someone cannot be used. Each vehicle has its own fuel, for motorbikes the fuel is pertalite, Pertamax, Pertamax Turbo and for cars the fuel is diesel and dexlite. For the fuel used in motorbikes, there are some people who are interested in Pertalite fuel and there are not many people who are interested in Pertamax fuel. So researchers will make a study of public interest in Pertamax fuel. This research will be made using the neural network method by classifying community data in data mining. This study aims to see the public's interest in purchasing Pertamax fuel. The research process was carried out with the initial stages of collecting and selecting data to be used, then preprocessing, then designing the neural network method and finally the testing process to obtain classification results using the neural network method. The results obtained from data classification using the neural network method state that there are 23 people who are interested in Pertamax fuel and 18 people who are not interested in Pertamax fuel. It turns out that many people are interested in Pertamax fuel.
Sentiment Analysis of Beauty Product Applications using the Naïve Bayes Method Rambe, Tiara Syavitri; Hasibuan, Mila Nirmala Sari; Dar, Muhammad Halmi
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12303

Abstract

The number of beauty products that appear on the market makes every producer compete in attracting consumers. One of the facilities provided by manufacturers to make it easier for consumers to shop is an online shopping application that can be accessed via gadgets. Where the feature of the application is the availability of user review services User reviews are often used as a recommendation for the product to be purchased. The more positive the reviews that appear, the greater the consumer's confidence to buy the product; conversely, the more negative the reviews that appear, the more reluctant consumers are to buy. This study aims to find out how much accuracy the Naïve Bayes algorithm has in conducting sentiment analysis on user reviews of beauty product applications with different combinations of training and test data. Furthermore, it is also important to know the frequency of words that often appear in the review. The sentiment class used is divided into three, namely, positive, negative, and neutral. This research method includes a number of stages, namely: data collection, data labeling, text pre-processing, data visualization, TF-IDF, sentiment analysis, etc., until the results are obtained. This research has produced the highest accuracy rate of 90.08% in the Naïve Bayes algorithm, with a composition of 90% training data and 10% test data. While the word that often appears in user reviews is "application," with a frequency of 446 occurrences, it is followed by the word "product," 444 times, and the word "price," 312 times. The greater the amount of training data used, the higher the level of accuracy resulting from the Naïve Bayes algorithm. Meanwhile, the greater the amount of test data used, the lower the resulting accuracy value.
Co-Authors Adi, Panggih Nur Ahra, Ahra Amelia, Tri Suci Aprilianto, Muhammad Arfi Pratama, Hubban Benyamin Situmorang Cantika, Putri Talia Ichlas, Al Indah Lestari, Indah Irmayani, Deci Iwan Purnama Kartikaningsih, Reni Manurung, Romtika Mayang Sari Muhammad Halmi Dar Munazhif, Nanda Fahrezi Munthe, Ibnu Rasyid Muti'ah, Rahma Nasution, Fitri Aini Nasution, Marnis Pane, Rahmadani Puji Rahayu Rambe, Tiara Syavitri Riyanto, Tiara Rohana, R. Sadina, Icha Dzulfahani Saragih, Siti Zahara Siahaan, Rahma Aulia Sihombing, Volvo Sinaga, Novica Handayani Siregar, Marlina Syaiful Zuhri Harahap Violita, Putri Yanris, Gomal Juni Yullyana, Yullyana