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All Journal Jurnal TAM (Technology Acceptance Model) Jusikom : Jurnal Sistem Komputer Musirawas Jurnal Informatika dan Rekayasa Elektronik Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pengabdian kepada Masyarakat Nusantara Dewantara Journal of Technology KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) Jurnal Komputer dan Teknologi (JUKOMTEK) Jurnal TAM (Technology Acceptance Model)
Armanto Armanto
Universitas Bina Insan, Lubuklinggau
Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Library & Information Science Social Sciences

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Pengukuran Tingkat Kelembapan Tanah Dan Suhu Berbasis Arduino Uno pada Kelompok Tani Karya Maju II (Dua) Armanto Armanto; Andri Anto Tri Susilo; Harma Oktavia Lingga Wijaya; Wisdalia Maya Sari
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 3 No. 4 (2022): Juni 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v3i4.4197

Abstract

Electronic technology has recently developed rapidly, almost all aspects of daily human life have been covered by equipment with electronic technology systems, both using analog and digital control systems. Measurement is very important in science, especially in engineering. Measurement plays an important role in helping human work. As a country with vast natural resources, agriculture has enormous potential as state revenue. In addition, the agricultural sector is one of the most important sectors that increase the economic growth of the Indonesian people. One of the most important factors in agriculture is the quality of agricultural land. The better the agricultural land, the agricultural output will also increase. Factors that affect the quality of agricultural land are soil moisture and temperature. The life of biological elements contained in the soil including hosts, pathogens, and other microorganisms which vary greatly is influenced by soil moisture factors. condition of agricultural land in the area of Air Satan village. farmers in the air satan village have difficulty monitoring soil fertility in agricultural areas in the air satan village area, therefore the author wants to develop a tool that functions to measure the level of soil moisture with the measurement results displayed using a 16x2 LC which can be directly seen in order to make it easier for farmers or farmer groups in monitoring soil moisture and temperature in the agricultural area of Airsatan Village.
Sistem Prediksi Pertumbuhan Ekonomi Kabupaten Musi Rawas, Kabupaten Musi Rawas Utara Dan Kota Lubuklinggau Dengan Metode Regresi Linier Andri Anto Tri S; Armanto Armanto; Harma Oktafia Lingga Wijaya; Wisdalia Maya Sari
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 3 No. 4 (2022): Juni 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v3i4.4198

Abstract

The economic condition of a region in each period can increase or decrease by looking at changes in goods and services. An increase in economic activity is a process of changing economic conditions that occur in an area on an ongoing basis to get to a better state for a certain period of time. Economic growth is a benchmark in achieving the development of economic conditions in a region so that it has an impact on increasing people's welfare. South Sumatra's economic growth in the first quarter of 2021 improved compared to the previous quarter. Similar to economic growth in South Sumatra Province, the districts and cities in it (Musi Rawas Regency, North Musi Rawas and Lubuklinggau City) also experienced ups and downs of economic growth. With the current ups and downs of economic growth, Musi Rawas Regency, North Musi Rawas and Lubuklinggau City need accurate information about the picture of economic growth in the future, this is intended to be able to prepare various policies or actions so that the level of the economy in Musi Rawas Regency, Musi North Rawas and Lubuklinggau City can be increased. Based on this problem, Musi Rawas Regency, North Musi Rawas and Lubuklinggau City need a prediction system in order to see a picture of economic growth in the future. The purpose of this study is to design a prediction system that can predict the rate of economic growth in Musi Rawas Regency, North Musi Rawas and Lubuklinggau City. The method used in the prediction system is a simple linear regression method, the use of a simple linear regression method in this study due to the limited time of the study and used to determine the direction of the relationship between the independent variable and the dependent variable, whether it has a positive or negative relationship and to predict the value of the dependent variable if the value of the independent variable increases or decreases.
Prediksi Pola Penjualan Barang pada UMKM XYZ dengan Metode Algoritma Apriori Harma Oktafia Lingga Wijaya; Andri Anto Tri. S; A Armanto; Wisdalia Maya Sari
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 3 No. 4 (2022): Juni 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v3i4.4200

Abstract

Through the development of information technology today, the need for clear and accurate information is needed in everyday life, so that information will become an important thing in society. Sometimes high information needs are not accompanied by the presentation of adequate information, often information through the mining process is expected to provide information that was previously hidden in the data warehouse so that it becomes important and valuable information [1]. Utilization of existing data in the information system to support decision-making activities, it is not enough to just rely on operational data, a data analysis is needed to explore the potential of existing information. Decision makers try to take advantage of existing data warehouses to explore useful information to help make decisions, this encourages the emergence of new branches of science to overcome the problem of extracting important or interesting information or patterns from large amounts of data, which is called data mining. 2]. MSME XYZ is one of the leading MSMEs in Lubuklinggau City where this MSME sells various kinds of durian products such as tempoyak, lempok durian, peeled durian, durian pancakes, durian ice cream, durian coffee, durian seed chips etc. Every day MSME XYZ carries out activities such as sales transactions, providing product stock and so on, from the existing sales data so far XYZ has not been able to provide information about the pattern of customer spending habits so that transaction data cannot help leaders in making decisions from data collected. there is. Association analysis or association rule mining is a data mining technique to find the rules of a combination of items. One of the stages of association analysis that has attracted the attention of many researchers to produce efficient algorithms is high frequency pattern analysis (frequent pattern mining). The output of data mining can be used to improve decision making in the future.
Sentiment Analysis of User Reviews of Kitalulus Job Search App on Google Play Store Using Machine Learning Astrid Ayuzi Putri Hendri Hariadi; Bunga Intan; Armanto
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2220

Abstract

This study seeks to assess the sentiment of user reviews for the "KitaLulus" job search app found on the Google Play Store, utilizing Machine Learning techniques. Given the intensifying competition within the job market, this application serves as a crucial resource for job seekers in Indonesia. The study employs a sentiment analysis method to categorize user reviews into three groups: positive, negative, and neutral. The dataset comprises 20,000 reviews in Indonesian gathered from the Google Play Store. The methodologies used in this study include K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Logistic Regression, and Naïve Bayes. The findings indicate that various algorithms demonstrate different levels of accuracy in sentiment classification. It is anticipated that the outcomes of this analysis will offer valuable insights to developers about the quality and effectiveness of the "KitaLulus" application, while also assisting users in making informed decisions prior to utilizing the app. Additionally, this research contributes to the domain of sentiment analysis, particularly concerning job search applications in Indonesia.
Deteksi Serangan Man-In-The-Middle (MITM) Berbasis Machine Learning pada Dataset CIC IIOT 2025 Vera Deska; Armanto Armanto; Elmayati Elmayati
Dewantara Journal of Technology Vol. 6 No. 2 (2026)
Publisher : Akademi Teknologi Industri Dewantara Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59563/djtech.v6i2.317

Abstract

Keamanan komunikasi data pada ekosistem Industrial Internet of Things (IIoT) menjadi sangat rentan terhadap serangan Man-In-The-Middle (MITM), di mana penyerang secara diam-diam menyadap atau memanipulasi lalu lintas data antar perangkat. Serangan ini sangat berbahaya dalam lingkungan industri karena dapat menyebabkan kesalahan instruksi pada mesin yang berujung pada kerusakan fisik. Penelitian ini bertujuan untuk mengimplementasikan model machine learning yang mampu mendeteksi keberadaan anomali MITM secara presisi. Dengan menggunakan dataset CIC IIoT 2025, penelitian ini menganalisis fitur-fitur jaringan yang paling representatif terhadap perilaku serangan spoofing dan interception untuk membangun sistem deteksi yang responsif. Metodologi penelitian ini mencakup tahapan preprocessing, penanganan ketidakseimbangan data, klasifikasi, dan evaluasi model. Pada tahap preprocessing dilakukan ekstraksi fitur, pembersihan data, dan normalisasi data. Jika terdapat ketidakseimbangan kelas, teknik SMOTE dapat digunakan untuk menyeimbangkan distribusi data. Selanjutnya, proses klasifikasi dilakukan menggunakan algoritma Decision Tree, Random Forest, dan Support Vector Machine (SVM). Evaluasi model dilakukan dengan metrik accuracy, precision, recall, f1-score, confusion matrix, serta AUC-ROC. Penggunaan dataset CIC IIoT 2025 memberikan keunggulan karena memuat data trafik yang relevan dengan protokol industri terbaru, sehingga hasil model memiliki validitas yang lebih tinggi. Hasil penelitian menunjukkan performa deteksi yang optimal dengan nilai False Acceptance Rate (FAR) yang rendah. Kontribusi penelitian ini diharapkan dapat menjadi fondasi dalam pengembangan sistem keamanan otonom yang mampu melindungi integritas data pada infrastruktur IIoT dari ancaman penyusupan pihak ketiga.
SISTEM PERAMALAN PENJUALAN KOPI BUBUK SELANGIT MENGGUNAKAN METODE WEIGHTED MOVING AVERAGE (WMA) MENGGUNAKAN DATA TIME SERIES BERBASIS FRAMEORK CI (CODEIGNITER) Glen Jupiter; Armanto Armanto; Nelly Khairani Daulay
Jurnal Komputer dan Teknologi Vol 5 No 2 (2026): JUKOMTEK JULI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i2.706

Abstract

This study aims to forecast ground coffee sales using the Weighted Moving Average (WMA) method to support decision-making in business planning. The WMA method was selected because it assigns greater weight to recent historical data, thereby enabling a more responsive capture of changes in sales trends. The results indicate that ground coffee sales are projected to experience a stable upward trend in 2025. The model achieved a high level of accuracy, yielding a MAPE of 0.098%, an MAE of 54.463, and an RMSE of 70.683. Although discrepancies occurred in certain periods due to high sales volatility, the WMA method generally tracked actual data patterns effectively and produced realistic estimates. Consequently, the WMA method is a suitable tool for sales forecasting to support production planning, inventory control, and the formulation of more effective sales strategies.
Co-Authors Ahmad Sobri Andri Anto Tri Susilo, Andri Anto Astrid Ayuzi Putri Hendri Hariadi Budi Santoso Bunga Intan Elmayati Elmayati Glen Jupiter Harma Oktavia Lingga Wijaya Lingga Wijaya, Harma Oktafia Muhammad Husein Nelly Khairani Daulay Nelly Khairani Daulay Novi Lestari Satrianansyah Susanto Taufik Rahman Vera Deska Wisdalia Maya Sari Wisdalia Maya Sari